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You searched for subject:(Text classification). Showing records 1 – 30 of 266 total matches.

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Université de Neuchâtel

1. Kummer, Olena. Feature weighting approaches in sentiment analysis of short text.

Degree: 2012, Université de Neuchâtel

 In this thesis, we propose a supervised classification scheme based on computation of the statistical scores for the textual features. More specifically, we consider binary… (more)

Subjects/Keywords: Text Classification

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

APA (6th Edition):

Kummer, O. (2012). Feature weighting approaches in sentiment analysis of short text. (Thesis). Université de Neuchâtel. Retrieved from http://doc.rero.ch/record/30954

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):

Kummer, Olena. “Feature weighting approaches in sentiment analysis of short text.” 2012. Thesis, Université de Neuchâtel. Accessed May 26, 2019. http://doc.rero.ch/record/30954.

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

MLA Handbook (7th Edition):

Kummer, Olena. “Feature weighting approaches in sentiment analysis of short text.” 2012. Web. 26 May 2019.

Vancouver:

Kummer O. Feature weighting approaches in sentiment analysis of short text. [Internet] [Thesis]. Université de Neuchâtel; 2012. [cited 2019 May 26]. Available from: http://doc.rero.ch/record/30954.

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

Council of Science Editors:

Kummer O. Feature weighting approaches in sentiment analysis of short text. [Thesis]. Université de Neuchâtel; 2012. Available from: http://doc.rero.ch/record/30954

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


University of Technology, Sydney

2. Long, G. Instance-based and feature-based classification enhancement for short & sparse texts.

Degree: 2014, University of Technology, Sydney

 Short, sparse texts are becoming increasingly prevalent as a result of the growing popularity of social networking web sites, such as micro-blogs, Twitter and Flickr,… (more)

Subjects/Keywords: Short text.; Classification.; Text messages.; Text processing.

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

APA (6th Edition):

Long, G. (2014). Instance-based and feature-based classification enhancement for short & sparse texts. (Thesis). University of Technology, Sydney. Retrieved from http://hdl.handle.net/10453/29252

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):

Long, G. “Instance-based and feature-based classification enhancement for short & sparse texts.” 2014. Thesis, University of Technology, Sydney. Accessed May 26, 2019. http://hdl.handle.net/10453/29252.

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

MLA Handbook (7th Edition):

Long, G. “Instance-based and feature-based classification enhancement for short & sparse texts.” 2014. Web. 26 May 2019.

Vancouver:

Long G. Instance-based and feature-based classification enhancement for short & sparse texts. [Internet] [Thesis]. University of Technology, Sydney; 2014. [cited 2019 May 26]. Available from: http://hdl.handle.net/10453/29252.

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

Council of Science Editors:

Long G. Instance-based and feature-based classification enhancement for short & sparse texts. [Thesis]. University of Technology, Sydney; 2014. Available from: http://hdl.handle.net/10453/29252

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


Penn State University

3. Eden, Jake. Location Extraction from Text Features in Practical Environments.

Degree: 2018, Penn State University

 This thesis explores the potential of harnessing text extraction within a constrained environment aimed at guiding and augmenting a visually impaired end-users shopping experience. Most… (more)

Subjects/Keywords: Text; text extraction; localization; classification; text features

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APA (6th Edition):

Eden, J. (2018). Location Extraction from Text Features in Practical Environments. (Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/15168jte5085

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):

Eden, Jake. “Location Extraction from Text Features in Practical Environments.” 2018. Thesis, Penn State University. Accessed May 26, 2019. https://etda.libraries.psu.edu/catalog/15168jte5085.

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

MLA Handbook (7th Edition):

Eden, Jake. “Location Extraction from Text Features in Practical Environments.” 2018. Web. 26 May 2019.

Vancouver:

Eden J. Location Extraction from Text Features in Practical Environments. [Internet] [Thesis]. Penn State University; 2018. [cited 2019 May 26]. Available from: https://etda.libraries.psu.edu/catalog/15168jte5085.

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

Council of Science Editors:

Eden J. Location Extraction from Text Features in Practical Environments. [Thesis]. Penn State University; 2018. Available from: https://etda.libraries.psu.edu/catalog/15168jte5085

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


Dalhousie University

4. Kumar, Mathavan. AUTOMATIC IDENTIFICATION OF USER INTEREST FROM SOCIAL MEDIA.

Degree: Master of Computer Science, Faculty of Computer Science, 2015, Dalhousie University

 Automatic identification of user interest from social media has gained much attention in the recent years. In Twitter, users could post tweets about a wide… (more)

Subjects/Keywords: Text classification; Social media; Twitter

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

APA (6th Edition):

Kumar, M. (2015). AUTOMATIC IDENTIFICATION OF USER INTEREST FROM SOCIAL MEDIA. (Masters Thesis). Dalhousie University. Retrieved from http://hdl.handle.net/10222/56292

Chicago Manual of Style (16th Edition):

Kumar, Mathavan. “AUTOMATIC IDENTIFICATION OF USER INTEREST FROM SOCIAL MEDIA.” 2015. Masters Thesis, Dalhousie University. Accessed May 26, 2019. http://hdl.handle.net/10222/56292.

MLA Handbook (7th Edition):

Kumar, Mathavan. “AUTOMATIC IDENTIFICATION OF USER INTEREST FROM SOCIAL MEDIA.” 2015. Web. 26 May 2019.

