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You searched for subject:( Association rule mining). Showing records 1 – 30 of 13630 total matches.

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AUT University

1. Vithal Kadam, Omkar. Novel applications of Association Rule Mining- Data Stream Mining .

Degree: 2010, AUT University

 From the advent of association rule mining, it has become one of the most researched areas of data exploration schemes. In recent years, implementing association(more)

Subjects/Keywords: Data stream mining; Association rule mining

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Vithal Kadam, O. (2010). Novel applications of Association Rule Mining- Data Stream Mining . (Thesis). AUT University. Retrieved from http://hdl.handle.net/10292/826

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Vithal Kadam, Omkar. “Novel applications of Association Rule Mining- Data Stream Mining .” 2010. Thesis, AUT University. Accessed May 20, 2019. http://hdl.handle.net/10292/826.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Vithal Kadam, Omkar. “Novel applications of Association Rule Mining- Data Stream Mining .” 2010. Web. 20 May 2019.

Vancouver:

Vithal Kadam O. Novel applications of Association Rule Mining- Data Stream Mining . [Internet] [Thesis]. AUT University; 2010. [cited 2019 May 20]. Available from: http://hdl.handle.net/10292/826.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vithal Kadam O. Novel applications of Association Rule Mining- Data Stream Mining . [Thesis]. AUT University; 2010. Available from: http://hdl.handle.net/10292/826

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Lethbridge

2. University of Lethbridge. Faculty of Arts and Science. Two new approaches to evaluate association rules .

Degree: 2010, University of Lethbridge

 Data mining aims to discover interesting and unknown patterns in large-volume data. Association rule mining is one of the major data mining tasks, which attempts… (more)

Subjects/Keywords: Data mining; Association rule mining; Dissertations, Academic

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Science, U. o. L. F. o. A. a. (2010). Two new approaches to evaluate association rules . (Thesis). University of Lethbridge. Retrieved from http://hdl.handle.net/10133/2530

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Science, University of Lethbridge. Faculty of Arts and. “Two new approaches to evaluate association rules .” 2010. Thesis, University of Lethbridge. Accessed May 20, 2019. http://hdl.handle.net/10133/2530.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Science, University of Lethbridge. Faculty of Arts and. “Two new approaches to evaluate association rules .” 2010. Web. 20 May 2019.

Vancouver:

Science UoLFoAa. Two new approaches to evaluate association rules . [Internet] [Thesis]. University of Lethbridge; 2010. [cited 2019 May 20]. Available from: http://hdl.handle.net/10133/2530.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Science UoLFoAa. Two new approaches to evaluate association rules . [Thesis]. University of Lethbridge; 2010. Available from: http://hdl.handle.net/10133/2530

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Anna University

3. Kanimozhiselvi C S. An investigation on automatic support thresholds for association rule mining.

Degree: Association rule mining, 2013, Anna University

The process of Knowledge Discovery in Database is aimed at extracting useful information from large databases. Among the several steps of Knowledge Discovery in Databases,… (more)

Subjects/Keywords: Knowledge Discovery; Data mining; Rule mining; Exact association rule

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

S, K. C. (2013). An investigation on automatic support thresholds for association rule mining. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/9847

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

S, Kanimozhiselvi C. “An investigation on automatic support thresholds for association rule mining.” 2013. Thesis, Anna University. Accessed May 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/9847.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

S, Kanimozhiselvi C. “An investigation on automatic support thresholds for association rule mining.” 2013. Web. 20 May 2019.

Vancouver:

S KC. An investigation on automatic support thresholds for association rule mining. [Internet] [Thesis]. Anna University; 2013. [cited 2019 May 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/9847.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

S KC. An investigation on automatic support thresholds for association rule mining. [Thesis]. Anna University; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/9847

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


AUT University

4. Pisalpanus, Songwut. A landmark model for assigning item weight for pattern mining .

Degree: 2012, AUT University

 In weighted association rule mining, items are typically weighted based on background domain knowledge. However, it may not be feasible to gather domain information on… (more)

Subjects/Keywords: Weight estimation; Landmark weights; Association Rule Mining

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pisalpanus, S. (2012). A landmark model for assigning item weight for pattern mining . (Thesis). AUT University. Retrieved from http://hdl.handle.net/10292/4684

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pisalpanus, Songwut. “A landmark model for assigning item weight for pattern mining .” 2012. Thesis, AUT University. Accessed May 20, 2019. http://hdl.handle.net/10292/4684.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pisalpanus, Songwut. “A landmark model for assigning item weight for pattern mining .” 2012. Web. 20 May 2019.

