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You searched for subject:(Data mining ). Showing records 1 – 30 of 3330 total matches.

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University of Hong Kong

1. Xu, Yong. Top-k SAS : on reliable retrieval of top-k tags.

Degree: M. Phil., 2017, University of Hong Kong

above method is quite challenging. To address this problem, we propose a learning-based method which applies machine learning models to estimate whether the k most… (more)

Subjects/Keywords: Data mining

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APA (6th Edition):

Xu, Y. (2017). Top-k SAS : on reliable retrieval of top-k tags. (Masters Thesis). University of Hong Kong. Retrieved from http://hdl.handle.net/10722/244320

Chicago Manual of Style (16th Edition):

Xu, Yong. “Top-k SAS : on reliable retrieval of top-k tags.” 2017. Masters Thesis, University of Hong Kong. Accessed June 17, 2019. http://hdl.handle.net/10722/244320.

MLA Handbook (7th Edition):

Xu, Yong. “Top-k SAS : on reliable retrieval of top-k tags.” 2017. Web. 17 Jun 2019.

Vancouver:

Xu Y. Top-k SAS : on reliable retrieval of top-k tags. [Internet] [Masters thesis]. University of Hong Kong; 2017. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/10722/244320.

Council of Science Editors:

Xu Y. Top-k SAS : on reliable retrieval of top-k tags. [Masters Thesis]. University of Hong Kong; 2017. Available from: http://hdl.handle.net/10722/244320


University of Hong Kong

2. Wan, Chang. Mining multi-faceted data.

Degree: M. Phil., 2013, University of Hong Kong

Multi-faceted data contains different types of objects and relationships between them. With rapid growth of web-based services, multi-faceted data are increasing (e.g. Flickr, Yago, IMDB),… (more)

Subjects/Keywords: Data mining

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APA (6th Edition):

Wan, C. (2013). Mining multi-faceted data. (Masters Thesis). University of Hong Kong. Retrieved from Wan, C. [萬暢]. (2013). Mining multi-faceted data. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5194751 ; http://dx.doi.org/10.5353/th_b5194751 ; http://hdl.handle.net/10722/197527

Chicago Manual of Style (16th Edition):

Wan, Chang. “Mining multi-faceted data.” 2013. Masters Thesis, University of Hong Kong. Accessed June 17, 2019. Wan, C. [萬暢]. (2013). Mining multi-faceted data. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5194751 ; http://dx.doi.org/10.5353/th_b5194751 ; http://hdl.handle.net/10722/197527.

MLA Handbook (7th Edition):

Wan, Chang. “Mining multi-faceted data.” 2013. Web. 17 Jun 2019.

Vancouver:

Wan C. Mining multi-faceted data. [Internet] [Masters thesis]. University of Hong Kong; 2013. [cited 2019 Jun 17]. Available from: Wan, C. [萬暢]. (2013). Mining multi-faceted data. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5194751 ; http://dx.doi.org/10.5353/th_b5194751 ; http://hdl.handle.net/10722/197527.

Council of Science Editors:

Wan C. Mining multi-faceted data. [Masters Thesis]. University of Hong Kong; 2013. Available from: Wan, C. [萬暢]. (2013). Mining multi-faceted data. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5194751 ; http://dx.doi.org/10.5353/th_b5194751 ; http://hdl.handle.net/10722/197527


Central Connecticut State University

3. Adu-Poku, Sampson, 1961-. Comparing classification algorithms in data mining.

Degree: Department of Mathematical Sciences, 2012, Central Connecticut State University

 In this thesis, support vector machines, neural networks, logistic regression, naïve Bayes, classification and regression trees, the C5.0 algorithms, QUEST, CHAID and discriminant analysis have… (more)

Subjects/Keywords: Data mining

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APA (6th Edition):

Adu-Poku, Sampson, 1. (2012). Comparing classification algorithms in data mining. (Thesis). Central Connecticut State University. Retrieved from http://content.library.ccsu.edu/u?/ccsutheses,1768

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):

Adu-Poku, Sampson, 1961-. “Comparing classification algorithms in data mining.” 2012. Thesis, Central Connecticut State University. Accessed June 17, 2019. http://content.library.ccsu.edu/u?/ccsutheses,1768.

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

MLA Handbook (7th Edition):

Adu-Poku, Sampson, 1961-. “Comparing classification algorithms in data mining.” 2012. Web. 17 Jun 2019.

Vancouver:

Adu-Poku, Sampson 1. Comparing classification algorithms in data mining. [Internet] [Thesis]. Central Connecticut State University; 2012. [cited 2019 Jun 17]. Available from: http://content.library.ccsu.edu/u?/ccsutheses,1768.

