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You searched for subject:(Collaborative filtering). Showing records 1 – 14 of 14 total matches.

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University of New South Wales

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

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 June 19, 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. 19 Jun 2019.

Vancouver:

Zhou B. Advanced Collaborative Filtering and Image-based Recommender Systems. [Internet] [Masters thesis]. University of New South Wales; 2017. [cited 2019 Jun 19]. 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


RMIT University

2. Badsha, S. Privacy preserving recommender systems.

Degree: 2018, RMIT University

 The recommender systems help users find suitable and interesting products and contents from the huge amount of information that are available in the internet. There… (more)

Subjects/Keywords: Fields of Research; Cryptography; Recommender systems; Collaborative filtering; Encryption; Content based filtering; Ratings; Users

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

APA (6th Edition):

Badsha, S. (2018). Privacy preserving recommender systems. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:162593

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):

Badsha, S. “Privacy preserving recommender systems.” 2018. Thesis, RMIT University. Accessed June 19, 2019. http://researchbank.rmit.edu.au/view/rmit:162593.

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

MLA Handbook (7th Edition):

Badsha, S. “Privacy preserving recommender systems.” 2018. Web. 19 Jun 2019.

Vancouver:

Badsha S. Privacy preserving recommender systems. [Internet] [Thesis]. RMIT University; 2018. [cited 2019 Jun 19]. Available from: http://researchbank.rmit.edu.au/view/rmit:162593.

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

Council of Science Editors:

Badsha S. Privacy preserving recommender systems. [Thesis]. RMIT University; 2018. Available from: http://researchbank.rmit.edu.au/view/rmit:162593

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


University of New South Wales

3. Chowdhury, Nipa. Collaborative learning for recommender systems by boosting and non-parametric methods.

Degree: Computer Science & Engineering, 2016, University of New South Wales

 As the Internet becomes larger in size, its information content threatens to be-come overwhelming. Therefore, recommender systems have gained much attentionin information retrieval to guide… (more)

Subjects/Keywords: Matrix Factorisation,; Recommender Systems,; Collaborative Filtering,; Boosting,; Non-parametric methods

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

APA (6th Edition):

Chowdhury, N. (2016). Collaborative learning for recommender systems by boosting and non-parametric methods. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/58816 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:47632/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Chowdhury, Nipa. “Collaborative learning for recommender systems by boosting and non-parametric methods.” 2016. Doctoral Dissertation, University of New South Wales. Accessed June 19, 2019. http://handle.unsw.edu.au/1959.4/58816 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:47632/SOURCE02?view=true.

MLA Handbook (7th Edition):

Chowdhury, Nipa. “Collaborative learning for recommender systems by boosting and non-parametric methods.” 2016. Web. 19 Jun 2019.

Vancouver:

Chowdhury N. Collaborative learning for recommender systems by boosting and non-parametric methods. [Internet] [Doctoral dissertation]. University of New South Wales; 2016. [cited 2019 Jun 19]. Available from: http://handle.unsw.edu.au/1959.4/58816 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:47632/SOURCE02?view=true.

Council of Science Editors:

Chowdhury N. Collaborative learning for recommender systems by boosting and non-parametric methods. [Doctoral Dissertation]. University of New South Wales; 2016. Available from: http://handle.unsw.edu.au/1959.4/58816 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:47632/SOURCE02?view=true


Australian National University

4. Sedhain, Suvash. A Unified Approach to Collaborative Filtering via Linear Models and Beyond .

Degree: 2016, Australian National University

 Recommending a personalised list of items to users is a core task for many online services such as Amazon, Netflix, and Youtube. Recommender systems are… (more)

Subjects/Keywords: Recommender System; One-Class Collaborative Filtering; Cold-Start Recommendation; Social Recommendation; Rating Prediction; Deep Learning

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

APA (6th Edition):

Sedhain, S. (2016). A Unified Approach to Collaborative Filtering via Linear Models and Beyond . (Thesis). Australian National University. Retrieved from http://hdl.handle.net/1885/118270

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):

Sedhain, Suvash. “A Unified Approach to Collaborative Filtering via Linear Models and Beyond .” 2016. Thesis, Australian National University. Accessed June 19, 2019. http://hdl.handle.net/1885/118270.

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

MLA Handbook (7th Edition):

Sedhain, Suvash. “A Unified Approach to Collaborative Filtering via Linear Models and Beyond .” 2016. Web. 19 Jun 2019.

Vancouver:

Sedhain S. A Unified Approach to Collaborative Filtering via Linear Models and Beyond . [Internet] [Thesis]. Australian National University; 2016. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/1885/118270.