Vancouver:

Pisalpanus S. A landmark model for assigning item weight for pattern mining . [Internet] [Thesis]. AUT University; 2012. [cited 2019 May 20]. Available from: http://hdl.handle.net/10292/4684.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pisalpanus S. A landmark model for assigning item weight for pattern mining . [Thesis]. AUT University; 2012. Available from: http://hdl.handle.net/10292/4684

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

5. Wang, Chun-chin. A Study of Multi-site On-shelf Data Mining.

Degree: Master, Computer Science and Engineering, 2013, NSYSU

 Temporal data mining techniques have been widely used to extract desirable time-related knowledge from existing databases. However, most of the existing studies only considered different… (more)

Subjects/Keywords: data mining; temporal association rule; association-rule mining; on-shelf time period; multi-site environment

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wang, C. (2013). A Study of Multi-site On-shelf Data Mining. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0713113-165134

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wang, Chun-chin. “A Study of Multi-site On-shelf Data Mining.” 2013. Thesis, NSYSU. Accessed May 20, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0713113-165134.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wang, Chun-chin. “A Study of Multi-site On-shelf Data Mining.” 2013. Web. 20 May 2019.

Vancouver:

Wang C. A Study of Multi-site On-shelf Data Mining. [Internet] [Thesis]. NSYSU; 2013. [cited 2019 May 20]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0713113-165134.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wang C. A Study of Multi-site On-shelf Data Mining. [Thesis]. NSYSU; 2013. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0713113-165134

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Queensland University of Technology

6. Wu, Jingtong. Interpretation of association rules with multi-tier granule mining.

Degree: 2014, Queensland University of Technology

 This study was a step forward to improve the performance for discovering useful knowledge – especially, association rules in this study – in databases. The… (more)

Subjects/Keywords: Data mining; Association rule mining; Granule mining; Decision rules; Rough sets

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wu, J. (2014). Interpretation of association rules with multi-tier granule mining. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/71455/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wu, Jingtong. “Interpretation of association rules with multi-tier granule mining.” 2014. Thesis, Queensland University of Technology. Accessed May 20, 2019. https://eprints.qut.edu.au/71455/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wu, Jingtong. “Interpretation of association rules with multi-tier granule mining.” 2014. Web. 20 May 2019.

Vancouver:

Wu J. Interpretation of association rules with multi-tier granule mining. [Internet] [Thesis]. Queensland University of Technology; 2014. [cited 2019 May 20]. Available from: https://eprints.qut.edu.au/71455/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wu J. Interpretation of association rules with multi-tier granule mining. [Thesis]. Queensland University of Technology; 2014. Available from: https://eprints.qut.edu.au/71455/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Durban University of Technology

7. Singh, Pariksha. Validating cohesion metrics by mining open source software data with association rules.

Degree: 2008, Durban University of Technology

Dissertation submitted for the fulfillment of the requirement for the degree of Masters in Information Technology, Department of Information Technology, Faculty of Accounting and Informatics,… (more)

Subjects/Keywords: Open source software; Data mining; Association rule mining; Software measurement

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Singh, P. (2008). Validating cohesion metrics by mining open source software data with association rules. (Thesis). Durban University of Technology. Retrieved from http://hdl.handle.net/10321/427

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Singh, Pariksha. “Validating cohesion metrics by mining open source software data with association rules.” 2008. Thesis, Durban University of Technology. Accessed May 20, 2019. http://hdl.handle.net/10321/427.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Singh, Pariksha. “Validating cohesion metrics by mining open source software data with association rules.” 2008. Web. 20 May 2019.

Vancouver:

Singh P. Validating cohesion metrics by mining open source software data with association rules. [Internet] [Thesis]. Durban University of Technology; 2008. [cited 2019 May 20]. Available from: http://hdl.handle.net/10321/427.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Singh P. Validating cohesion metrics by mining open source software data with association rules. [Thesis]. Durban University of Technology; 2008. Available from: http://hdl.handle.net/10321/427

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Delft University of Technology

8. Van der Valk, R.J.A. Why My Payment Got Rejected: A Method to Mine Payment Refusal Clues:.

Degree: 2015, Delft University of Technology

 A significant amount of payments fail for seemingly ‘mysterious’ reasons when refused by an issuer (i.e. cardholder’s bank). The technical and social complexities, such as… (more)

Subjects/Keywords: payments; data mining; association rule mining; moral hazard; principal-agent problem

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Van der Valk, R. J. A. (2015). Why My Payment Got Rejected: A Method to Mine Payment Refusal Clues:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9768c196-e490-4ad7-b9e1-0912c5ebf6a4

Chicago Manual of Style (16th Edition):

Van der Valk, R J A. “Why My Payment Got Rejected: A Method to Mine Payment Refusal Clues:.” 2015. Masters Thesis, Delft University of Technology. Accessed May 20, 2019. http://resolver.tudelft.nl/uuid:9768c196-e490-4ad7-b9e1-0912c5ebf6a4.

MLA Handbook (7th Edition):

Van der Valk, R J A. “Why My Payment Got Rejected: A Method to Mine Payment Refusal Clues:.” 2015. Web. 20 May 2019.

Vancouver:

Van der Valk RJA. Why My Payment Got Rejected: A Method to Mine Payment Refusal Clues:. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2019 May 20]. Available from: http://resolver.tudelft.nl/uuid:9768c196-e490-4ad7-b9e1-0912c5ebf6a4.

