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You searched for subject:(Recommender systems). Showing records 1 – 30 of 372 total matches.

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Texas State University – San Marcos

1. Channamsetty, Sushma. Recommender response to user profile diversity and popularity bias.

Degree: MS, Computer Science, 2016, Texas State University – San Marcos

Recommender systems are commonly evaluated to understand the effectiveness of their algorithms. Diversity and novelty of the recommender systems have been in consideration while evaluating… (more)

Subjects/Keywords: Recommender systems; Recommender; Recommender systems (Information filtering); Expert systems (Computer science)

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

APA (6th Edition):

Channamsetty, S. (2016). Recommender response to user profile diversity and popularity bias. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/6313

Chicago Manual of Style (16th Edition):

Channamsetty, Sushma. “Recommender response to user profile diversity and popularity bias.” 2016. Masters Thesis, Texas State University – San Marcos. Accessed April 25, 2019. https://digital.library.txstate.edu/handle/10877/6313.

MLA Handbook (7th Edition):

Channamsetty, Sushma. “Recommender response to user profile diversity and popularity bias.” 2016. Web. 25 Apr 2019.

Vancouver:

Channamsetty S. Recommender response to user profile diversity and popularity bias. [Internet] [Masters thesis]. Texas State University – San Marcos; 2016. [cited 2019 Apr 25]. Available from: https://digital.library.txstate.edu/handle/10877/6313.

Council of Science Editors:

Channamsetty S. Recommender response to user profile diversity and popularity bias. [Masters Thesis]. Texas State University – San Marcos; 2016. Available from: https://digital.library.txstate.edu/handle/10877/6313


University of Technology, Sydney

2. Hao, Peng. Cross-domain recommender system through tag-based models.

Degree: 2018, University of Technology, Sydney

 Nowadays, data pertaining to clients are generated at such a rapid rate it is completely beyond the processing ability of a human, which leads to… (more)

Subjects/Keywords: Collaborative filtering-based model recommender systems.; Cross-domain recommender systems.; Recommender systems.

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

APA (6th Edition):

Hao, P. (2018). Cross-domain recommender system through tag-based models. (Thesis). University of Technology, Sydney. Retrieved from http://hdl.handle.net/10453/125626

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):

Hao, Peng. “Cross-domain recommender system through tag-based models.” 2018. Thesis, University of Technology, Sydney. Accessed April 25, 2019. http://hdl.handle.net/10453/125626.

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

MLA Handbook (7th Edition):

Hao, Peng. “Cross-domain recommender system through tag-based models.” 2018. Web. 25 Apr 2019.

Vancouver:

Hao P. Cross-domain recommender system through tag-based models. [Internet] [Thesis]. University of Technology, Sydney; 2018. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/10453/125626.

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

Council of Science Editors:

Hao P. Cross-domain recommender system through tag-based models. [Thesis]. University of Technology, Sydney; 2018. Available from: http://hdl.handle.net/10453/125626

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


University of Alberta

3. Bakhshinategh, Behdad. Design of a Course Recommender System as an Application of Collecting Graduating Attributes.

Degree: MS, Department of Computing Science, 2016, University of Alberta

 In educational research, the term of Graduating Attributes has been used for the qualities, skills and understandings a university community agrees its students would develop.… (more)

Subjects/Keywords: Graduating Attributes; Recommender Systems

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

APA (6th Edition):

Bakhshinategh, B. (2016). Design of a Course Recommender System as an Application of Collecting Graduating Attributes. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/cnz805z87v

Chicago Manual of Style (16th Edition):

Bakhshinategh, Behdad. “Design of a Course Recommender System as an Application of Collecting Graduating Attributes.” 2016. Masters Thesis, University of Alberta. Accessed April 25, 2019. https://era.library.ualberta.ca/files/cnz805z87v.

MLA Handbook (7th Edition):

Bakhshinategh, Behdad. “Design of a Course Recommender System as an Application of Collecting Graduating Attributes.” 2016. Web. 25 Apr 2019.

Vancouver:

Bakhshinategh B. Design of a Course Recommender System as an Application of Collecting Graduating Attributes. [Internet] [Masters thesis]. University of Alberta; 2016. [cited 2019 Apr 25]. Available from: https://era.library.ualberta.ca/files/cnz805z87v.

Council of Science Editors:

Bakhshinategh B. Design of a Course Recommender System as an Application of Collecting Graduating Attributes. [Masters Thesis]. University of Alberta; 2016. Available from: https://era.library.ualberta.ca/files/cnz805z87v


Texas A&M University

4. Guo, Shiqiang. ResuMatcher: A Personalized Resume-Job Matching System.

Degree: 2015, Texas A&M University

 Today, online recruiting web sites such as Monster and Indeed.com have become one of the main channels for people to find jobs. These web platforms… (more)

Subjects/Keywords: Job Search; Recommender Systems; NLP

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

APA (6th Edition):

Guo, S. (2015). ResuMatcher: A Personalized Resume-Job Matching System. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/154963

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):

Guo, Shiqiang. “ResuMatcher: A Personalized Resume-Job Matching System.” 2015. Thesis, Texas A&M University. Accessed April 25, 2019. http://hdl.handle.net/1969.1/154963.

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

MLA Handbook (7th Edition):

Guo, Shiqiang. “ResuMatcher: A Personalized Resume-Job Matching System.” 2015. Web. 25 Apr 2019.

Vancouver:

Guo S. ResuMatcher: A Personalized Resume-Job Matching System. [Internet] [Thesis]. Texas A&M University; 2015. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/1969.1/154963.