Vancouver:

Kumar M. AUTOMATIC IDENTIFICATION OF USER INTEREST FROM SOCIAL MEDIA. [Internet] [Masters thesis]. Dalhousie University; 2015. [cited 2019 May 26]. Available from: http://hdl.handle.net/10222/56292.

Council of Science Editors:

Kumar M. AUTOMATIC IDENTIFICATION OF USER INTEREST FROM SOCIAL MEDIA. [Masters Thesis]. Dalhousie University; 2015. Available from: http://hdl.handle.net/10222/56292


NSYSU

5. Chen, Yu-ling. The Research on the Detection of Noteworthy Symptom Descriptions.

Degree: Master, Information Management, 2016, NSYSU

 The advance of cell phone and technology create a convenient way to connect doctors and patients. Doctors can keep track of patientsâ situations by their… (more)

Subjects/Keywords: Text mining; CKIP; LIBSVM; Classification

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APA (6th Edition):

Chen, Y. (2016). The Research on the Detection of Noteworthy Symptom Descriptions. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0306116-140216

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):

Chen, Yu-ling. “The Research on the Detection of Noteworthy Symptom Descriptions.” 2016. Thesis, NSYSU. Accessed May 26, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0306116-140216.

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

MLA Handbook (7th Edition):

Chen, Yu-ling. “The Research on the Detection of Noteworthy Symptom Descriptions.” 2016. Web. 26 May 2019.

Vancouver:

Chen Y. The Research on the Detection of Noteworthy Symptom Descriptions. [Internet] [Thesis]. NSYSU; 2016. [cited 2019 May 26]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0306116-140216.

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

Council of Science Editors:

Chen Y. The Research on the Detection of Noteworthy Symptom Descriptions. [Thesis]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0306116-140216

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


The Ohio State University

6. Sriram, Bharath. Short Text Classification in Twitter to Improve Information Filtering.

Degree: MS, Computer Science and Engineering, 2010, The Ohio State University

  In micro-blogging services such as Twitter, the users may get overwhelmed by the raw data. One solution to this problem is the classification of… (more)

Subjects/Keywords: Computer Science; Text Classification; Twitter; Short Text; Information filtering

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APA (6th Edition):

Sriram, B. (2010). Short Text Classification in Twitter to Improve Information Filtering. (Masters Thesis). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1275406094

Chicago Manual of Style (16th Edition):

Sriram, Bharath. “Short Text Classification in Twitter to Improve Information Filtering.” 2010. Masters Thesis, The Ohio State University. Accessed May 26, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275406094.

MLA Handbook (7th Edition):

Sriram, Bharath. “Short Text Classification in Twitter to Improve Information Filtering.” 2010. Web. 26 May 2019.

Vancouver:

Sriram B. Short Text Classification in Twitter to Improve Information Filtering. [Internet] [Masters thesis]. The Ohio State University; 2010. [cited 2019 May 26]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1275406094.

Council of Science Editors:

Sriram B. Short Text Classification in Twitter to Improve Information Filtering. [Masters Thesis]. The Ohio State University; 2010. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1275406094


University of Cincinnati

7. Aryasomayajula, Naga Srinivasa Baradwaj. Machine Learning Models for Categorizing Privacy Policy Text.

Degree: MS, Engineering and Applied Science: Computer Science, 2018, University of Cincinnati

 A privacy policy is a legal document that discloses the privacy practices of a company to its customers and contains information on how the company… (more)

Subjects/Keywords: Computer Science; machine learning; privacy policy text; classification; text spans

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APA (6th Edition):

Aryasomayajula, N. S. B. (2018). Machine Learning Models for Categorizing Privacy Policy Text. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535633397362514

Chicago Manual of Style (16th Edition):

Aryasomayajula, Naga Srinivasa Baradwaj. “Machine Learning Models for Categorizing Privacy Policy Text.” 2018. Masters Thesis, University of Cincinnati. Accessed May 26, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535633397362514.

MLA Handbook (7th Edition):

Aryasomayajula, Naga Srinivasa Baradwaj. “Machine Learning Models for Categorizing Privacy Policy Text.” 2018. Web. 26 May 2019.

Vancouver:

Aryasomayajula NSB. Machine Learning Models for Categorizing Privacy Policy Text. [Internet] [Masters thesis]. University of Cincinnati; 2018. [cited 2019 May 26]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535633397362514.

Council of Science Editors:

Aryasomayajula NSB. Machine Learning Models for Categorizing Privacy Policy Text. [Masters Thesis]. University of Cincinnati; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535633397362514

8. Bouillot, Flavien. Classification de textes : de nouvelles pondérations adaptées aux petits volumes : Text Classification : new weights suitable for small dataset.

Degree: Docteur es, Informatique, 2015, Montpellier

Au quotidien, le réflexe de classifier est omniprésent et inconscient. Par exemple dans le processus de prise de décision où face à un élément (un… (more)

Subjects/Keywords: Classification textuelle; Petits volume de données; Méta-Classification; Text classification; Few data classification; Meta-Classification

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

APA (6th Edition):

Bouillot, F. (2015). Classification de textes : de nouvelles pondérations adaptées aux petits volumes : Text Classification : new weights suitable for small dataset. (Doctoral Dissertation). Montpellier. Retrieved from http://www.theses.fr/2015MONTS167

Chicago Manual of Style (16th Edition):

Bouillot, Flavien. “Classification de textes : de nouvelles pondérations adaptées aux petits volumes : Text Classification : new weights suitable for small dataset.” 2015. Doctoral Dissertation, Montpellier. Accessed May 26, 2019. http://www.theses.fr/2015MONTS167.