Council of Science Editors:

Van der Valk RJA. Why My Payment Got Rejected: A Method to Mine Payment Refusal Clues:. [Masters Thesis]. Delft University of Technology; 2015. Available from: http://resolver.tudelft.nl/uuid:9768c196-e490-4ad7-b9e1-0912c5ebf6a4


Iowa State University

9. Kim, Dongwook. Learning dispatching rules via an association rule mining approach.

Degree: 2015, Iowa State University

 This thesis proposes a new idea using association rule mining-based approach for discovering dispatching rules in production data. Decision trees have previously been used for… (more)

Subjects/Keywords: Industrial Engineering; Association rule mining; Data mining; Decision tree; Scheduling; Engineering

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APA (6th Edition):

Kim, D. (2015). Learning dispatching rules via an association rule mining approach. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/14383

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kim, Dongwook. “Learning dispatching rules via an association rule mining approach.” 2015. Thesis, Iowa State University. Accessed May 20, 2019. https://lib.dr.iastate.edu/etd/14383.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kim, Dongwook. “Learning dispatching rules via an association rule mining approach.” 2015. Web. 20 May 2019.

Vancouver:

Kim D. Learning dispatching rules via an association rule mining approach. [Internet] [Thesis]. Iowa State University; 2015. [cited 2019 May 20]. Available from: https://lib.dr.iastate.edu/etd/14383.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kim D. Learning dispatching rules via an association rule mining approach. [Thesis]. Iowa State University; 2015. Available from: https://lib.dr.iastate.edu/etd/14383

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

10. Ramachandran, Chandrasekar. A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets.

Degree: MS, 0112, 2010, University of Illinois – Urbana-Champaign

 In this work, we describe a comprehensive framework for knowledge discovery from medical records called SDM-Miner. The records are created before, during and after pancreatic… (more)

Subjects/Keywords: islet cell transplants; medical data mining; dimensionality reduction; association rule mining

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ramachandran, C. (2010). A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/14710

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ramachandran, Chandrasekar. “A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets.” 2010. Thesis, University of Illinois – Urbana-Champaign. Accessed May 20, 2019. http://hdl.handle.net/2142/14710.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ramachandran, Chandrasekar. “A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets.” 2010. Web. 20 May 2019.

Vancouver:

Ramachandran C. A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2010. [cited 2019 May 20]. Available from: http://hdl.handle.net/2142/14710.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ramachandran C. A Framework for Knowledge Discovery from Sparse, High-Dimensional Medical Datasets. [Thesis]. University of Illinois – Urbana-Champaign; 2010. Available from: http://hdl.handle.net/2142/14710

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

11. Wu, Pei-Shan. Temporal Data Mining with a Hierarchy of Time Granules.

Degree: Master, Computer Science and Engineering, 2012, NSYSU

 Data mining techniques have been widely applied to extract desirable knowledge from existing databases for specific purposes. In real-world applications, a database usually involves the… (more)

Subjects/Keywords: a hierarchy of time granules; item lifespan; temporal association rules; association-rule mining; Data mining

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wu, P. (2012). Temporal Data Mining with a Hierarchy of Time Granules. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0828112-142127

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wu, Pei-Shan. “Temporal Data Mining with a Hierarchy of Time Granules.” 2012. Thesis, NSYSU. Accessed May 20, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0828112-142127.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wu, Pei-Shan. “Temporal Data Mining with a Hierarchy of Time Granules.” 2012. Web. 20 May 2019.

Vancouver:

Wu P. Temporal Data Mining with a Hierarchy of Time Granules. [Internet] [Thesis]. NSYSU; 2012. [cited 2019 May 20]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0828112-142127.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wu P. Temporal Data Mining with a Hierarchy of Time Granules. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0828112-142127

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Queensland University of Technology

12. Yang, Wanzhong. Granule-based knowledge representation for intra and inter transaction association mining.

Degree: 2009, Queensland University of Technology

 Abstract With the phenomenal growth of electronic data and information, there are many demands for the development of efficient and effective systems (tools) to perform… (more)

Subjects/Keywords: knowledge discovery; knowledge representation; intratransaction association rule; intertransaction association rule; granule mining; multi-tier; association mapping

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yang, W. (2009). Granule-based knowledge representation for intra and inter transaction association mining. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/30398/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Yang, Wanzhong. “Granule-based knowledge representation for intra and inter transaction association mining.” 2009. Thesis, Queensland University of Technology. Accessed May 20, 2019. https://eprints.qut.edu.au/30398/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Yang, Wanzhong. “Granule-based knowledge representation for intra and inter transaction association mining.” 2009. Web. 20 May 2019.