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

Council of Science Editors:

Guo S. ResuMatcher: A Personalized Resume-Job Matching System. [Thesis]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/154963

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


University of Hong Kong

5. Lu, Ziyu. Location-aware recommendation problems.

Degree: PhD, 2016, University of Hong Kong

 Recommendation problems have been extensively studied in many areas, e.g. product recommendation in E-commerce sites and location recommendation in location-based social sites. With the development… (more)

Subjects/Keywords: Recommender systems (Information filtering)

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

APA (6th Edition):

Lu, Z. (2016). Location-aware recommendation problems. (Doctoral Dissertation). University of Hong Kong. Retrieved from http://hdl.handle.net/10722/235924

Chicago Manual of Style (16th Edition):

Lu, Ziyu. “Location-aware recommendation problems.” 2016. Doctoral Dissertation, University of Hong Kong. Accessed April 25, 2019. http://hdl.handle.net/10722/235924.

MLA Handbook (7th Edition):

Lu, Ziyu. “Location-aware recommendation problems.” 2016. Web. 25 Apr 2019.

Vancouver:

Lu Z. Location-aware recommendation problems. [Internet] [Doctoral dissertation]. University of Hong Kong; 2016. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/10722/235924.

Council of Science Editors:

Lu Z. Location-aware recommendation problems. [Doctoral Dissertation]. University of Hong Kong; 2016. Available from: http://hdl.handle.net/10722/235924


University of California – San Diego

6. Kannar, Kiran. Exploiting Geographical and Temporal Patterns for Personalized POI Recommendation.

Degree: Computer Science, 2018, University of California – San Diego

 Human behavior presents various temporal and geographical patterns that can be used to model user preferences and enhance prediction in the task of POI recommendation.… (more)

Subjects/Keywords: Artificial intelligence; recommender systems

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

APA (6th Edition):

Kannar, K. (2018). Exploiting Geographical and Temporal Patterns for Personalized POI Recommendation. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/5t29c8xq

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):

Kannar, Kiran. “Exploiting Geographical and Temporal Patterns for Personalized POI Recommendation.” 2018. Thesis, University of California – San Diego. Accessed April 25, 2019. http://www.escholarship.org/uc/item/5t29c8xq.

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

MLA Handbook (7th Edition):

Kannar, Kiran. “Exploiting Geographical and Temporal Patterns for Personalized POI Recommendation.” 2018. Web. 25 Apr 2019.

Vancouver:

Kannar K. Exploiting Geographical and Temporal Patterns for Personalized POI Recommendation. [Internet] [Thesis]. University of California – San Diego; 2018. [cited 2019 Apr 25]. Available from: http://www.escholarship.org/uc/item/5t29c8xq.

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

Council of Science Editors:

Kannar K. Exploiting Geographical and Temporal Patterns for Personalized POI Recommendation. [Thesis]. University of California – San Diego; 2018. Available from: http://www.escholarship.org/uc/item/5t29c8xq

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


University of Manchester

7. Alahmadi, Dimah Hussain N. RECOMMENDER SYSTEMS BASED ON ONLINE SOCIAL NETWORKS -AN IMPLICIT SOCIAL TRUST AND SENTIMENT ANALYSIS APPROACH.

Degree: 2017, University of Manchester

Recommender systems (RSs) provide personalised suggestions of information orproducts relevant to user’s needs. RSs are considered as powerful tools that help usersto find interesting items… (more)

Subjects/Keywords: Recommender systems; trust; sentiment analysis

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

APA (6th Edition):

Alahmadi, D. H. N. (2017). RECOMMENDER SYSTEMS BASED ON ONLINE SOCIAL NETWORKS -AN IMPLICIT SOCIAL TRUST AND SENTIMENT ANALYSIS APPROACH. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:306813

Chicago Manual of Style (16th Edition):

Alahmadi, Dimah Hussain N. “RECOMMENDER SYSTEMS BASED ON ONLINE SOCIAL NETWORKS -AN IMPLICIT SOCIAL TRUST AND SENTIMENT ANALYSIS APPROACH.” 2017. Doctoral Dissertation, University of Manchester. Accessed April 25, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:306813.

MLA Handbook (7th Edition):

Alahmadi, Dimah Hussain N. “RECOMMENDER SYSTEMS BASED ON ONLINE SOCIAL NETWORKS -AN IMPLICIT SOCIAL TRUST AND SENTIMENT ANALYSIS APPROACH.” 2017. Web. 25 Apr 2019.

Vancouver:

Alahmadi DHN. RECOMMENDER SYSTEMS BASED ON ONLINE SOCIAL NETWORKS -AN IMPLICIT SOCIAL TRUST AND SENTIMENT ANALYSIS APPROACH. [Internet] [Doctoral dissertation]. University of Manchester; 2017. [cited 2019 Apr 25]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:306813.

Council of Science Editors:

Alahmadi DHN. RECOMMENDER SYSTEMS BASED ON ONLINE SOCIAL NETWORKS -AN IMPLICIT SOCIAL TRUST AND SENTIMENT ANALYSIS APPROACH. [Doctoral Dissertation]. University of Manchester; 2017. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:306813


McGill University

8. Garden, Matthew. On the Use of Semantic Feedback in Recommender Systems.

Degree: MS, School of Computer Science, 2004, McGill University

Note:

This thesis presents a new approach to recommender systems. Previous recommender systems based on collaborative filtering typically solicit user feedback on domain items as… (more)

Subjects/Keywords: Recommender systems

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

APA (6th Edition):

Garden, M. (2004). On the Use of Semantic Feedback in Recommender Systems. (Masters Thesis). McGill University. Retrieved from http://digitool.library.mcgill.ca/thesisfile161894.pdf

Chicago Manual of Style (16th Edition):

Garden, Matthew. “On the Use of Semantic Feedback in Recommender Systems.” 2004. Masters Thesis, McGill University. Accessed April 25, 2019. http://digitool.library.mcgill.ca/thesisfile161894.pdf.

