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You searched for subject:(Data mining ). Showing records 1 – 30 of 3645 total matches.

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Central Connecticut State University

1. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Adu-Poku, Sampson 1. Comparing classification algorithms in data mining. [Internet] [Thesis]. Central Connecticut State University; 2012. [cited 2020 Jul 08]. 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

2. 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 July 08, 2020. http://hdl.handle.net/1993/33337.

MLA Handbook (7th Edition):

Yu, Jialiang. “Fast and scalable MapReduce-based vertical mining.” 2018. Web. 08 Jul 2020.

Vancouver:

Yu J. Fast and scalable MapReduce-based vertical mining. [Internet] [Masters thesis]. University of Manitoba; 2018. [cited 2020 Jul 08]. 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


Rutgers University

3. Agrawal, Aayush, 1989-. Yelp analytics.

Degree: MS, Computer Science, 2017, Rutgers University

 Yelp is a website and mobile app which publishes crowd-sourced reviews about local businesses. In this thesis, we analyze data about restaurants from Yelp, specifically… (more)

Subjects/Keywords: Data mining

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APA (6th Edition):

Agrawal, Aayush, 1. (2017). Yelp analytics. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/52036/

Chicago Manual of Style (16th Edition):

Agrawal, Aayush, 1989-. “Yelp analytics.” 2017. Masters Thesis, Rutgers University. Accessed July 08, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/52036/.

MLA Handbook (7th Edition):

Agrawal, Aayush, 1989-. “Yelp analytics.” 2017. Web. 08 Jul 2020.

Vancouver:

Agrawal, Aayush 1. Yelp analytics. [Internet] [Masters thesis]. Rutgers University; 2017. [cited 2020 Jul 08]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/52036/.

Council of Science Editors:

Agrawal, Aayush 1. Yelp analytics. [Masters Thesis]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/52036/


Cornell University

4. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Haque A. Information And Social System Interaction . [Internet] [Thesis]. Cornell University; 2011. [cited 2020 Jul 08]. 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


Queens University

5. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Lamb C. Detecting Deception in Interrogation Settings . [Internet] [Thesis]. Queens University; 2012. [cited 2020 Jul 08]. 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


Central Connecticut State University

6. 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 July 08, 2020. 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. 08 Jul 2020.

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 2020 Jul 08]. 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

7. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Snyder JD. Mining Gene Expression Data Generated by Next Generation Sequencing Technology. [Internet] [Thesis]. Central Connecticut State University; 2014. [cited 2020 Jul 08]. 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

8. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Farrell, Cathy L. 1. Trinary Predictive Classification of Diabetic Episode Recurrence. [Internet] [Thesis]. Central Connecticut State University; 2016. [cited 2020 Jul 08]. 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

9. 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 July 08, 2020. 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. 08 Jul 2020.

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 2020 Jul 08]. 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 Manitoba

10. 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 July 08, 2020. http://hdl.handle.net/1993/5233.

MLA Handbook (7th Edition):

Jiang, Fan. “Frequent pattern mining of uncertain data streams.” 2011. Web. 08 Jul 2020.

Vancouver:

Jiang F. Frequent pattern mining of uncertain data streams. [Internet] [Masters thesis]. University of Manitoba; 2011. [cited 2020 Jul 08]. 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

11. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

MacKinnon RK. Seeing the forest for the trees: tree-based uncertain frequent pattern mining. [Internet] [Masters thesis]. University of Manitoba; 2014. [cited 2020 Jul 08]. 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


University of Texas – Austin

12. -2916-0908. PM2.5 study : explore PM2.5 in Beijing using data mining methods and social media data.

Degree: MSin Information Studies, Information studies, 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 (6th Edition):

-2916-0908. (2016). PM2.5 study : explore PM2.5 in Beijing using data mining methods and social media data. (Masters 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

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. Masters Thesis, University of Texas – Austin. Accessed July 08, 2020. http://hdl.handle.net/2152/45792.

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

MLA Handbook (7th Edition):

-2916-0908. “PM2.5 study : explore PM2.5 in Beijing using data mining methods and social media data.” 2016. Web. 08 Jul 2020.

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] [Masters thesis]. University of Texas – Austin; 2016. [cited 2020 Jul 08]. 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

Council of Science Editors:

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


Rutgers University

13. Patel, Saad. Art ticker: discovering emerging artists on the web.

Degree: MS, Computer Science, 2016, Rutgers University

 Considering the large number of artists that exist, there is valuable talent to be discovered. But the question arises, how to find promising and emerging… (more)

Subjects/Keywords: Artists; Data mining

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APA (6th Edition):

Patel, S. (2016). Art ticker: discovering emerging artists on the web. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/49276/

Chicago Manual of Style (16th Edition):

Patel, Saad. “Art ticker: discovering emerging artists on the web.” 2016. Masters Thesis, Rutgers University. Accessed July 08, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/49276/.