Vancouver:

Yang W. Granule-based knowledge representation for intra and inter transaction association mining. [Internet] [Thesis]. Queensland University of Technology; 2009. [cited 2019 May 20]. Available from: https://eprints.qut.edu.au/30398/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yang W. Granule-based knowledge representation for intra and inter transaction association mining. [Thesis]. Queensland University of Technology; 2009. Available from: https://eprints.qut.edu.au/30398/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

13. Sengupta, Dipankar. Translational and High End Computing of Clinical Data in India;.

Degree: 2014, Jaypee University of Information Technology, Solan

Healthcare sector is generating large amount of data pertaining to diagnosis, disease identification and treatment of an individual. Mining knowledge and providing scientific decision-making for… (more)

Subjects/Keywords: Apriori Algorithm; Association Rule Mining; Beck Depression Inventory (BDI); Clinical Informatics

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APA (6th Edition):

Sengupta, D. (2014). Translational and High End Computing of Clinical Data in India;. (Thesis). Jaypee University of Information Technology, Solan. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/18011

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sengupta, Dipankar. “Translational and High End Computing of Clinical Data in India;.” 2014. Thesis, Jaypee University of Information Technology, Solan. Accessed May 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/18011.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sengupta, Dipankar. “Translational and High End Computing of Clinical Data in India;.” 2014. Web. 20 May 2019.

Vancouver:

Sengupta D. Translational and High End Computing of Clinical Data in India;. [Internet] [Thesis]. Jaypee University of Information Technology, Solan; 2014. [cited 2019 May 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/18011.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sengupta D. Translational and High End Computing of Clinical Data in India;. [Thesis]. Jaypee University of Information Technology, Solan; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/18011

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Anna University

14. Umarani V. On Developing Effectual Algorithms For Association Rule Discovery In Transaction Databases;.

Degree: Computer Science, 2013, Anna University

Association rule mining is the most important and well investigated data newlinemining technique used by an organizations decision makers to improve the newlineoverall profit It… (more)

Subjects/Keywords: Algorithms; Association Rule; data mining; scalability; Transaction Databases

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APA (6th Edition):

V, U. (2013). On Developing Effectual Algorithms For Association Rule Discovery In Transaction Databases;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/24357

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

V, Umarani. “On Developing Effectual Algorithms For Association Rule Discovery In Transaction Databases;.” 2013. Thesis, Anna University. Accessed May 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/24357.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

V, Umarani. “On Developing Effectual Algorithms For Association Rule Discovery In Transaction Databases;.” 2013. Web. 20 May 2019.

Vancouver:

V U. On Developing Effectual Algorithms For Association Rule Discovery In Transaction Databases;. [Internet] [Thesis]. Anna University; 2013. [cited 2019 May 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/24357.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

V U. On Developing Effectual Algorithms For Association Rule Discovery In Transaction Databases;. [Thesis]. Anna University; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/24357

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Addis Ababa University

15. Helen, Tefera Kidane. APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA .

Degree: 2012, Addis Ababa University

 Knowledge and understanding of a problem is always the first step in identifying effective solutions. Child labor is both a sign and cause of poverty… (more)

Subjects/Keywords: Data mining; apriori algorithm; association rule; knowledge discovery

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Helen, T. K. (2012). APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA . (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/dspace/handle/123456789/2811

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Helen, Tefera Kidane. “APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA .” 2012. Thesis, Addis Ababa University. Accessed May 20, 2019. http://etd.aau.edu.et/dspace/handle/123456789/2811.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Helen, Tefera Kidane. “APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA .” 2012. Web. 20 May 2019.

Vancouver:

Helen TK. APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA . [Internet] [Thesis]. Addis Ababa University; 2012. [cited 2019 May 20]. Available from: http://etd.aau.edu.et/dspace/handle/123456789/2811.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Helen TK. APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA . [Thesis]. Addis Ababa University; 2012. Available from: http://etd.aau.edu.et/dspace/handle/123456789/2811

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Addis Ababa University

16. Tefera, Helen. APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA .

Degree: 2008, Addis Ababa University

 Knowledge and understanding of a problem is always the first step in identifying effective solutions. Child labor is both a sign and cause of poverty… (more)

Subjects/Keywords: Data mining; knowledge discovery; association rule; apriori algorithm

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tefera, H. (2008). APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA . (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/dspace/handle/123456789/2819

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tefera, Helen. “APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA .” 2008. Thesis, Addis Ababa University. Accessed May 20, 2019. http://etd.aau.edu.et/dspace/handle/123456789/2819.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tefera, Helen. “APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA .” 2008. Web. 20 May 2019.

Vancouver:

Tefera H. APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA . [Internet] [Thesis]. Addis Ababa University; 2008. [cited 2019 May 20]. Available from: http://etd.aau.edu.et/dspace/handle/123456789/2819.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tefera H. APPLICATION OF DATA MINING TECHNOLOGY TO IDENTIFY SIGNIFICANT PATTERNS IN CENSUS OR SURVEY DATA: THE CASE OF 2001 CHILD LABOR SURVEY IN ETHIOPIA . [Thesis]. Addis Ababa University; 2008. Available from: http://etd.aau.edu.et/dspace/handle/123456789/2819

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Nairobi

17. Ronoh, Laban K. Use of GIS and association rule mining in guiding strategic business expansion planning:case study Chase Bank (K) Ltd .