MLA Handbook (7th Edition):

Garden, Matthew. “On the Use of Semantic Feedback in Recommender Systems.” 2004. Web. 25 Apr 2019.

Vancouver:

Garden M. On the Use of Semantic Feedback in Recommender Systems. [Internet] [Masters thesis]. McGill University; 2004. [cited 2019 Apr 25]. Available from: http://digitool.library.mcgill.ca/thesisfile161894.pdf.

Council of Science Editors:

Garden M. On the Use of Semantic Feedback in Recommender Systems. [Masters Thesis]. McGill University; 2004. Available from: http://digitool.library.mcgill.ca/thesisfile161894.pdf


Delft University of Technology

9. Wafula, J.B. Evaluation of Machine Learning Algorithms for Outlier Detection in Clustered Code Fragments:.

Degree: 2015, Delft University of Technology

 Many software systems are designed to be long-lived due to the costs involved in developing new systems. Changes in these systems are inevitable due to… (more)

Subjects/Keywords: Machine Learning; Recommender Systems

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

APA (6th Edition):

Wafula, J. B. (2015). Evaluation of Machine Learning Algorithms for Outlier Detection in Clustered Code Fragments:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2cc644d3-c95c-4331-8b07-445d491f697f

Chicago Manual of Style (16th Edition):

Wafula, J B. “Evaluation of Machine Learning Algorithms for Outlier Detection in Clustered Code Fragments:.” 2015. Masters Thesis, Delft University of Technology. Accessed April 25, 2019. http://resolver.tudelft.nl/uuid:2cc644d3-c95c-4331-8b07-445d491f697f.

MLA Handbook (7th Edition):

Wafula, J B. “Evaluation of Machine Learning Algorithms for Outlier Detection in Clustered Code Fragments:.” 2015. Web. 25 Apr 2019.

Vancouver:

Wafula JB. Evaluation of Machine Learning Algorithms for Outlier Detection in Clustered Code Fragments:. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2019 Apr 25]. Available from: http://resolver.tudelft.nl/uuid:2cc644d3-c95c-4331-8b07-445d491f697f.

Council of Science Editors:

Wafula JB. Evaluation of Machine Learning Algorithms for Outlier Detection in Clustered Code Fragments:. [Masters Thesis]. Delft University of Technology; 2015. Available from: http://resolver.tudelft.nl/uuid:2cc644d3-c95c-4331-8b07-445d491f697f


ITESO – Universidad Jesuita de Guadalajara

10. Hernández-Ortiz, Miguel A. Webpage recommender system .

Degree: 2016, ITESO – Universidad Jesuita de Guadalajara

 En este trabajo se hace una introducción al campo de estudio de los sistemas de recomendación. Se pretende aplicarlo para desarrollar un sistema recomendador para… (more)

Subjects/Keywords: Sistemas de Recomendación; Recommender Systems

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

APA (6th Edition):

Hernández-Ortiz, M. A. (2016). Webpage recommender system . (Thesis). ITESO – Universidad Jesuita de Guadalajara. Retrieved from http://hdl.handle.net/11117/4161

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):

Hernández-Ortiz, Miguel A. “Webpage recommender system .” 2016. Thesis, ITESO – Universidad Jesuita de Guadalajara. Accessed April 25, 2019. http://hdl.handle.net/11117/4161.

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

MLA Handbook (7th Edition):

Hernández-Ortiz, Miguel A. “Webpage recommender system .” 2016. Web. 25 Apr 2019.

Vancouver:

Hernández-Ortiz MA. Webpage recommender system . [Internet] [Thesis]. ITESO – Universidad Jesuita de Guadalajara; 2016. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/11117/4161.

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

Council of Science Editors:

Hernández-Ortiz MA. Webpage recommender system . [Thesis]. ITESO – Universidad Jesuita de Guadalajara; 2016. Available from: http://hdl.handle.net/11117/4161

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


University of New South Wales

11. Zhou, Bowen. Advanced Collaborative Filtering and Image-based Recommender Systems.

Degree: Computer Science & Engineering, 2017, University of New South Wales

 Due to burst of growth of information available all over the world, it has been of great necessity to retrieve most suitable data from the… (more)

Subjects/Keywords: Collaborative Filtering; Recommender Systems

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APA (6th Edition):

Zhou, B. (2017). Advanced Collaborative Filtering and Image-based Recommender Systems. (Masters Thesis). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/60049 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:51367/SOURCE2?view=true

Chicago Manual of Style (16th Edition):

Zhou, Bowen. “Advanced Collaborative Filtering and Image-based Recommender Systems.” 2017. Masters Thesis, University of New South Wales. Accessed April 25, 2019. http://handle.unsw.edu.au/1959.4/60049 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:51367/SOURCE2?view=true.

MLA Handbook (7th Edition):

Zhou, Bowen. “Advanced Collaborative Filtering and Image-based Recommender Systems.” 2017. Web. 25 Apr 2019.