MLA Handbook (7th Edition):

Bouillot, Flavien. “Classification de textes : de nouvelles pondérations adaptées aux petits volumes : Text Classification : new weights suitable for small dataset.” 2015. Web. 26 May 2019.

Vancouver:

Bouillot F. Classification de textes : de nouvelles pondérations adaptées aux petits volumes : Text Classification : new weights suitable for small dataset. [Internet] [Doctoral dissertation]. Montpellier; 2015. [cited 2019 May 26]. Available from: http://www.theses.fr/2015MONTS167.

Council of Science Editors:

Bouillot F. Classification de textes : de nouvelles pondérations adaptées aux petits volumes : Text Classification : new weights suitable for small dataset. [Doctoral Dissertation]. Montpellier; 2015. Available from: http://www.theses.fr/2015MONTS167


Georgia Tech

9. Musaev, Aibek. Landslide information service based on composition of physical and social information services.

Degree: PhD, Computer Science, 2016, Georgia Tech

 Modern world data come from an increasing number of sources, including data from physical sources like satellites and seismic sensors as well as social networks… (more)

Subjects/Keywords: Social networks; Event detection; Text classification

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APA (6th Edition):

Musaev, A. (2016). Landslide information service based on composition of physical and social information services. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55572

Chicago Manual of Style (16th Edition):

Musaev, Aibek. “Landslide information service based on composition of physical and social information services.” 2016. Doctoral Dissertation, Georgia Tech. Accessed May 26, 2019. http://hdl.handle.net/1853/55572.

MLA Handbook (7th Edition):

Musaev, Aibek. “Landslide information service based on composition of physical and social information services.” 2016. Web. 26 May 2019.

Vancouver:

Musaev A. Landslide information service based on composition of physical and social information services. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 May 26]. Available from: http://hdl.handle.net/1853/55572.

Council of Science Editors:

Musaev A. Landslide information service based on composition of physical and social information services. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55572


University of Southern California

10. Youn, Seongwook. Spam e-mail filtering via global and user-level dynamic ontologies.

Degree: PhD, Computer Science, 2009, University of Southern California

 E-mail is clearly a very important communication method between people on the Internet. However, the constant increase of e-mail misuse/abuse has resulted in a huge… (more)

Subjects/Keywords: e-mail; ontology; spam filtering; text classification

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APA (6th Edition):

Youn, S. (2009). Spam e-mail filtering via global and user-level dynamic ontologies. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/278798/rec/5971

Chicago Manual of Style (16th Edition):

Youn, Seongwook. “Spam e-mail filtering via global and user-level dynamic ontologies.” 2009. Doctoral Dissertation, University of Southern California. Accessed May 26, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/278798/rec/5971.

MLA Handbook (7th Edition):

Youn, Seongwook. “Spam e-mail filtering via global and user-level dynamic ontologies.” 2009. Web. 26 May 2019.

Vancouver:

Youn S. Spam e-mail filtering via global and user-level dynamic ontologies. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 May 26]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/278798/rec/5971.

Council of Science Editors:

Youn S. Spam e-mail filtering via global and user-level dynamic ontologies. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/278798/rec/5971

11. Cui, Man. Paper Categorization Using Naive Bayes.

Degree: Dept. of Computer Science, 2013, University of Victoria

 Literature survey is a time-consuming process as researchers spend a lot of time in searching the papers of interest. While search engines can be useful… (more)

Subjects/Keywords: Text classification

…and search for the documents of interest. The text classification algorithm used by Iris is… …called Naive Bayes, a popular algorithm in the text classification literature. There are two… …using Iris. Chapter 7 summaries the related work found in the text classification literature… …x28;B2 )...P (Bn ) (2.3) 5 2.1 Naive Bayes Text Classification… …The problem of text classification can be described as: given a document containing a list… 

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APA (6th Edition):

Cui, M. (2013). Paper Categorization Using Naive Bayes. (Masters Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/4564

Chicago Manual of Style (16th Edition):

Cui, Man. “Paper Categorization Using Naive Bayes.” 2013. Masters Thesis, University of Victoria. Accessed May 26, 2019. http://hdl.handle.net/1828/4564.

MLA Handbook (7th Edition):

Cui, Man. “Paper Categorization Using Naive Bayes.” 2013. Web. 26 May 2019.

Vancouver:

Cui M. Paper Categorization Using Naive Bayes. [Internet] [Masters thesis]. University of Victoria; 2013. [cited 2019 May 26]. Available from: http://hdl.handle.net/1828/4564.

Council of Science Editors:

Cui M. Paper Categorization Using Naive Bayes. [Masters Thesis]. University of Victoria; 2013. Available from: http://hdl.handle.net/1828/4564


Virginia Tech

12. Chakravarty, Saurabh. A Large Collection Learning Optimizer Framework.

Degree: MS, Computer Science, 2017, Virginia Tech

 Content is generated on the web at an increasing rate. The type of content varies from text on a traditional webpage to text on social… (more)

Subjects/Keywords: Digital Libraries; Text Classification; Tweets; Apache Spark

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APA (6th Edition):

Chakravarty, S. (2017). A Large Collection Learning Optimizer Framework. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78302

Chicago Manual of Style (16th Edition):

Chakravarty, Saurabh. “A Large Collection Learning Optimizer Framework.” 2017. Masters Thesis, Virginia Tech. Accessed May 26, 2019. http://hdl.handle.net/10919/78302.