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

Council of Science Editors:

Adu-Poku, Sampson 1. Comparing classification algorithms in data mining. [Thesis]. Central Connecticut State University; 2012. Available from: http://content.library.ccsu.edu/u?/ccsutheses,1768

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


Central Connecticut State University

4. Reybod, Ramin, 1962-. Applying Data Mining on relational data and networks analysis with emphasis on Link Prediction.

Degree: Department of Computer Science, 2018, Central Connecticut State University

The "contact" patterns of individuals in a hospital ward, can give us useful information to explain certain dynamics and processes such as spread of infectious… (more)

Subjects/Keywords: Data mining.

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APA (6th Edition):

Reybod, Ramin, 1. (2018). Applying Data Mining on relational data and networks analysis with emphasis on Link Prediction. (Thesis). Central Connecticut State University. Retrieved from http://content.library.ccsu.edu/u?/ccsutheses,2710

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):

Reybod, Ramin, 1962-. “Applying Data Mining on relational data and networks analysis with emphasis on Link Prediction.” 2018. Thesis, Central Connecticut State University. Accessed June 17, 2019. http://content.library.ccsu.edu/u?/ccsutheses,2710.

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

MLA Handbook (7th Edition):

Reybod, Ramin, 1962-. “Applying Data Mining on relational data and networks analysis with emphasis on Link Prediction.” 2018. Web. 17 Jun 2019.

Vancouver:

Reybod, Ramin 1. Applying Data Mining on relational data and networks analysis with emphasis on Link Prediction. [Internet] [Thesis]. Central Connecticut State University; 2018. [cited 2019 Jun 17]. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2710.

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

Council of Science Editors:

Reybod, Ramin 1. Applying Data Mining on relational data and networks analysis with emphasis on Link Prediction. [Thesis]. Central Connecticut State University; 2018. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2710

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


University of Manitoba

5. Yu, Jialiang. Fast and scalable MapReduce-based vertical mining.

Degree: Computer Science, 2018, University of Manitoba

Mining uncertain data is challenging because uncertainty is usually represented as real numbers which are in infinite (cf. representing infinite occurrence counts when mining precise… (more)

Subjects/Keywords: data mining

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APA (6th Edition):

Yu, J. (2018). Fast and scalable MapReduce-based vertical mining. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/33337

Chicago Manual of Style (16th Edition):

Yu, Jialiang. “Fast and scalable MapReduce-based vertical mining.” 2018. Masters Thesis, University of Manitoba. Accessed June 17, 2019. http://hdl.handle.net/1993/33337.

MLA Handbook (7th Edition):

Yu, Jialiang. “Fast and scalable MapReduce-based vertical mining.” 2018. Web. 17 Jun 2019.

Vancouver:

Yu J. Fast and scalable MapReduce-based vertical mining. [Internet] [Masters thesis]. University of Manitoba; 2018. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/1993/33337.

Council of Science Editors:

Yu J. Fast and scalable MapReduce-based vertical mining. [Masters Thesis]. University of Manitoba; 2018. Available from: http://hdl.handle.net/1993/33337


Queens University

6. Lamb, Carolyn. Detecting Deception in Interrogation Settings .

Degree: Computing, 2012, Queens University

 Bag-of-words deception detection systems outperform humans, but are still not always accurate enough to be useful. In interrogation settings, present models do not take into… (more)

Subjects/Keywords: Data Mining; Deception; Text Mining

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APA (6th Edition):

Lamb, C. (2012). Detecting Deception in Interrogation Settings . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/7695

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):

Lamb, Carolyn. “Detecting Deception in Interrogation Settings .” 2012. Thesis, Queens University. Accessed June 17, 2019. http://hdl.handle.net/1974/7695.

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

MLA Handbook (7th Edition):

Lamb, Carolyn. “Detecting Deception in Interrogation Settings .” 2012. Web. 17 Jun 2019.

Vancouver:

Lamb C. Detecting Deception in Interrogation Settings . [Internet] [Thesis]. Queens University; 2012. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/1974/7695.

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

Council of Science Editors:

Lamb C. Detecting Deception in Interrogation Settings . [Thesis]. Queens University; 2012. Available from: http://hdl.handle.net/1974/7695

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


Cornell University

7. Haque, Asif-ul. Information And Social System Interaction .

Degree: 2011, Cornell University

 Ever increasing participation has made the interaction between information and social systems not only interesting to observe but essential to quantify and analyze. This dissertation… (more)

Subjects/Keywords: data mining; networks; text mining

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APA (6th Edition):

Haque, A. (2011). Information And Social System Interaction . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/30752

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):

Haque, Asif-ul. “Information And Social System Interaction .” 2011. Thesis, Cornell University. Accessed June 17, 2019. http://hdl.handle.net/1813/30752.

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

MLA Handbook (7th Edition):

Haque, Asif-ul. “Information And Social System Interaction .” 2011. Web. 17 Jun 2019.

Vancouver:

Haque A. Information And Social System Interaction . [Internet] [Thesis]. Cornell University; 2011. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/1813/30752.