Vancouver:

Zhou B. Advanced Collaborative Filtering and Image-based Recommender Systems. [Internet] [Masters thesis]. University of New South Wales; 2017. [cited 2019 Apr 25]. Available from: http://handle.unsw.edu.au/1959.4/60049 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:51367/SOURCE2?view=true.

Council of Science Editors:

Zhou B. Advanced Collaborative Filtering and Image-based Recommender Systems. [Masters Thesis]. University of New South Wales; 2017. Available from: http://handle.unsw.edu.au/1959.4/60049 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:51367/SOURCE2?view=true


University of Minnesota

12. Christakopoulou, Evangelia. Improving the Quality of Top-N Recommendation.

Degree: PhD, Computer Science, 2018, University of Minnesota

 Top-N recommenders are systems that provide a ranked list of N products to every user; the recommendations are of items that the user will potentially… (more)

Subjects/Keywords: Recommender Systems; Top-N Recommendation

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

APA (6th Edition):

Christakopoulou, E. (2018). Improving the Quality of Top-N Recommendation. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/195398

Chicago Manual of Style (16th Edition):

Christakopoulou, Evangelia. “Improving the Quality of Top-N Recommendation.” 2018. Doctoral Dissertation, University of Minnesota. Accessed April 25, 2019. http://hdl.handle.net/11299/195398.

MLA Handbook (7th Edition):

Christakopoulou, Evangelia. “Improving the Quality of Top-N Recommendation.” 2018. Web. 25 Apr 2019.

Vancouver:

Christakopoulou E. Improving the Quality of Top-N Recommendation. [Internet] [Doctoral dissertation]. University of Minnesota; 2018. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/11299/195398.

Council of Science Editors:

Christakopoulou E. Improving the Quality of Top-N Recommendation. [Doctoral Dissertation]. University of Minnesota; 2018. Available from: http://hdl.handle.net/11299/195398


University of Minnesota

13. Ekstrand, Michael. Towards Recommender Engineering: tools and experiments for identifying recommender differences.

Degree: PhD, 2014, University of Minnesota

 Since the introduction of their modern form 20 years ago, recommender systems have proven a valuable tool for help users manage information overload.Two decades of… (more)

Subjects/Keywords: Human-computer interaction; Recommender systems

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

APA (6th Edition):

Ekstrand, M. (2014). Towards Recommender Engineering: tools and experiments for identifying recommender differences. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/165307

Chicago Manual of Style (16th Edition):

Ekstrand, Michael. “Towards Recommender Engineering: tools and experiments for identifying recommender differences.” 2014. Doctoral Dissertation, University of Minnesota. Accessed April 25, 2019. http://hdl.handle.net/11299/165307.

MLA Handbook (7th Edition):

Ekstrand, Michael. “Towards Recommender Engineering: tools and experiments for identifying recommender differences.” 2014. Web. 25 Apr 2019.

Vancouver:

Ekstrand M. Towards Recommender Engineering: tools and experiments for identifying recommender differences. [Internet] [Doctoral dissertation]. University of Minnesota; 2014. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/11299/165307.

Council of Science Editors:

Ekstrand M. Towards Recommender Engineering: tools and experiments for identifying recommender differences. [Doctoral Dissertation]. University of Minnesota; 2014. Available from: http://hdl.handle.net/11299/165307


Brigham Young University

14. Brinton, Derrick James. Recommender Systems for Family History Source Discovery.

Degree: MS, 2017, Brigham Young University

 As interest in family history research increases, greater numbers of amateurs are participating in genealogy. However, finding sources that provide useful information on individuals in… (more)

Subjects/Keywords: Recommender Systems; Genealogy; Computer Sciences

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

APA (6th Edition):

Brinton, D. J. (2017). Recommender Systems for Family History Source Discovery. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=7606&context=etd

Chicago Manual of Style (16th Edition):

Brinton, Derrick James. “Recommender Systems for Family History Source Discovery.” 2017. Masters Thesis, Brigham Young University. Accessed April 25, 2019. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=7606&context=etd.

MLA Handbook (7th Edition):

Brinton, Derrick James. “Recommender Systems for Family History Source Discovery.” 2017. Web. 25 Apr 2019.

Vancouver:

Brinton DJ. Recommender Systems for Family History Source Discovery. [Internet] [Masters thesis]. Brigham Young University; 2017. [cited 2019 Apr 25]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=7606&context=etd.

Council of Science Editors:

Brinton DJ. Recommender Systems for Family History Source Discovery. [Masters Thesis]. Brigham Young University; 2017. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=7606&context=etd


University of Johannesburg

15. Leonard, Justin Sean. PerTrust : leveraging personality and trust for group recommendations.

Degree: 2014, University of Johannesburg

M.Sc. (Information Technology)

Recommender systems assist a system user to identify relevant content within a specific context. This is typically performed through an analysis of… (more)

Subjects/Keywords: Recommender systems (Information filtering); Information filtering systems

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

APA (6th Edition):

Leonard, J. S. (2014). PerTrust : leveraging personality and trust for group recommendations. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/11364

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):

Leonard, Justin Sean. “PerTrust : leveraging personality and trust for group recommendations.” 2014. Thesis, University of Johannesburg. Accessed April 25, 2019. http://hdl.handle.net/10210/11364.

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

MLA Handbook (7th Edition):

Leonard, Justin Sean. “PerTrust : leveraging personality and trust for group recommendations.” 2014. Web. 25 Apr 2019.

Vancouver:

Leonard JS. PerTrust : leveraging personality and trust for group recommendations. [Internet] [Thesis]. University of Johannesburg; 2014. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/10210/11364.