MLA Handbook (7th Edition):

Chakravarty, Saurabh. “A Large Collection Learning Optimizer Framework.” 2017. Web. 26 May 2019.

Vancouver:

Chakravarty S. A Large Collection Learning Optimizer Framework. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2019 May 26]. Available from: http://hdl.handle.net/10919/78302.

Council of Science Editors:

Chakravarty S. A Large Collection Learning Optimizer Framework. [Masters Thesis]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/78302


University of Melbourne

13. LUI, MARCO. Generalized language identification.

Degree: 2014, University of Melbourne

 Language identification is the task of determining the natural language that a document or part thereof is written in. The central theme of this thesis… (more)

Subjects/Keywords: language identification; machine learning; text classification

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APA (6th Edition):

LUI, M. (2014). Generalized language identification. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/52819

Chicago Manual of Style (16th Edition):

LUI, MARCO. “Generalized language identification.” 2014. Doctoral Dissertation, University of Melbourne. Accessed May 26, 2019. http://hdl.handle.net/11343/52819.

MLA Handbook (7th Edition):

LUI, MARCO. “Generalized language identification.” 2014. Web. 26 May 2019.

Vancouver:

LUI M. Generalized language identification. [Internet] [Doctoral dissertation]. University of Melbourne; 2014. [cited 2019 May 26]. Available from: http://hdl.handle.net/11343/52819.

Council of Science Editors:

LUI M. Generalized language identification. [Doctoral Dissertation]. University of Melbourne; 2014. Available from: http://hdl.handle.net/11343/52819


University of Limerick

14. Alahmadi, Alaa. Automatic text classification using bag of words and bag of concepts based representations.

Degree: 2016, University of Limerick

 Automatic Text Classification (ATC) is one of the most important tasks in data mining for organizing information and knowledge discovery. The goal of ATC is… (more)

Subjects/Keywords: automatic text classification; ATC; knowledge discovery

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APA (6th Edition):

Alahmadi, A. (2016). Automatic text classification using bag of words and bag of concepts based representations. (Thesis). University of Limerick. Retrieved from http://hdl.handle.net/10344/5224

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):

Alahmadi, Alaa. “Automatic text classification using bag of words and bag of concepts based representations.” 2016. Thesis, University of Limerick. Accessed May 26, 2019. http://hdl.handle.net/10344/5224.

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

MLA Handbook (7th Edition):

Alahmadi, Alaa. “Automatic text classification using bag of words and bag of concepts based representations.” 2016. Web. 26 May 2019.

Vancouver:

Alahmadi A. Automatic text classification using bag of words and bag of concepts based representations. [Internet] [Thesis]. University of Limerick; 2016. [cited 2019 May 26]. Available from: http://hdl.handle.net/10344/5224.

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

Council of Science Editors:

Alahmadi A. Automatic text classification using bag of words and bag of concepts based representations. [Thesis]. University of Limerick; 2016. Available from: http://hdl.handle.net/10344/5224

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


Kansas State University

15. Bikki, Poojitha. Machine learning for text categorization: experiments using clustering and classification.

Degree: MS, Department of Computer Science, 2018, Kansas State University

 This work describes a comparative study of empirical methods for categorization of new articles within text corpora: unsupervised learning for an unlabeled corpus of text(more)

Subjects/Keywords: Text categorization; Machine learning; Classification; Clustering

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APA (6th Edition):

Bikki, P. (2018). Machine learning for text categorization: experiments using clustering and classification. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/38889

Chicago Manual of Style (16th Edition):

Bikki, Poojitha. “Machine learning for text categorization: experiments using clustering and classification.” 2018. Masters Thesis, Kansas State University. Accessed May 26, 2019. http://hdl.handle.net/2097/38889.

MLA Handbook (7th Edition):

Bikki, Poojitha. “Machine learning for text categorization: experiments using clustering and classification.” 2018. Web. 26 May 2019.

Vancouver:

Bikki P. Machine learning for text categorization: experiments using clustering and classification. [Internet] [Masters thesis]. Kansas State University; 2018. [cited 2019 May 26]. Available from: http://hdl.handle.net/2097/38889.

Council of Science Editors:

Bikki P. Machine learning for text categorization: experiments using clustering and classification. [Masters Thesis]. Kansas State University; 2018. Available from: http://hdl.handle.net/2097/38889


Arizona State University

16. Swadia, Japa Nimish. A Study of Text Mining Framework for Automated Classification of Software Requirements in Enterprise Systems.

Degree: Engineering, 2016, Arizona State University

Text Classification is a rapidly evolving area of Data Mining while Requirements Engineering is a less-explored area of Software Engineering which deals the process of… (more)

Subjects/Keywords: Computer science; Engineering; data analytics; R; requirements classification; text classification; text mining

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APA (6th Edition):

Swadia, J. N. (2016). A Study of Text Mining Framework for Automated Classification of Software Requirements in Enterprise Systems. (Masters Thesis). Arizona State University. Retrieved from http://repository.asu.edu/items/38809

Chicago Manual of Style (16th Edition):

Swadia, Japa Nimish. “A Study of Text Mining Framework for Automated Classification of Software Requirements in Enterprise Systems.” 2016. Masters Thesis, Arizona State University. Accessed May 26, 2019. http://repository.asu.edu/items/38809.

MLA Handbook (7th Edition):

Swadia, Japa Nimish. “A Study of Text Mining Framework for Automated Classification of Software Requirements in Enterprise Systems.” 2016. Web. 26 May 2019.