Degree: 2009, University of Nairobi

 In recent years, optimal site selection has become one of the main concerns for managers of business enterprises. In addition, various kinds of spatial and… (more)

Subjects/Keywords: Geographic Information Systems,; Data Mining,; Trade Area,; Spatial Association Rule; Efficiency.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ronoh, L. K. (2009). Use of GIS and association rule mining in guiding strategic business expansion planning:case study Chase Bank (K) Ltd . (Thesis). University of Nairobi. Retrieved from http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14934

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ronoh, Laban K. “Use of GIS and association rule mining in guiding strategic business expansion planning:case study Chase Bank (K) Ltd .” 2009. Thesis, University of Nairobi. Accessed May 20, 2019. http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14934.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ronoh, Laban K. “Use of GIS and association rule mining in guiding strategic business expansion planning:case study Chase Bank (K) Ltd .” 2009. Web. 20 May 2019.

Vancouver:

Ronoh LK. Use of GIS and association rule mining in guiding strategic business expansion planning:case study Chase Bank (K) Ltd . [Internet] [Thesis]. University of Nairobi; 2009. [cited 2019 May 20]. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14934.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ronoh LK. Use of GIS and association rule mining in guiding strategic business expansion planning:case study Chase Bank (K) Ltd . [Thesis]. University of Nairobi; 2009. Available from: http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14934

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


De Montfort University

18. Abdelhamid, Neda. Deriving classifiers with single and multi-label rules using new Associative Classification methods.

Degree: PhD, 2013, De Montfort University

 Associative Classification (AC) in data mining is a rule based approach that uses association rule techniques to construct accurate classification systems (classifiers). The majority of… (more)

Subjects/Keywords: 600; Class association rule; Classification; data mining; Phishing detection; Pattern recognition

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Abdelhamid, N. (2013). Deriving classifiers with single and multi-label rules using new Associative Classification methods. (Doctoral Dissertation). De Montfort University. Retrieved from http://hdl.handle.net/2086/10120

Chicago Manual of Style (16th Edition):

Abdelhamid, Neda. “Deriving classifiers with single and multi-label rules using new Associative Classification methods.” 2013. Doctoral Dissertation, De Montfort University. Accessed May 20, 2019. http://hdl.handle.net/2086/10120.

MLA Handbook (7th Edition):

Abdelhamid, Neda. “Deriving classifiers with single and multi-label rules using new Associative Classification methods.” 2013. Web. 20 May 2019.

Vancouver:

Abdelhamid N. Deriving classifiers with single and multi-label rules using new Associative Classification methods. [Internet] [Doctoral dissertation]. De Montfort University; 2013. [cited 2019 May 20]. Available from: http://hdl.handle.net/2086/10120.

Council of Science Editors:

Abdelhamid N. Deriving classifiers with single and multi-label rules using new Associative Classification methods. [Doctoral Dissertation]. De Montfort University; 2013. Available from: http://hdl.handle.net/2086/10120

19. Richardson, Jeff Cillian, 1987-. Applying Association Rules to Optimize Enterprise Software Development.

Degree: Department of Mathematical Sciences, 2014, Central Connecticut State University

Background: For most software companies, development consumes a substantial portion of their resources. As the volume of products offered increases, costs rise dramatically. For large… (more)

Subjects/Keywords: Association rule mining.

rule generation, CARMA – Continuous Association Rule Mining Algorithm. The authors focused… …counting, Continuous Association Rule Mining Algorithm (CARMA) introduces several… …standard for many problems of this nature. Association rule models are able to, and even excel at… …Overview of Related Research Mining Association rules between sets of items in large databases… …iteration of the association rule generation algorithm. The method involved an exhaustive search… 

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APA (6th Edition):

Richardson, Jeff Cillian, 1. (2014). Applying Association Rules to Optimize Enterprise Software Development. (Thesis). Central Connecticut State University. Retrieved from http://content.library.ccsu.edu/u?/ccsutheses,2032

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Richardson, Jeff Cillian, 1987-. “Applying Association Rules to Optimize Enterprise Software Development.” 2014. Thesis, Central Connecticut State University. Accessed May 20, 2019. http://content.library.ccsu.edu/u?/ccsutheses,2032.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Richardson, Jeff Cillian, 1987-. “Applying Association Rules to Optimize Enterprise Software Development.” 2014. Web. 20 May 2019.

Vancouver:

Richardson, Jeff Cillian 1. Applying Association Rules to Optimize Enterprise Software Development. [Internet] [Thesis]. Central Connecticut State University; 2014. [cited 2019 May 20]. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2032.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Richardson, Jeff Cillian 1. Applying Association Rules to Optimize Enterprise Software Development. [Thesis]. Central Connecticut State University; 2014. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2032

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Kansas State University

20. Aljandal, Waleed A. Itemset size-sensitive interestingness measures for association rule mining and link prediction.

Degree: PhD, Department of Computing and Information Sciences, 2009, Kansas State University

Association rule learning is a data mining technique that can capture relationships between pairs of entities in different domains. The goal of this research is… (more)

Subjects/Keywords: Data Mining; Association Rule; Interestingness Measures; Link Prediction; Computer Science (0984)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Aljandal, W. A. (2009). Itemset size-sensitive interestingness measures for association rule mining and link prediction. (Doctoral Dissertation). Kansas State University. Retrieved from http://hdl.handle.net/2097/1245

Chicago Manual of Style (16th Edition):

Aljandal, Waleed A. “Itemset size-sensitive interestingness measures for association rule mining and link prediction.” 2009. Doctoral Dissertation, Kansas State University. Accessed May 20, 2019. http://hdl.handle.net/2097/1245.