MLA Handbook (7th Edition):

Patel, Saad. “Art ticker: discovering emerging artists on the web.” 2016. Web. 08 Jul 2020.

Vancouver:

Patel S. Art ticker: discovering emerging artists on the web. [Internet] [Masters thesis]. Rutgers University; 2016. [cited 2020 Jul 08]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/49276/.

Council of Science Editors:

Patel S. Art ticker: discovering emerging artists on the web. [Masters Thesis]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/49276/


AUT University

14. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Gottgtroy P. An ontology driven knowledge discovery framework for Dynamic Domains: methodology, tools and a Biomedical case . [Internet] [Thesis]. AUT University; 2011. [cited 2020 Jul 08]. 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


University of Southern California

15. 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 July 08, 2020. 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. 08 Jul 2020.

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 2020 Jul 08]. 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


Montana State University

16. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Ganesan Pillai K. Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions. [Internet] [Thesis]. Montana State University; 2014. [cited 2020 Jul 08]. 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


Rutgers University

17. Patel, Jimit. Real time big data mining.

Degree: MS, Computer Science, 2015, Rutgers University

 This thesis presents a parallel implementation of data streaming algorithms for multiple streams. Thousands of data streams are generated in different industries like finance, health,… (more)

Subjects/Keywords: Big data; Data mining

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APA (6th Edition):

Patel, J. (2015). Real time big data mining. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/49077/

Chicago Manual of Style (16th Edition):

Patel, Jimit. “Real time big data mining.” 2015. Masters Thesis, Rutgers University. Accessed July 08, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/49077/.

MLA Handbook (7th Edition):

Patel, Jimit. “Real time big data mining.” 2015. Web. 08 Jul 2020.

Vancouver:

Patel J. Real time big data mining. [Internet] [Masters thesis]. Rutgers University; 2015. [cited 2020 Jul 08]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/49077/.

Council of Science Editors:

Patel J. Real time big data mining. [Masters Thesis]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/49077/

18. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Chung DHS. High-dimensional glyph-based visualization and interactive techniques. [Internet] [Doctoral dissertation]. Swansea University; 2014. [cited 2020 Jul 08]. 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


McMaster University

19. 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 July 08, 2020. http://hdl.handle.net/11375/19161.

MLA Handbook (7th Edition):

Al-janabi, Samir. “An Integrated Approach to Improve Data Quality.” 2016. Web. 08 Jul 2020.

Vancouver:

Al-janabi S. An Integrated Approach to Improve Data Quality. [Internet] [Doctoral dissertation]. McMaster University; 2016. [cited 2020 Jul 08]. 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


University of Lethbridge

20. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Science UoLFoAa. Two new approaches to evaluate association rules . [Internet] [Thesis]. University of Lethbridge; 2010. [cited 2020 Jul 08]. 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


AUT University

21. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Vithal Kadam O. Novel applications of Association Rule Mining- Data Stream Mining . [Internet] [Thesis]. AUT University; 2010. [cited 2020 Jul 08]. 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 Manitoba

22. 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 July 08, 2020. http://hdl.handle.net/1993/31951.

MLA Handbook (7th Edition):

Zhang, Hao. “Scalable vertical mining for big data analytics.” 2016. Web. 08 Jul 2020.

Vancouver:

Zhang H. Scalable vertical mining for big data analytics. [Internet] [Masters thesis]. University of Manitoba; 2016. [cited 2020 Jul 08]. 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


University of Manitoba

23. Pawliszak, Tomasz. An operon-based data science approach for the inference of tRNA and rRNA gene evolution.

Degree: Computer Science, 2019, University of Manitoba

 With advancements in technology, big data can be easily generated and collected. Big data mining and analytics is in demand for discovery of important information… (more)

Subjects/Keywords: Data mining; Data science; Bioinformatics; Biological data mining

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APA (6th Edition):

Pawliszak, T. (2019). An operon-based data science approach for the inference of tRNA and rRNA gene evolution. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/34397

Chicago Manual of Style (16th Edition):

Pawliszak, Tomasz. “An operon-based data science approach for the inference of tRNA and rRNA gene evolution.” 2019. Masters Thesis, University of Manitoba. Accessed July 08, 2020. http://hdl.handle.net/1993/34397.

MLA Handbook (7th Edition):

Pawliszak, Tomasz. “An operon-based data science approach for the inference of tRNA and rRNA gene evolution.” 2019. Web. 08 Jul 2020.

Vancouver:

Pawliszak T. An operon-based data science approach for the inference of tRNA and rRNA gene evolution. [Internet] [Masters thesis]. University of Manitoba; 2019. [cited 2020 Jul 08]. Available from: http://hdl.handle.net/1993/34397.

Council of Science Editors:

Pawliszak T. An operon-based data science approach for the inference of tRNA and rRNA gene evolution. [Masters Thesis]. University of Manitoba; 2019. Available from: http://hdl.handle.net/1993/34397


North Carolina State University

24. 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 July 08, 2020. 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. 08 Jul 2020.