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

Council of Science Editors:

Sedhain S. A Unified Approach to Collaborative Filtering via Linear Models and Beyond . [Thesis]. Australian National University; 2016. Available from: http://hdl.handle.net/1885/118270

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


Queensland University of Technology

5. Tang, Xiaoyu. Multidimensional recommendation framework based on the incorporation of nearest neighbourhood and tensor factorisation.

Degree: 2016, Queensland University of Technology

 This thesis investigated in depth the distinctive relations between users, items, and tags in recommender systems. This thesis proposed a number of novel techniques to… (more)

Subjects/Keywords: Collaborative Filtering; User Profiling; Recommender Systems; Multidimensional datasets; Folksonomy; Tags; Taxonomy; Personalisation

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

APA (6th Edition):

Tang, X. (2016). Multidimensional recommendation framework based on the incorporation of nearest neighbourhood and tensor factorisation. (Thesis). Queensland University of Technology. Retrieved from http://eprints.qut.edu.au/96195/

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):

Tang, Xiaoyu. “Multidimensional recommendation framework based on the incorporation of nearest neighbourhood and tensor factorisation.” 2016. Thesis, Queensland University of Technology. Accessed June 19, 2019. http://eprints.qut.edu.au/96195/.

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

MLA Handbook (7th Edition):

Tang, Xiaoyu. “Multidimensional recommendation framework based on the incorporation of nearest neighbourhood and tensor factorisation.” 2016. Web. 19 Jun 2019.

Vancouver:

Tang X. Multidimensional recommendation framework based on the incorporation of nearest neighbourhood and tensor factorisation. [Internet] [Thesis]. Queensland University of Technology; 2016. [cited 2019 Jun 19]. Available from: http://eprints.qut.edu.au/96195/.

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

Council of Science Editors:

Tang X. Multidimensional recommendation framework based on the incorporation of nearest neighbourhood and tensor factorisation. [Thesis]. Queensland University of Technology; 2016. Available from: http://eprints.qut.edu.au/96195/

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


Queensland University of Technology

6. Weng, Li-Tung. Information enrichment for quality recommender systems.

Degree: 2008, Queensland University of Technology

 The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems… (more)

Subjects/Keywords: collaborative filtering; cold-start problem; distributed systems; ecommerce; product taxonomy; recommendation novelty; recommender systems

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

APA (6th Edition):

Weng, L. (2008). Information enrichment for quality recommender systems. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/29165/

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):

Weng, Li-Tung. “Information enrichment for quality recommender systems.” 2008. Thesis, Queensland University of Technology. Accessed June 19, 2019. https://eprints.qut.edu.au/29165/.

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

MLA Handbook (7th Edition):

Weng, Li-Tung. “Information enrichment for quality recommender systems.” 2008. Web. 19 Jun 2019.

Vancouver:

Weng L. Information enrichment for quality recommender systems. [Internet] [Thesis]. Queensland University of Technology; 2008. [cited 2019 Jun 19]. Available from: https://eprints.qut.edu.au/29165/.

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

Council of Science Editors:

Weng L. Information enrichment for quality recommender systems. [Thesis]. Queensland University of Technology; 2008. Available from: https://eprints.qut.edu.au/29165/

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


University of Technology, Sydney

7. 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 June 19, 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. 19 Jun 2019.

Vancouver:

Hao P. Cross-domain recommender system through tag-based models. [Internet] [Thesis]. University of Technology, Sydney; 2018. [cited 2019 Jun 19]. 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 Adelaide

8. Lu, Zhigang. Privacy preserving neighbourhood-based collaborative filtering recommendation algorithms.

Degree: 2015, University of Adelaide

 Recommender systems, which recommend users the potentially preferred items by aggregating similar interest neighbours’ history data, show an increasing importance in various Internet applications. As… (more)

Subjects/Keywords: privacy preserving; differential privacy; neighbourhood-based collaborative filtering; internet commerce; recommender systems

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

APA (6th Edition):

Lu, Z. (2015). Privacy preserving neighbourhood-based collaborative filtering recommendation algorithms. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/98720

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, Zhigang. “Privacy preserving neighbourhood-based collaborative filtering recommendation algorithms.” 2015. Thesis, University of Adelaide. Accessed June 19, 2019. http://hdl.handle.net/2440/98720.

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

MLA Handbook (7th Edition):

Lu, Zhigang. “Privacy preserving neighbourhood-based collaborative filtering recommendation algorithms.” 2015. Web. 19 Jun 2019.

Vancouver:

Lu Z. Privacy preserving neighbourhood-based collaborative filtering recommendation algorithms. [Internet] [Thesis]. University of Adelaide; 2015. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/2440/98720.