MLA Handbook (7th Edition):

Aljandal, Waleed A. “Itemset size-sensitive interestingness measures for association rule mining and link prediction.” 2009. Web. 20 May 2019.

Vancouver:

Aljandal WA. Itemset size-sensitive interestingness measures for association rule mining and link prediction. [Internet] [Doctoral dissertation]. Kansas State University; 2009. [cited 2019 May 20]. Available from: http://hdl.handle.net/2097/1245.

Council of Science Editors:

Aljandal WA. Itemset size-sensitive interestingness measures for association rule mining and link prediction. [Doctoral Dissertation]. Kansas State University; 2009. Available from: http://hdl.handle.net/2097/1245


University of Miami

21. Sooriyaarachchi Wickramaratna, Kasun Jayamal. DS-ARM: An Association Rule Based Predictor that Can Learn from Imperfect Data.

Degree: PhD, Electrical and Computer Engineering (Engineering), 2010, University of Miami

 Over the past decades, many industries have heavily spent on computerizing their work environments with the intention to simplify and expedite access to information and… (more)

Subjects/Keywords: Data Imperfections; DS-theory; Dempster Shafer Evidence Theory; Association Rule Mining

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APA (6th Edition):

Sooriyaarachchi Wickramaratna, K. J. (2010). DS-ARM: An Association Rule Based Predictor that Can Learn from Imperfect Data. (Doctoral Dissertation). University of Miami. Retrieved from https://scholarlyrepository.miami.edu/oa_dissertations/159

Chicago Manual of Style (16th Edition):

Sooriyaarachchi Wickramaratna, Kasun Jayamal. “DS-ARM: An Association Rule Based Predictor that Can Learn from Imperfect Data.” 2010. Doctoral Dissertation, University of Miami. Accessed May 20, 2019. https://scholarlyrepository.miami.edu/oa_dissertations/159.

MLA Handbook (7th Edition):

Sooriyaarachchi Wickramaratna, Kasun Jayamal. “DS-ARM: An Association Rule Based Predictor that Can Learn from Imperfect Data.” 2010. Web. 20 May 2019.

Vancouver:

Sooriyaarachchi Wickramaratna KJ. DS-ARM: An Association Rule Based Predictor that Can Learn from Imperfect Data. [Internet] [Doctoral dissertation]. University of Miami; 2010. [cited 2019 May 20]. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/159.

Council of Science Editors:

Sooriyaarachchi Wickramaratna KJ. DS-ARM: An Association Rule Based Predictor that Can Learn from Imperfect Data. [Doctoral Dissertation]. University of Miami; 2010. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/159


North Carolina State University

22. Kim, Jihye. Mining of cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing.

Degree: PhD, Bioinformatics, 2009, North Carolina State University

 Alternative splicing (AS) is an important post-transcriptional mechanism that increases protein diversity and may affect mRNA stability and translaftion efficiency. Despite its importance, our knowledge… (more)

Subjects/Keywords: alternative splicing; cis-regulatory motifs; association rule mining

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APA (6th Edition):

Kim, J. (2009). Mining of cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/3709

Chicago Manual of Style (16th Edition):

Kim, Jihye. “Mining of cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing.” 2009. Doctoral Dissertation, North Carolina State University. Accessed May 20, 2019. http://www.lib.ncsu.edu/resolver/1840.16/3709.

MLA Handbook (7th Edition):

Kim, Jihye. “Mining of cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing.” 2009. Web. 20 May 2019.

Vancouver:

Kim J. Mining of cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 May 20]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/3709.

Council of Science Editors:

Kim J. Mining of cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/3709


Louisiana State University

23. Donepudi, Harisha. Detection of Interesting Traffic Accident Patterns by Association Rule Mining.

Degree: MSCS, Computer Sciences, 2013, Louisiana State University

 In recent years, the accident rate related to traffic is high. Analyzing the crash data and extracting useful information from it can help in taking… (more)

Subjects/Keywords: frequent item sets; mostly associated patterns; interesting patterns; association rules; association rule mining

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APA (6th Edition):

Donepudi, H. (2013). Detection of Interesting Traffic Accident Patterns by Association Rule Mining. (Masters Thesis). Louisiana State University. Retrieved from etd-07012013-160705 ; https://digitalcommons.lsu.edu/gradschool_theses/2585

Chicago Manual of Style (16th Edition):

Donepudi, Harisha. “Detection of Interesting Traffic Accident Patterns by Association Rule Mining.” 2013. Masters Thesis, Louisiana State University. Accessed May 20, 2019. etd-07012013-160705 ; https://digitalcommons.lsu.edu/gradschool_theses/2585.