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 2020 Jul 08]. 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

25. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

J I. Data mystification for optimised and Efficacious privacy preserving data Mining;. [Internet] [Thesis]. Anna University; 2014. [cited 2020 Jul 08]. 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

26. 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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Nekkaa M. Une approche SVM-méta-heuristique pour laclassification : application à l'information médicale. [Internet] [Thesis]. Université M'Hamed Bougara Boumerdès; 2016. [cited 2020 Jul 08]. 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

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

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 July 08, 2020. 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. 08 Jul 2020.

Vancouver:

Zhuo Y. Knowledge discovery from databases: cost-sensitive and imbalance learning. [Internet] [Doctoral dissertation]. University of Utah; 2010. [cited 2020 Jul 08]. 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


Penn State University

28. Iyer, Karthik Thyagarajan. Computational complexity of data mining algorithms used in fraud detection.

Degree: MS, Industrial Engineering, 2015, Penn State University

 According to estimates by certain government agencies, 10% of the total medical expenditure is lost to healthcare fraud. Similarly the credit card industry loses billions… (more)

Subjects/Keywords: Data mining; Complexity; Big O

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APA (6th Edition):

Iyer, K. T. (2015). Computational complexity of data mining algorithms used in fraud detection. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/26437

Chicago Manual of Style (16th Edition):

Iyer, Karthik Thyagarajan. “Computational complexity of data mining algorithms used in fraud detection.” 2015. Masters Thesis, Penn State University. Accessed July 08, 2020. https://etda.libraries.psu.edu/catalog/26437.

MLA Handbook (7th Edition):

Iyer, Karthik Thyagarajan. “Computational complexity of data mining algorithms used in fraud detection.” 2015. Web. 08 Jul 2020.

Vancouver:

Iyer KT. Computational complexity of data mining algorithms used in fraud detection. [Internet] [Masters thesis]. Penn State University; 2015. [cited 2020 Jul 08]. Available from: https://etda.libraries.psu.edu/catalog/26437.

Council of Science Editors:

Iyer KT. Computational complexity of data mining algorithms used in fraud detection. [Masters Thesis]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/26437


Penn State University

29. Polim, Rico. Real-Time Supply Chain Analytics - Shipment Duration Prediction.

Degree: MS, Industrial Engineering, 2016, Penn State University

 In today’s world, global manufacturing requires parts supplied from countries all over the world. Affordable labor cost in developing countries, coupled with the proximity to… (more)

Subjects/Keywords: Logistics; Data Mining; Forecasting

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APA (6th Edition):

Polim, R. (2016). Real-Time Supply Chain Analytics - Shipment Duration Prediction. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/13480rzp5177

Chicago Manual of Style (16th Edition):

Polim, Rico. “Real-Time Supply Chain Analytics - Shipment Duration Prediction.” 2016. Masters Thesis, Penn State University. Accessed July 08, 2020. https://etda.libraries.psu.edu/catalog/13480rzp5177.

MLA Handbook (7th Edition):

Polim, Rico. “Real-Time Supply Chain Analytics - Shipment Duration Prediction.” 2016. Web. 08 Jul 2020.

Vancouver:

Polim R. Real-Time Supply Chain Analytics - Shipment Duration Prediction. [Internet] [Masters thesis]. Penn State University; 2016. [cited 2020 Jul 08]. Available from: https://etda.libraries.psu.edu/catalog/13480rzp5177.

Council of Science Editors:

Polim R. Real-Time Supply Chain Analytics - Shipment Duration Prediction. [Masters Thesis]. Penn State University; 2016. Available from: https://etda.libraries.psu.edu/catalog/13480rzp5177


Penn State University

30. Hu, Xiaocheng. DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH.

Degree: MS, Industrial Engineering, 2015, Penn State University

 Most of the researches on corporate filling mainly focus on qualitative analysis. This thesis used quantitative method-Bayesian Learning Machine in analyzing the information content of… (more)

Subjects/Keywords: data mining; text analysis; Perl

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APA (6th Edition):

Hu, X. (2015). DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/25731

Chicago Manual of Style (16th Edition):

Hu, Xiaocheng. “DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH.” 2015. Masters Thesis, Penn State University. Accessed July 08, 2020. https://etda.libraries.psu.edu/catalog/25731.

MLA Handbook (7th Edition):

Hu, Xiaocheng. “DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH.” 2015. Web. 08 Jul 2020.

Vancouver:

Hu X. DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH. [Internet] [Masters thesis]. Penn State University; 2015. [cited 2020 Jul 08]. Available from: https://etda.libraries.psu.edu/catalog/25731.

Council of Science Editors:

Hu X. DATA MINING ON CORPORATE FILLING BASED ON BAYESIAN LEARNING APPROACH. [Masters Thesis]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/25731

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