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

Council of Science Editors:

Haque A. Information And Social System Interaction . [Thesis]. Cornell University; 2011. Available from: http://hdl.handle.net/1813/30752

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


AUT University

8. Gottgtroy, Paulo. An ontology driven knowledge discovery framework for Dynamic Domains: methodology, tools and a Biomedical case .

Degree: 2011, AUT University

 The explosive growth in the volume of data and the growing number of disparate data sources is bringing enormous opportunities and challenges to many research… (more)

Subjects/Keywords: Data mining; Ontology

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APA (6th Edition):

Gottgtroy, P. (2011). An ontology driven knowledge discovery framework for Dynamic Domains: methodology, tools and a Biomedical case . (Thesis). AUT University. Retrieved from http://hdl.handle.net/10292/1239

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):

Gottgtroy, Paulo. “An ontology driven knowledge discovery framework for Dynamic Domains: methodology, tools and a Biomedical case .” 2011. Thesis, AUT University. Accessed June 17, 2019. http://hdl.handle.net/10292/1239.

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

MLA Handbook (7th Edition):

Gottgtroy, Paulo. “An ontology driven knowledge discovery framework for Dynamic Domains: methodology, tools and a Biomedical case .” 2011. Web. 17 Jun 2019.

Vancouver:

Gottgtroy P. An ontology driven knowledge discovery framework for Dynamic Domains: methodology, tools and a Biomedical case . [Internet] [Thesis]. AUT University; 2011. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/10292/1239.

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

Council of Science Editors:

Gottgtroy P. An ontology driven knowledge discovery framework for Dynamic Domains: methodology, tools and a Biomedical case . [Thesis]. AUT University; 2011. Available from: http://hdl.handle.net/10292/1239

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


Central Connecticut State University

9. Murugan, Senthil K. (Senthil Kumar), 1973-. Mining for Profitable Low-Risk Delta-Neutral Long Straddle Option Strategies.

Degree: Department of Mathematical Sciences, 2012, Central Connecticut State University

This study provides a framework for identifying potential low-risk high-profit option strategies. Delta-neutral long straddle strategies are explored. These strategies are profitable when the underlying… (more)

Subjects/Keywords: Data mining.; Investments.

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APA (6th Edition):

Murugan, Senthil K. (Senthil Kumar), 1. (2012). Mining for Profitable Low-Risk Delta-Neutral Long Straddle Option Strategies. (Thesis). Central Connecticut State University. Retrieved from http://content.library.ccsu.edu/u?/ccsutheses,1816

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):

Murugan, Senthil K. (Senthil Kumar), 1973-. “Mining for Profitable Low-Risk Delta-Neutral Long Straddle Option Strategies.” 2012. Thesis, Central Connecticut State University. Accessed June 17, 2019. http://content.library.ccsu.edu/u?/ccsutheses,1816.

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

MLA Handbook (7th Edition):

Murugan, Senthil K. (Senthil Kumar), 1973-. “Mining for Profitable Low-Risk Delta-Neutral Long Straddle Option Strategies.” 2012. Web. 17 Jun 2019.

Vancouver:

Murugan, Senthil K. (Senthil Kumar) 1. Mining for Profitable Low-Risk Delta-Neutral Long Straddle Option Strategies. [Internet] [Thesis]. Central Connecticut State University; 2012. [cited 2019 Jun 17]. Available from: http://content.library.ccsu.edu/u?/ccsutheses,1816.

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

Council of Science Editors:

Murugan, Senthil K. (Senthil Kumar) 1. Mining for Profitable Low-Risk Delta-Neutral Long Straddle Option Strategies. [Thesis]. Central Connecticut State University; 2012. Available from: http://content.library.ccsu.edu/u?/ccsutheses,1816

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


Central Connecticut State University

10. Snyder, Jyota D. Mining Gene Expression Data Generated by Next Generation Sequencing Technology.

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

Next generation DNA sequencing (NGS) technology has emerged as a result of genomic research progress made related to the Human Genome Project. A protocol of… (more)

Subjects/Keywords: Data mining.; Genomics.

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APA (6th Edition):

Snyder, J. D. (2014). Mining Gene Expression Data Generated by Next Generation Sequencing Technology. (Thesis). Central Connecticut State University. Retrieved from http://content.library.ccsu.edu/u?/ccsutheses,2054

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):

Snyder, Jyota D. “Mining Gene Expression Data Generated by Next Generation Sequencing Technology.” 2014. Thesis, Central Connecticut State University. Accessed June 17, 2019. http://content.library.ccsu.edu/u?/ccsutheses,2054.

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

MLA Handbook (7th Edition):

Snyder, Jyota D. “Mining Gene Expression Data Generated by Next Generation Sequencing Technology.” 2014. Web. 17 Jun 2019.

Vancouver:

Snyder JD. Mining Gene Expression Data Generated by Next Generation Sequencing Technology. [Internet] [Thesis]. Central Connecticut State University; 2014. [cited 2019 Jun 17]. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2054.