MLA Handbook (7th Edition):

Donepudi, Harisha. “Detection of Interesting Traffic Accident Patterns by Association Rule Mining.” 2013. Web. 20 May 2019.

Vancouver:

Donepudi H. Detection of Interesting Traffic Accident Patterns by Association Rule Mining. [Internet] [Masters thesis]. Louisiana State University; 2013. [cited 2019 May 20]. Available from: etd-07012013-160705 ; https://digitalcommons.lsu.edu/gradschool_theses/2585.

Council of Science Editors:

Donepudi H. Detection of Interesting Traffic Accident Patterns by Association Rule Mining. [Masters Thesis]. Louisiana State University; 2013. Available from: etd-07012013-160705 ; https://digitalcommons.lsu.edu/gradschool_theses/2585


University of Victoria

24. Pinheiro, Fabiola M. R. Applying the Apriori and FP-Growth Association Algorithms to Liver Cancer Data.

Degree: School of Health Information Science, 2013, University of Victoria

 Cancer is the leading cause of deaths globally. Although liver cancer ranks only fourth in incidence worldwide among all types of cancer, its survivability rate… (more)

Subjects/Keywords: liver; cancer; association analysis; association rule; apriori; fp-growth; data mining; British Columbia; Yukon

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APA (6th Edition):

Pinheiro, F. M. R. (2013). Applying the Apriori and FP-Growth Association Algorithms to Liver Cancer Data. (Masters Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/4846

Chicago Manual of Style (16th Edition):

Pinheiro, Fabiola M R. “Applying the Apriori and FP-Growth Association Algorithms to Liver Cancer Data.” 2013. Masters Thesis, University of Victoria. Accessed May 20, 2019. http://hdl.handle.net/1828/4846.

MLA Handbook (7th Edition):

Pinheiro, Fabiola M R. “Applying the Apriori and FP-Growth Association Algorithms to Liver Cancer Data.” 2013. Web. 20 May 2019.

Vancouver:

Pinheiro FMR. Applying the Apriori and FP-Growth Association Algorithms to Liver Cancer Data. [Internet] [Masters thesis]. University of Victoria; 2013. [cited 2019 May 20]. Available from: http://hdl.handle.net/1828/4846.

Council of Science Editors:

Pinheiro FMR. Applying the Apriori and FP-Growth Association Algorithms to Liver Cancer Data. [Masters Thesis]. University of Victoria; 2013. Available from: http://hdl.handle.net/1828/4846


KTH

25. Thun, Julia. Automating debugging through data mining.

Degree: Computer and Electronic Engineering, 2017, KTH

Contemporary technological systems generate massive quantities of log messages. These messages can be stored, searched and visualized efficiently using log management and analysis tools.… (more)

Subjects/Keywords: Association rule mining; Machine learning; Classification algorithms; Supervised learning; Text mining; Log management and analysis tools; Association rule mining; Maskininlärning; Classification algorithms; Supervised learning; Text mining; Logghanteringsverktyg; Software Engineering; Programvaruteknik

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APA (6th Edition):

Thun, J. (2017). Automating debugging through data mining. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-203244

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Thun, Julia. “Automating debugging through data mining.” 2017. Thesis, KTH. Accessed May 20, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-203244.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Thun, Julia. “Automating debugging through data mining.” 2017. Web. 20 May 2019.

Vancouver:

Thun J. Automating debugging through data mining. [Internet] [Thesis]. KTH; 2017. [cited 2019 May 20]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-203244.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Thun J. Automating debugging through data mining. [Thesis]. KTH; 2017. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-203244

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Mississippi State University

26. Saha, Surya. PROXIMITY BASED ASSOCIATION RULES FOR SPATIAL DATA MINING IN GENOMES.

Degree: PhD, Computer Science and Engineering, 2009, Mississippi State University

 Our knowledge discovery algorithm employs a combination of association rule mining and graph mining to identify frequent spatial proximity relationships in genomic data where the… (more)

Subjects/Keywords: association rule mining; spatial rules; repeat; defragmentation; graph mining; association rule mining; spatial rules; repeat; defragmentation; graph mining; novel repeat regions; DNA

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Saha, S. (2009). PROXIMITY BASED ASSOCIATION RULES FOR SPATIAL DATA MINING IN GENOMES. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-07012009-104850/ ;

Chicago Manual of Style (16th Edition):

Saha, Surya. “PROXIMITY BASED ASSOCIATION RULES FOR SPATIAL DATA MINING IN GENOMES.” 2009. Doctoral Dissertation, Mississippi State University. Accessed May 20, 2019. http://sun.library.msstate.edu/ETD-db/theses/available/etd-07012009-104850/ ;.

MLA Handbook (7th Edition):

Saha, Surya. “PROXIMITY BASED ASSOCIATION RULES FOR SPATIAL DATA MINING IN GENOMES.” 2009. Web. 20 May 2019.