Vancouver:

Swadia JN. A Study of Text Mining Framework for Automated Classification of Software Requirements in Enterprise Systems. [Internet] [Masters thesis]. Arizona State University; 2016. [cited 2019 May 26]. Available from: http://repository.asu.edu/items/38809.

Council of Science Editors:

Swadia JN. A Study of Text Mining Framework for Automated Classification of Software Requirements in Enterprise Systems. [Masters Thesis]. Arizona State University; 2016. Available from: http://repository.asu.edu/items/38809


Penn State University

17. Song, Yang. Machine Learning for Text Mining: Classification, Retrieval and Recommendation.

Degree: PhD, Computer Science and Engineering, 2008, Penn State University

 We all witnessed the information explosion of the World Wide Web which has brought us with continuously rapid growth of information and data. However, as… (more)

Subjects/Keywords: classification; machine learning; text classification; information retrieval; clustering; recommendation

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

APA (6th Edition):

Song, Y. (2008). Machine Learning for Text Mining: Classification, Retrieval and Recommendation. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9176

Chicago Manual of Style (16th Edition):

Song, Yang. “Machine Learning for Text Mining: Classification, Retrieval and Recommendation.” 2008. Doctoral Dissertation, Penn State University. Accessed May 26, 2019. https://etda.libraries.psu.edu/catalog/9176.

MLA Handbook (7th Edition):

Song, Yang. “Machine Learning for Text Mining: Classification, Retrieval and Recommendation.” 2008. Web. 26 May 2019.

Vancouver:

Song Y. Machine Learning for Text Mining: Classification, Retrieval and Recommendation. [Internet] [Doctoral dissertation]. Penn State University; 2008. [cited 2019 May 26]. Available from: https://etda.libraries.psu.edu/catalog/9176.

Council of Science Editors:

Song Y. Machine Learning for Text Mining: Classification, Retrieval and Recommendation. [Doctoral Dissertation]. Penn State University; 2008. Available from: https://etda.libraries.psu.edu/catalog/9176


George Mason University

18. Charuvaka, Anveshi. Regularized Learning in Multiple Tasks with Relationship .

Degree: 2015, George Mason University

 Supervised classification is a sub-task of machine learning where the goal is to infer a classification function using labeled data. A vast amount of research… (more)

Subjects/Keywords: Computer science; Classification; Hierarchical Classification; Machine Learning; Text Mining

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APA (6th Edition):

Charuvaka, A. (2015). Regularized Learning in Multiple Tasks with Relationship . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/10193

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):

Charuvaka, Anveshi. “Regularized Learning in Multiple Tasks with Relationship .” 2015. Thesis, George Mason University. Accessed May 26, 2019. http://hdl.handle.net/1920/10193.

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

MLA Handbook (7th Edition):

Charuvaka, Anveshi. “Regularized Learning in Multiple Tasks with Relationship .” 2015. Web. 26 May 2019.

Vancouver:

Charuvaka A. Regularized Learning in Multiple Tasks with Relationship . [Internet] [Thesis]. George Mason University; 2015. [cited 2019 May 26]. Available from: http://hdl.handle.net/1920/10193.

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

Council of Science Editors:

Charuvaka A. Regularized Learning in Multiple Tasks with Relationship . [Thesis]. George Mason University; 2015. Available from: http://hdl.handle.net/1920/10193

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


Brno University of Technology

19. Jeleček, Jiří. Automatické zjišťování významu textu .

Degree: 2015, Brno University of Technology

 V rámci této práce byl navržen a implementován systém využívající technik dolování znalostí z textu za účelem rozpoznávání emocí v česky, anglicky a německy psaných… (more)

Subjects/Keywords: klasifikace; dolování znalostí; rozpoznávání emoce; SVM; negativní text; pozitivní text; strojové učení; classification; text mining; emotion detection; SVM; negative text; positive text; machine learning

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

APA (6th Edition):

Jeleček, J. (2015). Automatické zjišťování významu textu . (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/41354

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):

Jeleček, Jiří. “Automatické zjišťování významu textu .” 2015. Thesis, Brno University of Technology. Accessed May 26, 2019. http://hdl.handle.net/11012/41354.

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

MLA Handbook (7th Edition):

Jeleček, Jiří. “Automatické zjišťování významu textu .” 2015. Web. 26 May 2019.

Vancouver:

Jeleček J. Automatické zjišťování významu textu . [Internet] [Thesis]. Brno University of Technology; 2015. [cited 2019 May 26]. Available from: http://hdl.handle.net/11012/41354.

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

Council of Science Editors:

Jeleček J. Automatické zjišťování významu textu . [Thesis]. Brno University of Technology; 2015. Available from: http://hdl.handle.net/11012/41354

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


University of Bradford

20. AlKhateeb, Jawad Hasan Yasin. Word based off-line handwritten Arabic classification and recognition : design of automatic recognition system for large vocabulary offline handwritten Arabic words using machine learning approaches.

Degree: PhD, 2010, University of Bradford

 The design of a machine which reads unconstrained words still remains an unsolved problem. For example, automatic interpretation of handwritten documents by a computer is… (more)

Subjects/Keywords: 006.3; Arabic text; Pattern recognition; Word recognition; Handwritten documents; Text classification and recognition; Feature extraction

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

APA (6th Edition):

AlKhateeb, J. H. Y. (2010). Word based off-line handwritten Arabic classification and recognition : design of automatic recognition system for large vocabulary offline handwritten Arabic words using machine learning approaches. (Doctoral Dissertation). University of Bradford. Retrieved from http://hdl.handle.net/10454/4440

Chicago Manual of Style (16th Edition):

AlKhateeb, Jawad Hasan Yasin. “Word based off-line handwritten Arabic classification and recognition : design of automatic recognition system for large vocabulary offline handwritten Arabic words using machine learning approaches.” 2010. Doctoral Dissertation, University of Bradford. Accessed May 26, 2019. http://hdl.handle.net/10454/4440.