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

Council of Science Editors:

Snyder JD. Mining Gene Expression Data Generated by Next Generation Sequencing Technology. [Thesis]. Central Connecticut State University; 2014. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2054

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


Central Connecticut State University

11. Farrell, Cathy L., 1958-. Trinary Predictive Classification of Diabetic Episode Recurrence.

Degree: Department of Mathematical Sciences, 2016, Central Connecticut State University

This thesis explores the value of trinary predictive modeling to the understanding of diabetesrelated hospitalizations. According the U.S. Centers for Disease Control and Prevention, diabetes… (more)

Subjects/Keywords: Data mining.; Diabetes.

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APA (6th Edition):

Farrell, Cathy L., 1. (2016). Trinary Predictive Classification of Diabetic Episode Recurrence. (Thesis). Central Connecticut State University. Retrieved from http://content.library.ccsu.edu/u?/ccsutheses,2296

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):

Farrell, Cathy L., 1958-. “Trinary Predictive Classification of Diabetic Episode Recurrence.” 2016. Thesis, Central Connecticut State University. Accessed June 17, 2019. http://content.library.ccsu.edu/u?/ccsutheses,2296.

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

MLA Handbook (7th Edition):

Farrell, Cathy L., 1958-. “Trinary Predictive Classification of Diabetic Episode Recurrence.” 2016. Web. 17 Jun 2019.

Vancouver:

Farrell, Cathy L. 1. Trinary Predictive Classification of Diabetic Episode Recurrence. [Internet] [Thesis]. Central Connecticut State University; 2016. [cited 2019 Jun 17]. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2296.

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

Council of Science Editors:

Farrell, Cathy L. 1. Trinary Predictive Classification of Diabetic Episode Recurrence. [Thesis]. Central Connecticut State University; 2016. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2296

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


Central Connecticut State University

12. Ironside, Brian Michael, 1978-. Improving the Performance of Ensemble Classifier Models through the Local Specialization of Base Classifiers.

Degree: Department of Mathematical Sciences, 2016, Central Connecticut State University

Two approaches are tested to improve the predictive performance of classification ensembles, individually, and in combination. Eight datasets from the UCI machine learning repository are… (more)

Subjects/Keywords: Data mining.; Classification.

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APA (6th Edition):

Ironside, Brian Michael, 1. (2016). Improving the Performance of Ensemble Classifier Models through the Local Specialization of Base Classifiers. (Thesis). Central Connecticut State University. Retrieved from http://content.library.ccsu.edu/u?/ccsutheses,2357

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):

Ironside, Brian Michael, 1978-. “Improving the Performance of Ensemble Classifier Models through the Local Specialization of Base Classifiers.” 2016. Thesis, Central Connecticut State University. Accessed June 17, 2019. http://content.library.ccsu.edu/u?/ccsutheses,2357.

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

MLA Handbook (7th Edition):

Ironside, Brian Michael, 1978-. “Improving the Performance of Ensemble Classifier Models through the Local Specialization of Base Classifiers.” 2016. Web. 17 Jun 2019.

Vancouver:

Ironside, Brian Michael 1. Improving the Performance of Ensemble Classifier Models through the Local Specialization of Base Classifiers. [Internet] [Thesis]. Central Connecticut State University; 2016. [cited 2019 Jun 17]. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2357.

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

Council of Science Editors:

Ironside, Brian Michael 1. Improving the Performance of Ensemble Classifier Models through the Local Specialization of Base Classifiers. [Thesis]. Central Connecticut State University; 2016. Available from: http://content.library.ccsu.edu/u?/ccsutheses,2357

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


University of Southern California

13. Lim, Jongwoo. An efficient approach to clustering datasets with mixed type attributes in data mining.

Degree: PhD, Computer Science, 2013, University of Southern California

 We propose an efficient approach to clustering datasets with mixed type attributes (both numerical and categorical), while minimizing information loss during clustering. Real world datasets… (more)

Subjects/Keywords: clustering; data mining

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APA (6th Edition):

Lim, J. (2013). An efficient approach to clustering datasets with mixed type attributes in data mining. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/333350/rec/695

Chicago Manual of Style (16th Edition):

Lim, Jongwoo. “An efficient approach to clustering datasets with mixed type attributes in data mining.” 2013. Doctoral Dissertation, University of Southern California. Accessed June 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/333350/rec/695.

MLA Handbook (7th Edition):

Lim, Jongwoo. “An efficient approach to clustering datasets with mixed type attributes in data mining.” 2013. Web. 17 Jun 2019.

Vancouver:

Lim J. An efficient approach to clustering datasets with mixed type attributes in data mining. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Jun 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/333350/rec/695.

Council of Science Editors:

Lim J. An efficient approach to clustering datasets with mixed type attributes in data mining. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/333350/rec/695


University of Debrecen

14. Kocsis, Annamária. Data Mining Algorithm in Bi-Clustering Applications .

Degree: DE – TEK – Informatikai Kar, 2009, University of Debrecen

A szakdolgozat célja a biclustering, mint technika bemutatása, és az adatbányászat e biológiai alkalmazásának, gyakorlati szinten történő illusztrációja. Advisors/Committee Members: Ispány, Márton (advisor).