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. Privacy preserving neighbourhood-based collaborative filtering recommendation algorithms. [Thesis]. University of Adelaide; 2015. Available from: http://hdl.handle.net/2440/98720

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


Deakin University

9. Ren, Yongli. Intelligent techniques for recommender systems.

Degree: School of Information Technology, 2013, Deakin University

 This thesis focuses on the data sparsity issue and the temporal dynamic issue in the context of collaborative filtering, and addresses them with imputation techniques,… (more)

Subjects/Keywords: Recommender systems; Collaborative filtering; Imputation techniques; Low-rank subspace techniques; Optimizations techniques; Rating pattern subspace

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

APA (6th Edition):

Ren, Y. (2013). Intelligent techniques for recommender systems. (Thesis). Deakin University. Retrieved from http://hdl.handle.net/10536/DRO/DU:30062528

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):

Ren, Yongli. “Intelligent techniques for recommender systems.” 2013. Thesis, Deakin University. Accessed June 19, 2019. http://hdl.handle.net/10536/DRO/DU:30062528.

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

MLA Handbook (7th Edition):

Ren, Yongli. “Intelligent techniques for recommender systems.” 2013. Web. 19 Jun 2019.

Vancouver:

Ren Y. Intelligent techniques for recommender systems. [Internet] [Thesis]. Deakin University; 2013. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10536/DRO/DU:30062528.

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

Council of Science Editors:

Ren Y. Intelligent techniques for recommender systems. [Thesis]. Deakin University; 2013. Available from: http://hdl.handle.net/10536/DRO/DU:30062528

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


University of Technology, Sydney

10. Li, Fangfang. Incorporating couplings into collaborative filtering.

Degree: 2016, University of Technology, Sydney

 Recommender Systems (RS) have been proposed to help users tackle information overload by suggesting potentially interesting items to users. A typical RS usually has a… (more)

Subjects/Keywords: Recommender Systems (RS).; Collaborative Filtering (CF).; Hybrid Filtering.; Coupling.; Coupled user-based matrix factorization (CUMF).; Coupled item-based matrix factorization (CIMF).; Coupled matrix factorization (CMF).

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

APA (6th Edition):

Li, F. (2016). Incorporating couplings into collaborative filtering. (Thesis). University of Technology, Sydney. Retrieved from http://hdl.handle.net/10453/44174

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

Chicago Manual of Style (16th Edition):

Li, Fangfang. “Incorporating couplings into collaborative filtering.” 2016. Thesis, University of Technology, Sydney. Accessed June 19, 2019. http://hdl.handle.net/10453/44174.

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

MLA Handbook (7th Edition):

Li, Fangfang. “Incorporating couplings into collaborative filtering.” 2016. Web. 19 Jun 2019.

Vancouver:

Li F. Incorporating couplings into collaborative filtering. [Internet] [Thesis]. University of Technology, Sydney; 2016. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10453/44174.

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

Council of Science Editors:

Li F. Incorporating couplings into collaborative filtering. [Thesis]. University of Technology, Sydney; 2016. Available from: http://hdl.handle.net/10453/44174

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


Queensland University of Technology

11. Chen, Lin. A social matching system : using implicit and explicit information for personalized recommendation in online dating service.

Degree: 2013, Queensland University of Technology

 Online dating websites enable a specific form of social networking and their efficiency can be increased by supporting proactive recommendations based on participants' preferences with… (more)

Subjects/Keywords: Online Dating Network; Social Matching; Social Network Analysis; Recommendation System; Collaborative Filtering; User Profile; Implicit Preference; Explicit Preference

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

APA (6th Edition):

Chen, L. (2013). A social matching system : using implicit and explicit information for personalized recommendation in online dating service. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/64157/

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, Lin. “A social matching system : using implicit and explicit information for personalized recommendation in online dating service.” 2013. Thesis, Queensland University of Technology. Accessed June 19, 2019. https://eprints.qut.edu.au/64157/.

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

MLA Handbook (7th Edition):

Chen, Lin. “A social matching system : using implicit and explicit information for personalized recommendation in online dating service.” 2013. Web. 19 Jun 2019.

Vancouver:

Chen L. A social matching system : using implicit and explicit information for personalized recommendation in online dating service. [Internet] [Thesis]. Queensland University of Technology; 2013. [cited 2019 Jun 19]. Available from: https://eprints.qut.edu.au/64157/.