MLA Handbook (7th Edition):

AlKhateeb, Jawad Hasan Yasin. “Word based off-line handwritten Arabic classification and recognition : design of automatic recognition system for large vocabulary offline handwritten Arabic words using machine learning approaches.” 2010. Web. 26 May 2019.

Vancouver:

AlKhateeb JHY. Word based off-line handwritten Arabic classification and recognition : design of automatic recognition system for large vocabulary offline handwritten Arabic words using machine learning approaches. [Internet] [Doctoral dissertation]. University of Bradford; 2010. [cited 2019 May 26]. Available from: http://hdl.handle.net/10454/4440.

Council of Science Editors:

AlKhateeb JHY. Word based off-line handwritten Arabic classification and recognition : design of automatic recognition system for large vocabulary offline handwritten Arabic words using machine learning approaches. [Doctoral Dissertation]. University of Bradford; 2010. Available from: http://hdl.handle.net/10454/4440


Case Western Reserve University

21. Walker, Briana Shanise. Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care.

Degree: MSs, Systems Biology and Bioinformatics, 2017, Case Western Reserve University

 The research efforts undertaken in this thesis project represent an extension of the previously published works of Alfes & Reimer (2016). This pilot study evaluates… (more)

Subjects/Keywords: Bioinformatics; Nursing; critical care; transfer of care; text classification; document classification; supervised classification; dialogue

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

APA (6th Edition):

Walker, B. S. (2017). Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care. (Masters Thesis). Case Western Reserve University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537

Chicago Manual of Style (16th Edition):

Walker, Briana Shanise. “Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care.” 2017. Masters Thesis, Case Western Reserve University. Accessed May 26, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537.

MLA Handbook (7th Edition):

Walker, Briana Shanise. “Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care.” 2017. Web. 26 May 2019.

Vancouver:

Walker BS. Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care. [Internet] [Masters thesis]. Case Western Reserve University; 2017. [cited 2019 May 26]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537.

Council of Science Editors:

Walker BS. Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care. [Masters Thesis]. Case Western Reserve University; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537


Purdue University

22. Huang, Hsin-Ying. Examination and utilization of rare features in text classification of injury narratives.

Degree: PhD, Industrial Engineering, 2016, Purdue University

  Thanks to the advances in computing and information technology, analyzing injury surveillance data with statistical machine learning methods has grown in popularity, complexity, and… (more)

Subjects/Keywords: Applied sciences; Injury surveillance; Machine learning; Narrative text; Rare words; Text classification; Text preprocessing; Industrial Engineering

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

APA (6th Edition):

Huang, H. (2016). Examination and utilization of rare features in text classification of injury narratives. (Doctoral Dissertation). Purdue University. Retrieved from http://docs.lib.purdue.edu/open_access_dissertations/936

Chicago Manual of Style (16th Edition):

Huang, Hsin-Ying. “Examination and utilization of rare features in text classification of injury narratives.” 2016. Doctoral Dissertation, Purdue University. Accessed May 26, 2019. http://docs.lib.purdue.edu/open_access_dissertations/936.

MLA Handbook (7th Edition):

Huang, Hsin-Ying. “Examination and utilization of rare features in text classification of injury narratives.” 2016. Web. 26 May 2019.

Vancouver:

Huang H. Examination and utilization of rare features in text classification of injury narratives. [Internet] [Doctoral dissertation]. Purdue University; 2016. [cited 2019 May 26]. Available from: http://docs.lib.purdue.edu/open_access_dissertations/936.

Council of Science Editors:

Huang H. Examination and utilization of rare features in text classification of injury narratives. [Doctoral Dissertation]. Purdue University; 2016. Available from: http://docs.lib.purdue.edu/open_access_dissertations/936


University of Cambridge

23. Xia, Menglin. Text readability and summarisation for non-native reading comprehension.

Degree: PhD, 2019, University of Cambridge

 This thesis focuses on two important aspects of non-native reading comprehension: text readability assessment, which estimates the reading difficulty of a given text for L2… (more)

Subjects/Keywords: Natural Language Processing; Text Readability; Summarisation Evaluation; L2 Reading; Text Similarity; Text Classification; Automated Summarisation Assessment

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

APA (6th Edition):

Xia, M. (2019). Text readability and summarisation for non-native reading comprehension. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/288740 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767785

Chicago Manual of Style (16th Edition):

Xia, Menglin. “Text readability and summarisation for non-native reading comprehension.” 2019. Doctoral Dissertation, University of Cambridge. Accessed May 26, 2019. https://www.repository.cam.ac.uk/handle/1810/288740 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767785.

MLA Handbook (7th Edition):

Xia, Menglin. “Text readability and summarisation for non-native reading comprehension.” 2019. Web. 26 May 2019.

Vancouver:

Xia M. Text readability and summarisation for non-native reading comprehension. [Internet] [Doctoral dissertation]. University of Cambridge; 2019. [cited 2019 May 26]. Available from: https://www.repository.cam.ac.uk/handle/1810/288740 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767785.