Subjects/Keywords: Biclustering; Data Mining

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APA (6th Edition):

Kocsis, A. (2009). Data Mining Algorithm in Bi-Clustering Applications . (Thesis). University of Debrecen. Retrieved from http://hdl.handle.net/2437/85461

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):

Kocsis, Annamária. “Data Mining Algorithm in Bi-Clustering Applications .” 2009. Thesis, University of Debrecen. Accessed June 17, 2019. http://hdl.handle.net/2437/85461.

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

MLA Handbook (7th Edition):

Kocsis, Annamária. “Data Mining Algorithm in Bi-Clustering Applications .” 2009. Web. 17 Jun 2019.

Vancouver:

Kocsis A. Data Mining Algorithm in Bi-Clustering Applications . [Internet] [Thesis]. University of Debrecen; 2009. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/2437/85461.

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

Council of Science Editors:

Kocsis A. Data Mining Algorithm in Bi-Clustering Applications . [Thesis]. University of Debrecen; 2009. Available from: http://hdl.handle.net/2437/85461

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


University of Texas – Austin

15. -2916-0908. PM2.5 study : explore PM2.5 in Beijing using data mining methods and social media data.

Degree: Information, 2016, University of Texas – Austin

 Air pollution is one of the worst outcomes from industrialization. Among other air pollutants, PM2.5 is believed to pose the greatest risks to human health… (more)

Subjects/Keywords: Data mining; Weibo

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

APA (6th Edition):

-2916-0908. (2016). PM2.5 study : explore PM2.5 in Beijing using data mining methods and social media data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/45792

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

Chicago Manual of Style (16th Edition):

-2916-0908. “PM2.5 study : explore PM2.5 in Beijing using data mining methods and social media data.” 2016. Thesis, University of Texas – Austin. Accessed June 17, 2019. http://hdl.handle.net/2152/45792.

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

MLA Handbook (7th Edition):

-2916-0908. “PM2.5 study : explore PM2.5 in Beijing using data mining methods and social media data.” 2016. Web. 17 Jun 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-2916-0908. PM2.5 study : explore PM2.5 in Beijing using data mining methods and social media data. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/2152/45792.

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

Council of Science Editors:

-2916-0908. PM2.5 study : explore PM2.5 in Beijing using data mining methods and social media data. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/45792

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


University of Manitoba

16. Jiang, Fan. Frequent pattern mining of uncertain data streams.

Degree: Computer Science, 2011, University of Manitoba

 When dealing with uncertain data, users may not be certain about the presence of an item in the database. For example, due to inherent instrumental… (more)

Subjects/Keywords: Data mining; Databases

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APA (6th Edition):

Jiang, F. (2011). Frequent pattern mining of uncertain data streams. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/5233

Chicago Manual of Style (16th Edition):

Jiang, Fan. “Frequent pattern mining of uncertain data streams.” 2011. Masters Thesis, University of Manitoba. Accessed June 17, 2019. http://hdl.handle.net/1993/5233.

MLA Handbook (7th Edition):

Jiang, Fan. “Frequent pattern mining of uncertain data streams.” 2011. Web. 17 Jun 2019.

Vancouver:

Jiang F. Frequent pattern mining of uncertain data streams. [Internet] [Masters thesis]. University of Manitoba; 2011. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/1993/5233.

Council of Science Editors:

Jiang F. Frequent pattern mining of uncertain data streams. [Masters Thesis]. University of Manitoba; 2011. Available from: http://hdl.handle.net/1993/5233


University of Manitoba

17. MacKinnon, Richard Kyle. Seeing the forest for the trees: tree-based uncertain frequent pattern mining.

Degree: Computer Science, 2014, University of Manitoba

 Many frequent pattern mining algorithms operate on precise data, where each data point is an exact accounting of a phenomena (e.g., I have exactly two… (more)

Subjects/Keywords: Data mining; Databases

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APA (6th Edition):

MacKinnon, R. K. (2014). Seeing the forest for the trees: tree-based uncertain frequent pattern mining. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/31059

Chicago Manual of Style (16th Edition):

MacKinnon, Richard Kyle. “Seeing the forest for the trees: tree-based uncertain frequent pattern mining.” 2014. Masters Thesis, University of Manitoba. Accessed June 17, 2019. http://hdl.handle.net/1993/31059.

MLA Handbook (7th Edition):

MacKinnon, Richard Kyle. “Seeing the forest for the trees: tree-based uncertain frequent pattern mining.” 2014. Web. 17 Jun 2019.

Vancouver:

MacKinnon RK. Seeing the forest for the trees: tree-based uncertain frequent pattern mining. [Internet] [Masters thesis]. University of Manitoba; 2014. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/1993/31059.