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

Council of Science Editors:

Leonard JS. PerTrust : leveraging personality and trust for group recommendations. [Thesis]. University of Johannesburg; 2014. Available from: http://hdl.handle.net/10210/11364

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


University of Texas – Austin

16. Budalakoti, Suratna. Expertise modeling and recommendation in online question and answer forums.

Degree: Electrical and Computer Engineering, 2009, University of Texas – Austin

 Question and answer (Q&A) forums, as a way for seeking expertise on the Internet, have seen rapid growth in popularity in recent years. The expertise… (more)

Subjects/Keywords: Recommender systems; Recommender engine; Expertise modeling; Online forums

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

APA (6th Edition):

Budalakoti, S. (2009). Expertise modeling and recommendation in online question and answer forums. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2009-12-519

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):

Budalakoti, Suratna. “Expertise modeling and recommendation in online question and answer forums.” 2009. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2009-12-519.

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

MLA Handbook (7th Edition):

Budalakoti, Suratna. “Expertise modeling and recommendation in online question and answer forums.” 2009. Web. 25 Apr 2019.

Vancouver:

Budalakoti S. Expertise modeling and recommendation in online question and answer forums. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2009-12-519.

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

Council of Science Editors:

Budalakoti S. Expertise modeling and recommendation in online question and answer forums. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/ETD-UT-2009-12-519

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


Texas State University – San Marcos

17. Mahant, Vaibhav. Improving Top-N Evaluation of Recommender Systems.

Degree: MS, Computer Science, 2016, Texas State University – San Marcos

Recommender systems are used to provide the user with a list of recommended items to help user find new items they might prefer. One of… (more)

Subjects/Keywords: Recommender Systems; Evaluation; Recommender systems (Information filtering); Management information systems; Artificial intelligence – Data processing

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

APA (6th Edition):

Mahant, V. (2016). Improving Top-N Evaluation of Recommender Systems. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/6309

Chicago Manual of Style (16th Edition):

Mahant, Vaibhav. “Improving Top-N Evaluation of Recommender Systems.” 2016. Masters Thesis, Texas State University – San Marcos. Accessed April 25, 2019. https://digital.library.txstate.edu/handle/10877/6309.

MLA Handbook (7th Edition):

Mahant, Vaibhav. “Improving Top-N Evaluation of Recommender Systems.” 2016. Web. 25 Apr 2019.

Vancouver:

Mahant V. Improving Top-N Evaluation of Recommender Systems. [Internet] [Masters thesis]. Texas State University – San Marcos; 2016. [cited 2019 Apr 25]. Available from: https://digital.library.txstate.edu/handle/10877/6309.

Council of Science Editors:

Mahant V. Improving Top-N Evaluation of Recommender Systems. [Masters Thesis]. Texas State University – San Marcos; 2016. Available from: https://digital.library.txstate.edu/handle/10877/6309


University of Edinburgh

18. Givon, Sharon. Predicting and using social tags to improve the accuracy and transparency of recommender systems.

Degree: PhD, 2011, University of Edinburgh

 This thesis describes work on using content to improve recommendation systems. Personalised recommendations help potential buyers filter information and identify products that they might be… (more)

Subjects/Keywords: 300.285; recommender systems; social tags; textual content

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

APA (6th Edition):

Givon, S. (2011). Predicting and using social tags to improve the accuracy and transparency of recommender systems. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/5770

Chicago Manual of Style (16th Edition):

Givon, Sharon. “Predicting and using social tags to improve the accuracy and transparency of recommender systems.” 2011. Doctoral Dissertation, University of Edinburgh. Accessed April 25, 2019. http://hdl.handle.net/1842/5770.

MLA Handbook (7th Edition):

Givon, Sharon. “Predicting and using social tags to improve the accuracy and transparency of recommender systems.” 2011. Web. 25 Apr 2019.

Vancouver:

Givon S. Predicting and using social tags to improve the accuracy and transparency of recommender systems. [Internet] [Doctoral dissertation]. University of Edinburgh; 2011. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/1842/5770.

Council of Science Editors:

Givon S. Predicting and using social tags to improve the accuracy and transparency of recommender systems. [Doctoral Dissertation]. University of Edinburgh; 2011. Available from: http://hdl.handle.net/1842/5770


Temple University

19. Zhao, Feipeng. Learning Top-N Recommender Systems with Implicit Feedbacks.

Degree: PhD, 2017, Temple University

Computer and Information Science

Top-N recommender systems automatically recommend N items for users from huge amounts of products. Personalized Top-N recommender systems have great impact… (more)

Subjects/Keywords: Computer science;

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

APA (6th Edition):

Zhao, F. (2017). Learning Top-N Recommender Systems with Implicit Feedbacks. (Doctoral Dissertation). Temple University. Retrieved from http://digital.library.temple.edu/u?/p245801coll10,450099

Chicago Manual of Style (16th Edition):

Zhao, Feipeng. “Learning Top-N Recommender Systems with Implicit Feedbacks.” 2017. Doctoral Dissertation, Temple University. Accessed April 25, 2019. http://digital.library.temple.edu/u?/p245801coll10,450099.

MLA Handbook (7th Edition):

Zhao, Feipeng. “Learning Top-N Recommender Systems with Implicit Feedbacks.” 2017. Web. 25 Apr 2019.

Vancouver:

Zhao F. Learning Top-N Recommender Systems with Implicit Feedbacks. [Internet] [Doctoral dissertation]. Temple University; 2017. [cited 2019 Apr 25]. Available from: http://digital.library.temple.edu/u?/p245801coll10,450099.