Council of Science Editors:

Xia M. Text readability and summarisation for non-native reading comprehension. [Doctoral Dissertation]. University of Cambridge; 2019. Available from: https://www.repository.cam.ac.uk/handle/1810/288740 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767785


Queen Mary, University of London

24. Martinez-Alvarez, Miguel. Knowledge-enhanced text classification : descriptive modelling and new approaches.

Degree: PhD, 2014, Queen Mary, University of London

 The knowledge available to be exploited by text classification and information retrieval systems has significantly changed, both in nature and quantity, in the last years.… (more)

Subjects/Keywords: Electronic Engineering and Computer Science; Information retrieval; text classification; Semi-Automatic Text Classification; Document Performance Prediction

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

APA (6th Edition):

Martinez-Alvarez, M. (2014). Knowledge-enhanced text classification : descriptive modelling and new approaches. (Doctoral Dissertation). Queen Mary, University of London. Retrieved from http://qmro.qmul.ac.uk/xmlui/handle/123456789/27205 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.765757

Chicago Manual of Style (16th Edition):

Martinez-Alvarez, Miguel. “Knowledge-enhanced text classification : descriptive modelling and new approaches.” 2014. Doctoral Dissertation, Queen Mary, University of London. Accessed May 26, 2019. http://qmro.qmul.ac.uk/xmlui/handle/123456789/27205 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.765757.

MLA Handbook (7th Edition):

Martinez-Alvarez, Miguel. “Knowledge-enhanced text classification : descriptive modelling and new approaches.” 2014. Web. 26 May 2019.

Vancouver:

Martinez-Alvarez M. Knowledge-enhanced text classification : descriptive modelling and new approaches. [Internet] [Doctoral dissertation]. Queen Mary, University of London; 2014. [cited 2019 May 26]. Available from: http://qmro.qmul.ac.uk/xmlui/handle/123456789/27205 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.765757.

Council of Science Editors:

Martinez-Alvarez M. Knowledge-enhanced text classification : descriptive modelling and new approaches. [Doctoral Dissertation]. Queen Mary, University of London; 2014. Available from: http://qmro.qmul.ac.uk/xmlui/handle/123456789/27205 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.765757

25. Bouaziz, Ameni. Méthodes d’apprentissage interactif pour la classification des messages courts : Interactive learning methods for short text classification.

Degree: Docteur es, Informatique, 2017, Côte d'Azur

La classification automatique des messages courts est de plus en plus employée de nos jours dans diverses applications telles que l'analyse des sentiments ou la… (more)

Subjects/Keywords: Classification des messages courts; Sémantique; Forêts aléatoires; Interactivité; Short text classification; Semantics; Random Forest; Interactivity

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APA (6th Edition):

Bouaziz, A. (2017). Méthodes d’apprentissage interactif pour la classification des messages courts : Interactive learning methods for short text classification. (Doctoral Dissertation). Côte d'Azur. Retrieved from http://www.theses.fr/2017AZUR4039

Chicago Manual of Style (16th Edition):

Bouaziz, Ameni. “Méthodes d’apprentissage interactif pour la classification des messages courts : Interactive learning methods for short text classification.” 2017. Doctoral Dissertation, Côte d'Azur. Accessed May 26, 2019. http://www.theses.fr/2017AZUR4039.

MLA Handbook (7th Edition):

Bouaziz, Ameni. “Méthodes d’apprentissage interactif pour la classification des messages courts : Interactive learning methods for short text classification.” 2017. Web. 26 May 2019.

Vancouver:

Bouaziz A. Méthodes d’apprentissage interactif pour la classification des messages courts : Interactive learning methods for short text classification. [Internet] [Doctoral dissertation]. Côte d'Azur; 2017. [cited 2019 May 26]. Available from: http://www.theses.fr/2017AZUR4039.

Council of Science Editors:

Bouaziz A. Méthodes d’apprentissage interactif pour la classification des messages courts : Interactive learning methods for short text classification. [Doctoral Dissertation]. Côte d'Azur; 2017. Available from: http://www.theses.fr/2017AZUR4039


NSYSU

26. Chen, Po-ling. Recommending Travel Threads Based on Information Need Model.

Degree: Master, Information Management, 2012, NSYSU

 Recommendation techniques are developed to discover userâs real information need among large amounts of information. Recommendation systems help users filter out information and attempt to… (more)

Subjects/Keywords: Text classification; Travel threads recommendation; Travel threads classification; Question recommendation; Information need model

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APA (6th Edition):

Chen, P. (2012). Recommending Travel Threads Based on Information Need Model. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729112-222447

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):

Chen, Po-ling. “Recommending Travel Threads Based on Information Need Model.” 2012. Thesis, NSYSU. Accessed May 26, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729112-222447.

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

MLA Handbook (7th Edition):

Chen, Po-ling. “Recommending Travel Threads Based on Information Need Model.” 2012. Web. 26 May 2019.

Vancouver:

Chen P. Recommending Travel Threads Based on Information Need Model. [Internet] [Thesis]. NSYSU; 2012. [cited 2019 May 26]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729112-222447.