Council of Science Editors:

MacKinnon RK. Seeing the forest for the trees: tree-based uncertain frequent pattern mining. [Masters Thesis]. University of Manitoba; 2014. Available from: http://hdl.handle.net/1993/31059


IUPUI

18. Peng, Bo. Applications of Data Mining in Healthcare.

Degree: 2019, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

With increases in the quantity and quality of healthcare related data, data mining tools have the potential to improve people’s… (more)

Subjects/Keywords: Data mining; Healthcare

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APA (6th Edition):

Peng, B. (2019). Applications of Data Mining in Healthcare. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/18933

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):

Peng, Bo. “Applications of Data Mining in Healthcare.” 2019. Thesis, IUPUI. Accessed June 17, 2019. http://hdl.handle.net/1805/18933.

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

MLA Handbook (7th Edition):

Peng, Bo. “Applications of Data Mining in Healthcare.” 2019. Web. 17 Jun 2019.

Vancouver:

Peng B. Applications of Data Mining in Healthcare. [Internet] [Thesis]. IUPUI; 2019. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/1805/18933.

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

Council of Science Editors:

Peng B. Applications of Data Mining in Healthcare. [Thesis]. IUPUI; 2019. Available from: http://hdl.handle.net/1805/18933

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


Montana State University

19. Ganesan Pillai, Karthik. Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions.

Degree: College of Engineering, 2014, Montana State University

 Due to the current rates of data acquisition, the growth of data volumes in nearly all domains of our lives is reaching historic proportions [5],… (more)

Subjects/Keywords: Data mining.; Big data.

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APA (6th Edition):

Ganesan Pillai, K. (2014). Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions. (Thesis). Montana State University. Retrieved from https://scholarworks.montana.edu/xmlui/handle/1/9422

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):

Ganesan Pillai, Karthik. “Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions.” 2014. Thesis, Montana State University. Accessed June 17, 2019. https://scholarworks.montana.edu/xmlui/handle/1/9422.

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

MLA Handbook (7th Edition):

Ganesan Pillai, Karthik. “Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions.” 2014. Web. 17 Jun 2019.

Vancouver:

Ganesan Pillai K. Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions. [Internet] [Thesis]. Montana State University; 2014. [cited 2019 Jun 17]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/9422.

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

Council of Science Editors:

Ganesan Pillai K. Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions. [Thesis]. Montana State University; 2014. Available from: https://scholarworks.montana.edu/xmlui/handle/1/9422

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

20. Chung, David H. S. High-dimensional glyph-based visualization and interactive techniques.

Degree: PhD, 2014, Swansea University

 The advancement of modern technology and scientific measurements has led to datasets growing in both size and complexity, exposing the need for more efficient and… (more)

Subjects/Keywords: 004; Data mining; Data processing

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APA (6th Edition):

Chung, D. H. S. (2014). High-dimensional glyph-based visualization and interactive techniques. (Doctoral Dissertation). Swansea University. Retrieved from https://cronfa.swan.ac.uk/Record/cronfa42276 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.678364

Chicago Manual of Style (16th Edition):

Chung, David H S. “High-dimensional glyph-based visualization and interactive techniques.” 2014. Doctoral Dissertation, Swansea University. Accessed June 17, 2019. https://cronfa.swan.ac.uk/Record/cronfa42276 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.678364.

MLA Handbook (7th Edition):

Chung, David H S. “High-dimensional glyph-based visualization and interactive techniques.” 2014. Web. 17 Jun 2019.

Vancouver:

Chung DHS. High-dimensional glyph-based visualization and interactive techniques. [Internet] [Doctoral dissertation]. Swansea University; 2014. [cited 2019 Jun 17]. Available from: https://cronfa.swan.ac.uk/Record/cronfa42276 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.678364.

Council of Science Editors:

Chung DHS. High-dimensional glyph-based visualization and interactive techniques. [Doctoral Dissertation]. Swansea University; 2014. Available from: https://cronfa.swan.ac.uk/Record/cronfa42276 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.678364


University of Texas – Austin

21. -3478-7289. Clinically interpretable models for healthcare data.

Degree: Electrical and Computer Engineering, 2015, University of Texas – Austin

 The increasing availability of electronic health records (EHRs) has spurred the adoption of data-driven approaches to provide additional insights for diagnoses, prognoses, and cost-effective patient… (more)

Subjects/Keywords: Data mining; Healthcare data

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APA (6th Edition):

-3478-7289. (2015). Clinically interpretable models for healthcare data. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/33383

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

Chicago Manual of Style (16th Edition):

-3478-7289. “Clinically interpretable models for healthcare data.” 2015. Thesis, University of Texas – Austin. Accessed June 17, 2019. http://hdl.handle.net/2152/33383.

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

MLA Handbook (7th Edition):

-3478-7289. “Clinically interpretable models for healthcare data.” 2015. Web. 17 Jun 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-3478-7289. Clinically interpretable models for healthcare data. [Internet] [Thesis]. University of Texas – Austin; 2015. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/2152/33383.