Council of Science Editors:

Zhao F. Learning Top-N Recommender Systems with Implicit Feedbacks. [Doctoral Dissertation]. Temple University; 2017. Available from: http://digital.library.temple.edu/u?/p245801coll10,450099


Hong Kong University of Science and Technology

20. Lu, Zhongqi. Temporal dynamics in recommender systems.

Degree: 2017, Hong Kong University of Science and Technology

 We investigate on the temporal dynamics phenomenon in recommender systems. By analyzing the public dataset from real world applications, we find the temporal dynamics phenomenon… (more)

Subjects/Keywords: Recommender systems (Information filtering); Mathematical models; Analysis

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

APA (6th Edition):

Lu, Z. (2017). Temporal dynamics in recommender systems. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1778947 ; http://repository.ust.hk/ir/bitstream/1783.1-87955/1/th_redirect.html

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):

Lu, Zhongqi. “Temporal dynamics in recommender systems.” 2017. Thesis, Hong Kong University of Science and Technology. Accessed April 25, 2019. https://doi.org/10.14711/thesis-b1778947 ; http://repository.ust.hk/ir/bitstream/1783.1-87955/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Lu, Zhongqi. “Temporal dynamics in recommender systems.” 2017. Web. 25 Apr 2019.

Vancouver:

Lu Z. Temporal dynamics in recommender systems. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2017. [cited 2019 Apr 25]. Available from: https://doi.org/10.14711/thesis-b1778947 ; http://repository.ust.hk/ir/bitstream/1783.1-87955/1/th_redirect.html.

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

Council of Science Editors:

Lu Z. Temporal dynamics in recommender systems. [Thesis]. Hong Kong University of Science and Technology; 2017. Available from: https://doi.org/10.14711/thesis-b1778947 ; http://repository.ust.hk/ir/bitstream/1783.1-87955/1/th_redirect.html

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


Hong Kong University of Science and Technology

21. Lu, Zhongqi. Selective transfer learning for cross domain recommendation.

Degree: 2013, Hong Kong University of Science and Technology

 Collaborative Filtering (CF) aims to predict users’ ratings on items according to historical user-itempreference data. In many real-world applications, preference data are usually sparse, which… (more)

Subjects/Keywords: Recommender systems (Information filtering); Machine learning

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

APA (6th Edition):

Lu, Z. (2013). Selective transfer learning for cross domain recommendation. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1240240 ; http://repository.ust.hk/ir/bitstream/1783.1-7976/1/th_redirect.html

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):

Lu, Zhongqi. “Selective transfer learning for cross domain recommendation.” 2013. Thesis, Hong Kong University of Science and Technology. Accessed April 25, 2019. https://doi.org/10.14711/thesis-b1240240 ; http://repository.ust.hk/ir/bitstream/1783.1-7976/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Lu, Zhongqi. “Selective transfer learning for cross domain recommendation.” 2013. Web. 25 Apr 2019.

Vancouver:

Lu Z. Selective transfer learning for cross domain recommendation. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2013. [cited 2019 Apr 25]. Available from: https://doi.org/10.14711/thesis-b1240240 ; http://repository.ust.hk/ir/bitstream/1783.1-7976/1/th_redirect.html.

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

Council of Science Editors:

Lu Z. Selective transfer learning for cross domain recommendation. [Thesis]. Hong Kong University of Science and Technology; 2013. Available from: https://doi.org/10.14711/thesis-b1240240 ; http://repository.ust.hk/ir/bitstream/1783.1-7976/1/th_redirect.html

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


University of Hong Kong

22. Li, Hui. Social network based recommender systems.

Degree: M. Phil., 2015, University of Hong Kong

Recommender systems have become de facto tools for suggesting items that are of potential interest to users and achieving great success in e-commerce. Many famous… (more)

Subjects/Keywords: Online social networks; Recommender systems (Information filtering)

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APA (6th Edition):

Li, H. (2015). Social network based recommender systems. (Masters Thesis). University of Hong Kong. Retrieved from Li, H. [李輝]. (2015). Social network based recommender systems. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5610991 ; http://hdl.handle.net/10722/221187

Chicago Manual of Style (16th Edition):

Li, Hui. “Social network based recommender systems.” 2015. Masters Thesis, University of Hong Kong. Accessed April 25, 2019. Li, H. [李輝]. (2015). Social network based recommender systems. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5610991 ; http://hdl.handle.net/10722/221187.

MLA Handbook (7th Edition):

Li, Hui. “Social network based recommender systems.” 2015. Web. 25 Apr 2019.

Vancouver:

Li H. Social network based recommender systems. [Internet] [Masters thesis]. University of Hong Kong; 2015. [cited 2019 Apr 25]. Available from: Li, H. [李輝]. (2015). Social network based recommender systems. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5610991 ; http://hdl.handle.net/10722/221187.

Council of Science Editors:

Li H. Social network based recommender systems. [Masters Thesis]. University of Hong Kong; 2015. Available from: Li, H. [李輝]. (2015). Social network based recommender systems. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5610991 ; http://hdl.handle.net/10722/221187


University of Hong Kong

23. 江浩; Jiang, Hao. Personalized web search re-ranking and content recommendation.