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

Council of Science Editors:

Chen L. A social matching system : using implicit and explicit information for personalized recommendation in online dating service. [Thesis]. Queensland University of Technology; 2013. Available from: https://eprints.qut.edu.au/64157/

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


University of New South Wales

12. Lim, Soo Ling. Social networks and collaborative filtering for large-scale requirements elicitation.

Degree: Computer Science & Engineering, 2010, University of New South Wales

 Within the field of software engineering, requirements elicitation is the activity in which stakeholder needs are understood. In large-scale software projects, requirements elicitation tends to… (more)

Subjects/Keywords: Rrequirements engineering; Social network analysis; Stakeholder analysis; Software engineering; Collaborative filtering; Large-scale; Software projects; Project management; Requirements elicitation

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

APA (6th Edition):

Lim, S. L. (2010). Social networks and collaborative filtering for large-scale requirements elicitation. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/50210 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:9088/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Lim, Soo Ling. “Social networks and collaborative filtering for large-scale requirements elicitation.” 2010. Doctoral Dissertation, University of New South Wales. Accessed June 19, 2019. http://handle.unsw.edu.au/1959.4/50210 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:9088/SOURCE02?view=true.

MLA Handbook (7th Edition):

Lim, Soo Ling. “Social networks and collaborative filtering for large-scale requirements elicitation.” 2010. Web. 19 Jun 2019.

Vancouver:

Lim SL. Social networks and collaborative filtering for large-scale requirements elicitation. [Internet] [Doctoral dissertation]. University of New South Wales; 2010. [cited 2019 Jun 19]. Available from: http://handle.unsw.edu.au/1959.4/50210 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:9088/SOURCE02?view=true.

Council of Science Editors:

Lim SL. Social networks and collaborative filtering for large-scale requirements elicitation. [Doctoral Dissertation]. University of New South Wales; 2010. Available from: http://handle.unsw.edu.au/1959.4/50210 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:9088/SOURCE02?view=true


University of Technology, Sydney

13. Wang, Wei. Enhanced group recommender system and visualization.

Degree: 2016, University of Technology, Sydney

 Requirement of group recommender systems (GRSs) is experiencing a dramatic growth due to intelligent services being applied more broadly and involved in more and more… (more)

Subjects/Keywords: Group recommender systems (GRSs).; E-shopping & e-tourism.; Group profiles modelling.; Analysis of contributed member ratings.; Contribution Score.; Local collaborative filtering method.; Contribution Score-based Group Recommendation (CS-GR) approach.; GRSs effectivity.

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

APA (6th Edition):

Wang, W. (2016). Enhanced group recommender system and visualization. (Thesis). University of Technology, Sydney. Retrieved from http://hdl.handle.net/10453/62409

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

Chicago Manual of Style (16th Edition):

Wang, Wei. “Enhanced group recommender system and visualization.” 2016. Thesis, University of Technology, Sydney. Accessed June 19, 2019. http://hdl.handle.net/10453/62409.

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

MLA Handbook (7th Edition):

Wang, Wei. “Enhanced group recommender system and visualization.” 2016. Web. 19 Jun 2019.

Vancouver:

Wang W. Enhanced group recommender system and visualization. [Internet] [Thesis]. University of Technology, Sydney; 2016. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10453/62409.

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

Council of Science Editors:

Wang W. Enhanced group recommender system and visualization. [Thesis]. University of Technology, Sydney; 2016. Available from: http://hdl.handle.net/10453/62409

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


University of Adelaide

14. Ma, Hui. Collaborative information processing techniques for target tracking in wireless sensor networks.

Degree: 2008, University of Adelaide

 Target tracking is one of the typical applications of wireless sensor networks: a large number of spatially deployed sensor nodes collaboratively sense, process and estimate… (more)

Subjects/Keywords: target tracking; wireless sensor network; Kalman filter; Particle filter; collaborative information processing; Wireless sensor networks. Kalman filtering.

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

APA (6th Edition):

Ma, H. (2008). Collaborative information processing techniques for target tracking in wireless sensor networks. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/49462

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):

Ma, Hui. “Collaborative information processing techniques for target tracking in wireless sensor networks.” 2008. Thesis, University of Adelaide. Accessed June 19, 2019. http://hdl.handle.net/2440/49462.

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

MLA Handbook (7th Edition):

Ma, Hui. “Collaborative information processing techniques for target tracking in wireless sensor networks.” 2008. Web. 19 Jun 2019.

Vancouver:

Ma H. Collaborative information processing techniques for target tracking in wireless sensor networks. [Internet] [Thesis]. University of Adelaide; 2008. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/2440/49462.

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

Council of Science Editors:

Ma H. Collaborative information processing techniques for target tracking in wireless sensor networks. [Thesis]. University of Adelaide; 2008. Available from: http://hdl.handle.net/2440/49462

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

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