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

Council of Science Editors:

-3478-7289. Clinically interpretable models for healthcare data. [Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/33383

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


McMaster University

22. Al-janabi, Samir. An Integrated Approach to Improve Data Quality.

Degree: PhD, 2016, McMaster University

Thesis

A huge quantity of data is created and saved everyday in databases from different types of data sources, including financial data, web log data,… (more)

Subjects/Keywords: data management; data quality; data mining

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APA (6th Edition):

Al-janabi, S. (2016). An Integrated Approach to Improve Data Quality. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/19161

Chicago Manual of Style (16th Edition):

Al-janabi, Samir. “An Integrated Approach to Improve Data Quality.” 2016. Doctoral Dissertation, McMaster University. Accessed June 17, 2019. http://hdl.handle.net/11375/19161.

MLA Handbook (7th Edition):

Al-janabi, Samir. “An Integrated Approach to Improve Data Quality.” 2016. Web. 17 Jun 2019.

Vancouver:

Al-janabi S. An Integrated Approach to Improve Data Quality. [Internet] [Doctoral dissertation]. McMaster University; 2016. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/11375/19161.

Council of Science Editors:

Al-janabi S. An Integrated Approach to Improve Data Quality. [Doctoral Dissertation]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/19161


AUT University

23. 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 (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 June 17, 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. 17 Jun 2019.

Vancouver:

Vithal Kadam O. Novel applications of Association Rule Mining- Data Stream Mining . [Internet] [Thesis]. AUT University; 2010. [cited 2019 Jun 17]. 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

24. 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 (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 June 17, 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. 17 Jun 2019.

Vancouver:

Science UoLFoAa. Two new approaches to evaluate association rules . [Internet] [Thesis]. University of Lethbridge; 2010. [cited 2019 Jun 17]. 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


University of Manitoba

25. Zhang, Hao. Scalable vertical mining for big data analytics.

Degree: Computer Science, 2016, University of Manitoba

 The increasing size of modern applications produces huge amounts of data, which in turn leads to a new challenge to data mining or big data(more)

Subjects/Keywords: Data mining; Frequent pattern mining; Big data; Data analytics

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APA (6th Edition):

Zhang, H. (2016). Scalable vertical mining for big data analytics. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/31951

Chicago Manual of Style (16th Edition):

Zhang, Hao. “Scalable vertical mining for big data analytics.” 2016. Masters Thesis, University of Manitoba. Accessed June 17, 2019. http://hdl.handle.net/1993/31951.

MLA Handbook (7th Edition):

Zhang, Hao. “Scalable vertical mining for big data analytics.” 2016. Web. 17 Jun 2019.

Vancouver:

Zhang H. Scalable vertical mining for big data analytics. [Internet] [Masters thesis]. University of Manitoba; 2016. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/1993/31951.

Council of Science Editors:

Zhang H. Scalable vertical mining for big data analytics. [Masters Thesis]. University of Manitoba; 2016. Available from: http://hdl.handle.net/1993/31951


North Carolina State University

26. Chopra, Pankaj. Data Mining Techniques to Enable Large-scale Exploratory Analysis of Heterogeneous Scientific Data.

Degree: PhD, Computer Science, 2009, North Carolina State University

 Recent advances in microarray technology have enabled scientists to simultaneously gather data on thousands of genes. However, due to the complexity of genetic interactions, the… (more)

Subjects/Keywords: pathway analysis; data mining; gene expression; data mining genetic pathways; microarray data mining; microarray clustering

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

APA (6th Edition):

Chopra, P. (2009). Data Mining Techniques to Enable Large-scale Exploratory Analysis of Heterogeneous Scientific Data. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/4168

Chicago Manual of Style (16th Edition):

Chopra, Pankaj. “Data Mining Techniques to Enable Large-scale Exploratory Analysis of Heterogeneous Scientific Data.” 2009. Doctoral Dissertation, North Carolina State University. Accessed June 17, 2019. http://www.lib.ncsu.edu/resolver/1840.16/4168.

MLA Handbook (7th Edition):

Chopra, Pankaj. “Data Mining Techniques to Enable Large-scale Exploratory Analysis of Heterogeneous Scientific Data.” 2009. Web. 17 Jun 2019.

Vancouver:

Chopra P. Data Mining Techniques to Enable Large-scale Exploratory Analysis of Heterogeneous Scientific Data. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 Jun 17]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4168.

Council of Science Editors:

Chopra P. Data Mining Techniques to Enable Large-scale Exploratory Analysis of Heterogeneous Scientific Data. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4168


Anna University

27. Indumathi J. Data mystification for optimised and Efficacious privacy preserving data Mining;.

Degree: Data mystification for optimised and Efficacious privacy preserving data Mining, 2014, Anna University

The world has entered into the information era and the human newlinerace is forced to join in the forefront of the imminent technology The newlinerapid… (more)

Subjects/Keywords: Privacy preserving Data Mining

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APA (6th Edition):

J, I. (2014). Data mystification for optimised and Efficacious privacy preserving data Mining;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/28073

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):

J, Indumathi. “Data mystification for optimised and Efficacious privacy preserving data Mining;.” 2014. Thesis, Anna University. Accessed June 17, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/28073.