Degree: PhD, 2013, University of Hong Kong

 In this thesis, I propose a method for establishing a personalized recommendation system for re-ranking web search results and recommending web contents. The method is… (more)

Subjects/Keywords: Web usage mining; Recommender systems (Information filtering)

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

APA (6th Edition):

江浩; Jiang, H. (2013). Personalized web search re-ranking and content recommendation. (Doctoral Dissertation). University of Hong Kong. Retrieved from Jiang, H. [江浩]. (2013). Personalized web search re-ranking and content recommendation. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5194774 ; http://dx.doi.org/10.5353/th_b5194774 ; http://hdl.handle.net/10722/197548

Chicago Manual of Style (16th Edition):

江浩; Jiang, Hao. “Personalized web search re-ranking and content recommendation.” 2013. Doctoral Dissertation, University of Hong Kong. Accessed April 25, 2019. Jiang, H. [江浩]. (2013). Personalized web search re-ranking and content recommendation. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5194774 ; http://dx.doi.org/10.5353/th_b5194774 ; http://hdl.handle.net/10722/197548.

MLA Handbook (7th Edition):

江浩; Jiang, Hao. “Personalized web search re-ranking and content recommendation.” 2013. Web. 25 Apr 2019.

Vancouver:

江浩; Jiang H. Personalized web search re-ranking and content recommendation. [Internet] [Doctoral dissertation]. University of Hong Kong; 2013. [cited 2019 Apr 25]. Available from: Jiang, H. [江浩]. (2013). Personalized web search re-ranking and content recommendation. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5194774 ; http://dx.doi.org/10.5353/th_b5194774 ; http://hdl.handle.net/10722/197548.

Council of Science Editors:

江浩; Jiang H. Personalized web search re-ranking and content recommendation. [Doctoral Dissertation]. University of Hong Kong; 2013. Available from: Jiang, H. [江浩]. (2013). Personalized web search re-ranking and content recommendation. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5194774 ; http://dx.doi.org/10.5353/th_b5194774 ; http://hdl.handle.net/10722/197548


University of Toronto

24. Russell, Travis. An MDP-based Coupon Issuing System.

Degree: 2015, University of Toronto

We present a system based on the work of Shani et al. [An MDP-based recommender system," Journal of Machine Learning Research, vol. 6, pp. 1265-1295,… (more)

Subjects/Keywords: machine learning; probabilistic models; recommender systems; 0405

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APA (6th Edition):

Russell, T. (2015). An MDP-based Coupon Issuing System. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/70564

Chicago Manual of Style (16th Edition):

Russell, Travis. “An MDP-based Coupon Issuing System.” 2015. Masters Thesis, University of Toronto. Accessed April 25, 2019. http://hdl.handle.net/1807/70564.

MLA Handbook (7th Edition):

Russell, Travis. “An MDP-based Coupon Issuing System.” 2015. Web. 25 Apr 2019.

Vancouver:

Russell T. An MDP-based Coupon Issuing System. [Internet] [Masters thesis]. University of Toronto; 2015. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/1807/70564.

Council of Science Editors:

Russell T. An MDP-based Coupon Issuing System. [Masters Thesis]. University of Toronto; 2015. Available from: http://hdl.handle.net/1807/70564


University of California – Irvine

25. Seaver, Nicholas Patrick. Computing Taste: The Making of Algorithmic Music Recommendation.

Degree: Anthropology, 2015, University of California – Irvine

 This dissertation reports on several years of multi-sited ethnographic fieldwork with the developers of algorithmic music recommendation systems in the US. It identifies and contributes… (more)

Subjects/Keywords: Cultural anthropology; algorithms; music; recommender systems

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APA (6th Edition):

Seaver, N. P. (2015). Computing Taste: The Making of Algorithmic Music Recommendation. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/1p64m732

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):

Seaver, Nicholas Patrick. “Computing Taste: The Making of Algorithmic Music Recommendation.” 2015. Thesis, University of California – Irvine. Accessed April 25, 2019. http://www.escholarship.org/uc/item/1p64m732.

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

MLA Handbook (7th Edition):

Seaver, Nicholas Patrick. “Computing Taste: The Making of Algorithmic Music Recommendation.” 2015. Web. 25 Apr 2019.

Vancouver:

Seaver NP. Computing Taste: The Making of Algorithmic Music Recommendation. [Internet] [Thesis]. University of California – Irvine; 2015. [cited 2019 Apr 25]. Available from: http://www.escholarship.org/uc/item/1p64m732.

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

Council of Science Editors:

Seaver NP. Computing Taste: The Making of Algorithmic Music Recommendation. [Thesis]. University of California – Irvine; 2015. Available from: http://www.escholarship.org/uc/item/1p64m732

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


Ryerson University

26. Sivapalan, Sanjeevan. A genetic algorithm approach to recommender system cold start problem.

Degree: 2015, Ryerson University

Recommender systems (RS) are ubiquitous and used in many systems to augment user experience to improve usability and they achieve this by helping users discover… (more)

Subjects/Keywords: Recommender systems (Information filtering); Genetic algorithms.

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APA (6th Edition):

Sivapalan, S. (2015). A genetic algorithm approach to recommender system cold start problem. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A3664

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):

Sivapalan, Sanjeevan. “A genetic algorithm approach to recommender system cold start problem.” 2015. Thesis, Ryerson University. Accessed April 25, 2019. https://digital.library.ryerson.ca/islandora/object/RULA%3A3664.

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

MLA Handbook (7th Edition):

Sivapalan, Sanjeevan. “A genetic algorithm approach to recommender system cold start problem.” 2015. Web. 25 Apr 2019.

Vancouver:

Sivapalan S. A genetic algorithm approach to recommender system cold start problem. [Internet] [Thesis]. Ryerson University; 2015. [cited 2019 Apr 25]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3664.