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

Council of Science Editors:

Chen P. Recommending Travel Threads Based on Information Need Model. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729112-222447

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


Kennesaw State University

27. Kranzlein, Michael. A Multiple Classifier System for Predicting Best-Selling Amazon Products.

Degree: MSCS, Computer Science, 2018, Kennesaw State University

  In this work, I examine a dataset of Amazon product metadata and propose a heterogeneous multiple classifier system for the task of identifying best-selling… (more)

Subjects/Keywords: data analysis; ecommerce; image classification; machine learning; text classification; Other Computer Sciences

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APA (6th Edition):

Kranzlein, M. (2018). A Multiple Classifier System for Predicting Best-Selling Amazon Products. (Thesis). Kennesaw State University. Retrieved from https://digitalcommons.kennesaw.edu/cs_etd/18

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):

Kranzlein, Michael. “A Multiple Classifier System for Predicting Best-Selling Amazon Products.” 2018. Thesis, Kennesaw State University. Accessed May 26, 2019. https://digitalcommons.kennesaw.edu/cs_etd/18.

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

MLA Handbook (7th Edition):

Kranzlein, Michael. “A Multiple Classifier System for Predicting Best-Selling Amazon Products.” 2018. Web. 26 May 2019.

Vancouver:

Kranzlein M. A Multiple Classifier System for Predicting Best-Selling Amazon Products. [Internet] [Thesis]. Kennesaw State University; 2018. [cited 2019 May 26]. Available from: https://digitalcommons.kennesaw.edu/cs_etd/18.

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

Council of Science Editors:

Kranzlein M. A Multiple Classifier System for Predicting Best-Selling Amazon Products. [Thesis]. Kennesaw State University; 2018. Available from: https://digitalcommons.kennesaw.edu/cs_etd/18

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


NSYSU

28. Chiang , Chia-Che. Use Text Mining Techniques to Identify Noteworthy Hotel Reviews from Travel Forums.

Degree: Master, Information Management, 2014, NSYSU

 The advance of user-generated content (UGC) inspires knowledge sharing among Internet users. A good example is the well-known travel site TripAdvisor.com, which enables users to… (more)

Subjects/Keywords: Latent Dirichlet allocation; Text classification; Word-sense disambiguation; SVM; WordNet

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APA (6th Edition):

Chiang , C. (2014). Use Text Mining Techniques to Identify Noteworthy Hotel Reviews from Travel Forums. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0819114-155606

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):

Chiang , Chia-Che. “Use Text Mining Techniques to Identify Noteworthy Hotel Reviews from Travel Forums.” 2014. Thesis, NSYSU. Accessed May 26, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0819114-155606.

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

MLA Handbook (7th Edition):

Chiang , Chia-Che. “Use Text Mining Techniques to Identify Noteworthy Hotel Reviews from Travel Forums.” 2014. Web. 26 May 2019.

Vancouver:

Chiang C. Use Text Mining Techniques to Identify Noteworthy Hotel Reviews from Travel Forums. [Internet] [Thesis]. NSYSU; 2014. [cited 2019 May 26]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0819114-155606.

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

Council of Science Editors:

Chiang C. Use Text Mining Techniques to Identify Noteworthy Hotel Reviews from Travel Forums. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0819114-155606

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


Queens University

29. Denroche, Robert. Automatic Identification of Protein Characterization Articles in support of Database Curation .

Degree: Computing, 2010, Queens University

 Experimentally determining the biological function of a protein is a process known as protein characterization. Establishing the role a specific protein plays is a vital… (more)

Subjects/Keywords: machine learning; database curation; bioinformatics; classification; biomedical text mining

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APA (6th Edition):

Denroche, R. (2010). Automatic Identification of Protein Characterization Articles in support of Database Curation . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/5415

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):

Denroche, Robert. “Automatic Identification of Protein Characterization Articles in support of Database Curation .” 2010. Thesis, Queens University. Accessed May 26, 2019. http://hdl.handle.net/1974/5415.

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

MLA Handbook (7th Edition):

Denroche, Robert. “Automatic Identification of Protein Characterization Articles in support of Database Curation .” 2010. Web. 26 May 2019.

Vancouver:

Denroche R. Automatic Identification of Protein Characterization Articles in support of Database Curation . [Internet] [Thesis]. Queens University; 2010. [cited 2019 May 26]. Available from: http://hdl.handle.net/1974/5415.

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

Council of Science Editors:

Denroche R. Automatic Identification of Protein Characterization Articles in support of Database Curation . [Thesis]. Queens University; 2010. Available from: http://hdl.handle.net/1974/5415

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

30. Sun, Ming. Data Fusion via Manifold Matching.

Degree: 2013, Johns Hopkins University

 Data fusion has been an interesting and challenging research topic, which receives intensive investigation in many areas. The theory and practice of data fusion -… (more)

Subjects/Keywords: manifold matching; cross-language text classification; graph vertex nomination; inferential variability

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APA (6th Edition):

Sun, M. (2013). Data Fusion via Manifold Matching. (Thesis). Johns Hopkins University. Retrieved from http://jhir.library.jhu.edu/handle/1774.2/37023

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):

Sun, Ming. “Data Fusion via Manifold Matching.” 2013. Thesis, Johns Hopkins University. Accessed May 26, 2019. http://jhir.library.jhu.edu/handle/1774.2/37023.

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

MLA Handbook (7th Edition):

Sun, Ming. “Data Fusion via Manifold Matching.” 2013. Web. 26 May 2019.

Vancouver:

Sun M. Data Fusion via Manifold Matching. [Internet] [Thesis]. Johns Hopkins University; 2013. [cited 2019 May 26]. Available from: http://jhir.library.jhu.edu/handle/1774.2/37023.

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

Council of Science Editors:

Sun M. Data Fusion via Manifold Matching. [Thesis]. Johns Hopkins University; 2013. Available from: http://jhir.library.jhu.edu/handle/1774.2/37023

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

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