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

MLA Handbook (7th Edition):

J, Indumathi. “Data mystification for optimised and Efficacious privacy preserving data Mining;.” 2014. Web. 17 Jun 2019.

Vancouver:

J I. Data mystification for optimised and Efficacious privacy preserving data Mining;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Jun 17]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28073.

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

Council of Science Editors:

J I. Data mystification for optimised and Efficacious privacy preserving data Mining;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28073

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

28. Nekkaa, Messaouda. Une approche SVM-méta-heuristique pour laclassification : application à l'information médicale.

Degree: 2016, Université M'Hamed Bougara Boumerdès

108 p. : ill. ; 30 cm

Ce projet de doctorat porte sur la r esolution du problème de classifcation de donn ees médicales par… (more)

Subjects/Keywords: Algorithmes : Informatique; Data mining

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APA (6th Edition):

Nekkaa, M. (2016). Une approche SVM-méta-heuristique pour laclassification : application à l'information médicale. (Thesis). Université M'Hamed Bougara Boumerdès. Retrieved from http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/2981

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):

Nekkaa, Messaouda. “Une approche SVM-méta-heuristique pour laclassification : application à l'information médicale.” 2016. Thesis, Université M'Hamed Bougara Boumerdès. Accessed June 17, 2019. http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/2981.

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

MLA Handbook (7th Edition):

Nekkaa, Messaouda. “Une approche SVM-méta-heuristique pour laclassification : application à l'information médicale.” 2016. Web. 17 Jun 2019.

Vancouver:

Nekkaa M. Une approche SVM-méta-heuristique pour laclassification : application à l'information médicale. [Internet] [Thesis]. Université M'Hamed Bougara Boumerdès; 2016. [cited 2019 Jun 17]. Available from: http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/2981.

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

Council of Science Editors:

Nekkaa M. Une approche SVM-méta-heuristique pour laclassification : application à l'information médicale. [Thesis]. Université M'Hamed Bougara Boumerdès; 2016. Available from: http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/2981

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


University of Utah

29. Zhuo, Yang. Knowledge discovery from databases: cost-sensitive and imbalance learning.

Degree: PhD, Operations Management (The David Eccles School of Business), 2010, University of Utah

 In the current business world, data collection for business analysis is not difficult any more. The major concern faced by business managers is whether they… (more)

Subjects/Keywords: Data mining; Knowledge acquisition

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APA (6th Edition):

Zhuo, Y. (2010). Knowledge discovery from databases: cost-sensitive and imbalance learning. (Doctoral Dissertation). University of Utah. Retrieved from http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/589/rec/1455

Chicago Manual of Style (16th Edition):

Zhuo, Yang. “Knowledge discovery from databases: cost-sensitive and imbalance learning.” 2010. Doctoral Dissertation, University of Utah. Accessed June 17, 2019. http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/589/rec/1455.

MLA Handbook (7th Edition):

Zhuo, Yang. “Knowledge discovery from databases: cost-sensitive and imbalance learning.” 2010. Web. 17 Jun 2019.

Vancouver:

Zhuo Y. Knowledge discovery from databases: cost-sensitive and imbalance learning. [Internet] [Doctoral dissertation]. University of Utah; 2010. [cited 2019 Jun 17]. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/589/rec/1455.

Council of Science Editors:

Zhuo Y. Knowledge discovery from databases: cost-sensitive and imbalance learning. [Doctoral Dissertation]. University of Utah; 2010. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/589/rec/1455


Cornell University

30. Soundarajan, Sucheta. Communities In Social Networks .

Degree: 2013, Cornell University

 Within the broad area of social network analysis research, the study of communities has become an important and popular topic. However, there is little consensus… (more)

Subjects/Keywords: data mining; social networks; communities

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APA (6th Edition):

Soundarajan, S. (2013). Communities In Social Networks . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/34083

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):

Soundarajan, Sucheta. “Communities In Social Networks .” 2013. Thesis, Cornell University. Accessed June 17, 2019. http://hdl.handle.net/1813/34083.

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

MLA Handbook (7th Edition):

Soundarajan, Sucheta. “Communities In Social Networks .” 2013. Web. 17 Jun 2019.

Vancouver:

Soundarajan S. Communities In Social Networks . [Internet] [Thesis]. Cornell University; 2013. [cited 2019 Jun 17]. Available from: http://hdl.handle.net/1813/34083.

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

Council of Science Editors:

Soundarajan S. Communities In Social Networks . [Thesis]. Cornell University; 2013. Available from: http://hdl.handle.net/1813/34083

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

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