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

Council of Science Editors:

Sivapalan S. A genetic algorithm approach to recommender system cold start problem. [Thesis]. Ryerson University; 2015. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3664

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


Ryerson University

27. Islam, Masudul. Personalized recommender system on whom to follow in Twitter.

Degree: 2014, Ryerson University

Recommender systems have been widely used in social networking sites. In this thesis, we propose a novel approach to recommend new followees to Twitter users… (more)

Subjects/Keywords: Recommender systems (Information filtering); Online social networks

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

APA (6th Edition):

Islam, M. (2014). Personalized recommender system on whom to follow in Twitter. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A2958

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):

Islam, Masudul. “Personalized recommender system on whom to follow in Twitter.” 2014. Thesis, Ryerson University. Accessed April 25, 2019. https://digital.library.ryerson.ca/islandora/object/RULA%3A2958.

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

MLA Handbook (7th Edition):

Islam, Masudul. “Personalized recommender system on whom to follow in Twitter.” 2014. Web. 25 Apr 2019.

Vancouver:

Islam M. Personalized recommender system on whom to follow in Twitter. [Internet] [Thesis]. Ryerson University; 2014. [cited 2019 Apr 25]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A2958.

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

Council of Science Editors:

Islam M. Personalized recommender system on whom to follow in Twitter. [Thesis]. Ryerson University; 2014. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A2958

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


University of Victoria

28. Zheng, Lan. Performance evaluation of latent factor models for rating prediction.

Degree: Department of Computer Science, 2015, University of Victoria

 Since the Netflix Prize competition, latent factor models (LFMs) have become the comparison ``staples'' for many of the recent recommender methods. Meanwhile, it is still… (more)

Subjects/Keywords: Recommender systems; latent factor models; evaluation

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APA (6th Edition):

Zheng, L. (2015). Performance evaluation of latent factor models for rating prediction. (Masters Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/6011

Chicago Manual of Style (16th Edition):

Zheng, Lan. “Performance evaluation of latent factor models for rating prediction.” 2015. Masters Thesis, University of Victoria. Accessed April 25, 2019. http://hdl.handle.net/1828/6011.

MLA Handbook (7th Edition):

Zheng, Lan. “Performance evaluation of latent factor models for rating prediction.” 2015. Web. 25 Apr 2019.

Vancouver:

Zheng L. Performance evaluation of latent factor models for rating prediction. [Internet] [Masters thesis]. University of Victoria; 2015. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/1828/6011.

Council of Science Editors:

Zheng L. Performance evaluation of latent factor models for rating prediction. [Masters Thesis]. University of Victoria; 2015. Available from: http://hdl.handle.net/1828/6011


University of Texas – Austin

29. Edwards, James Adrian. Quantifying the multi-user account problem for collaborative filtering based recommender systems.

Degree: Electrical and Computer Engineering, 2009, University of Texas – Austin

 Identification based recommender systems make no distinction between users and accounts; all the data collected during account sessions are attributed to a single user. In… (more)

Subjects/Keywords: Recommender systems; Collaborative filtering; Multi-user accounts

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

APA (6th Edition):

Edwards, J. A. (2009). Quantifying the multi-user account problem for collaborative filtering based recommender systems. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2009-12-460

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):

Edwards, James Adrian. “Quantifying the multi-user account problem for collaborative filtering based recommender systems.” 2009. Thesis, University of Texas – Austin. Accessed April 25, 2019. http://hdl.handle.net/2152/ETD-UT-2009-12-460.

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

MLA Handbook (7th Edition):

Edwards, James Adrian. “Quantifying the multi-user account problem for collaborative filtering based recommender systems.” 2009. Web. 25 Apr 2019.

Vancouver:

Edwards JA. Quantifying the multi-user account problem for collaborative filtering based recommender systems. [Internet] [Thesis]. University of Texas – Austin; 2009. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/2152/ETD-UT-2009-12-460.

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

Council of Science Editors:

Edwards JA. Quantifying the multi-user account problem for collaborative filtering based recommender systems. [Thesis]. University of Texas – Austin; 2009. Available from: http://hdl.handle.net/2152/ETD-UT-2009-12-460

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


Texas A&M University

30. Jayarathna, Ukwatta Kankanamalage Sampath. Unified Implicit and Explicit Feedback for Multi-Application User Interest Modeling.

Degree: PhD, Computer Science, 2016, Texas A&M University

 A user often interacts with multiple applications while working on a task. User models can be developed individually at each of the individual applications, but… (more)

Subjects/Keywords: user interest modeling; relevance feedback; recommender systems

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APA (6th Edition):

Jayarathna, U. K. S. (2016). Unified Implicit and Explicit Feedback for Multi-Application User Interest Modeling. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/158044

Chicago Manual of Style (16th Edition):

Jayarathna, Ukwatta Kankanamalage Sampath. “Unified Implicit and Explicit Feedback for Multi-Application User Interest Modeling.” 2016. Doctoral Dissertation, Texas A&M University. Accessed April 25, 2019. http://hdl.handle.net/1969.1/158044.

MLA Handbook (7th Edition):

Jayarathna, Ukwatta Kankanamalage Sampath. “Unified Implicit and Explicit Feedback for Multi-Application User Interest Modeling.” 2016. Web. 25 Apr 2019.

Vancouver:

Jayarathna UKS. Unified Implicit and Explicit Feedback for Multi-Application User Interest Modeling. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2019 Apr 25]. Available from: http://hdl.handle.net/1969.1/158044.

Council of Science Editors:

Jayarathna UKS. Unified Implicit and Explicit Feedback for Multi-Application User Interest Modeling. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/158044

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