Vancouver:

Saha S. PROXIMITY BASED ASSOCIATION RULES FOR SPATIAL DATA MINING IN GENOMES. [Internet] [Doctoral dissertation]. Mississippi State University; 2009. [cited 2019 May 20]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-07012009-104850/ ;.

Council of Science Editors:

Saha S. PROXIMITY BASED ASSOCIATION RULES FOR SPATIAL DATA MINING IN GENOMES. [Doctoral Dissertation]. Mississippi State University; 2009. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-07012009-104850/ ;


Anna University

27. Nandagopal, S. Adept strategy for mining of association rules from inter transactional domains; -.

Degree: Information and Communication Engineering, 2014, Anna University

The world revolves around the information stored by various users in different environments Data can be of different forms such as informative sequence notification of… (more)

Subjects/Keywords: Categorized and Bounded Inter- Transaction; Crumb Based Association Rule Mining; Information and communication engineering; Inter-transaction Association Rule; Modified Apriori Algorithm

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APA (6th Edition):

Nandagopal, S. (2014). Adept strategy for mining of association rules from inter transactional domains; -. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/23889

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Nandagopal, S. “Adept strategy for mining of association rules from inter transactional domains; -.” 2014. Thesis, Anna University. Accessed May 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/23889.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Nandagopal, S. “Adept strategy for mining of association rules from inter transactional domains; -.” 2014. Web. 20 May 2019.

Vancouver:

Nandagopal S. Adept strategy for mining of association rules from inter transactional domains; -. [Internet] [Thesis]. Anna University; 2014. [cited 2019 May 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/23889.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nandagopal S. Adept strategy for mining of association rules from inter transactional domains; -. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/23889

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

28. Li, Yu. Genetic-Fuzzy Mining with Type-2 Membership Functions.

Degree: Master, Computer Science and Engineering, 2015, NSYSU

Association rule mining is commonly utilized to extract useful information from given data. Since items are usually with quantities in real-world transaction databases, the fuzzy… (more)

Subjects/Keywords: genetic-fuzzy mining; association rule; data mining; type-2 fuzzy set; membership function

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Li, Y. (2015). Genetic-Fuzzy Mining with Type-2 Membership Functions. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0705115-170321

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Li, Yu. “Genetic-Fuzzy Mining with Type-2 Membership Functions.” 2015. Thesis, NSYSU. Accessed May 20, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0705115-170321.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Li, Yu. “Genetic-Fuzzy Mining with Type-2 Membership Functions.” 2015. Web. 20 May 2019.

Vancouver:

Li Y. Genetic-Fuzzy Mining with Type-2 Membership Functions. [Internet] [Thesis]. NSYSU; 2015. [cited 2019 May 20]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0705115-170321.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li Y. Genetic-Fuzzy Mining with Type-2 Membership Functions. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0705115-170321

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

29. Lee, Ko-han. A context-aware system to predict user's intention on smartphone based on ECA Model.

Degree: Master, Information Management, 2012, NSYSU

 With the development of artificial intelligence , the application of recommender systems has been extended to fields such as e-commerce shopping cart analysis or video… (more)

Subjects/Keywords: Fuzzy Clustering; Context-aware; Recommender systems; User behavior analysis; Data Mining; Association rule mining

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lee, K. (2012). A context-aware system to predict user's intention on smartphone based on ECA Model. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821112-143035

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lee, Ko-han. “A context-aware system to predict user's intention on smartphone based on ECA Model.” 2012. Thesis, NSYSU. Accessed May 20, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821112-143035.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lee, Ko-han. “A context-aware system to predict user's intention on smartphone based on ECA Model.” 2012. Web. 20 May 2019.

Vancouver:

Lee K. A context-aware system to predict user's intention on smartphone based on ECA Model. [Internet] [Thesis]. NSYSU; 2012. [cited 2019 May 20]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821112-143035.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lee K. A context-aware system to predict user's intention on smartphone based on ECA Model. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0821112-143035

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


NSYSU

30. Lin, Shih-Bin. A Study on Fuzzy Temporal Data Mining.

Degree: Master, Computer Science and Engineering, 2011, NSYSU

 Data mining is an important process of extracting desirable knowledge from existing databases for specific purposes. Nearly all transactions in real-world databases involve items bought,… (more)

Subjects/Keywords: fuzzy data mining; Fuzzy set; data mining; fuzzy temporal association rule; item lifespan

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lin, S. (2011). A Study on Fuzzy Temporal Data Mining. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-214151

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lin, Shih-Bin. “A Study on Fuzzy Temporal Data Mining.” 2011. Thesis, NSYSU. Accessed May 20, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-214151.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lin, Shih-Bin. “A Study on Fuzzy Temporal Data Mining.” 2011. Web. 20 May 2019.

Vancouver:

Lin S. A Study on Fuzzy Temporal Data Mining. [Internet] [Thesis]. NSYSU; 2011. [cited 2019 May 20]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-214151.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lin S. A Study on Fuzzy Temporal Data Mining. [Thesis]. NSYSU; 2011. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906111-214151

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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