Document Type : Research Paper

Authors

1 Msc. Student in computer science, Faculty of Math and Computer Science of Allame Tabataba’i, Tehran, Iran

2 Assistant Prof., Faculty of Math and Computer Sciences, Allame Tabatab’i University, Tehran, Iran

Abstract

 
 Given the overwhelming amount of information on the web, users face many options when selecting products or services. Recommender systems build a model based on information from users' past choices and ratings, related or trusted individuals, previously selected products, and the features of such products; the system then prioritize items to recommend them to the user based on this model. Trust aware method will use the trust network between users for estimating products ratings. Researchers have been interested in subject of trust in different facets because of different level of trust in professional fields. This article presents multi-faceted trust model for estimating product ratings, in which users and items are considered due to amount of dependency to each facet and also level of trust in it. Epinions dataset analysis indicates that distance dispersion of users’ choice in a multi-facted trust network is significantly lower than their distribution in a general trust network. Then baseline and similarity base models’ performance have been checked and compared in forms of general and multi-faceted. Model evaluation has been done based on Root Mean Squared Error and Epinions dataset separation in two groups of test and train and also croos validation method. Results indicate that estimation error has been averagely decreased 20% and improve recommender system performance obviously by considering trust component in multi-facted form. 



 

Keywords

 
حقیقی، الهام؛ و منتظر، غلامعلی. (1394)، شناسایی عوامل مؤثر بر اعتمادسازی در شبکه‌های اجتماعی برخط به کمک روش الکترۀ فازی، نشریه مدیریت فناوری اطلاعات، دوره 7، شماره 4، زمستان 1394، صفحه 715-740.
روشنی، سعید. رضایی نیک، نفیسه؛ و شجاعی، محمدحسین. (1392)، مطالعه مقایسه‌ای قابلیت سازی و جامعه‌پذیری شبکه‌های اجتماعی عمومی و تخصصی، نشریه مدیریت فناوری اطلاعات، دوره 2، شماره 5، تابستان 1392، صفحه 97-132.
کریمی علویجه، محمدرضا. عسکری، شیوا؛ و پرسته، سیروان. (1394)، فروشگاه اینترنتی هوشمند: سیستم پیشنهاددهندۀ مبتنی بر تحلیل رفتار کاربران، نشریه مدیریت فناوری اطلاعات، دوره 7، شماره 2، تابستان 1394، صفحه 385-406.
مطهری نژاد، مریم. ذوالفقار زاده، محمدمهدی؛ و خدنگی، احسان. (1395)، طراحی مدلی برای بهبود سیستم‌های پیشنهاددهندۀ بانکی بر اساس پیش‌بینی علایق مشتریان: کاربرد روش‎های داده‌کاوی، نشریه مدیریت فناوری اطلاعات، دوره 8، شماره2، تابستان 1395، صفحه 393-314.
Abbasi, M. A. Tang, J. & Liu, H. (2014). Trust-aware recommender systems. Machine Learning book on computational trust, Chapman & Hall/CRC Press.
Adomavicius, G. Bockstedt, J. Curley, S. & Zhang, J. (2014, September). De-biasing user preference ratings in recommender systems. In RecSys 2014 Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2014), Foster City, CA, USA (pp. 2-9).
Adomavicius, G. & Tuzhilin, A. (2011). Context-aware recommender systems. In Recommender systems handbook (pp. 217-253). Springer US.
Artz, D. & Gil, Y. (2007). A survey of trust in computer science and the semantic web. Web Semantics: Science, Services and Agents on the World Wide Web, 5(2), 58-71.
Bedi, P. & Agarwal, S. K. (2013). Aspect-Oriented trust based mobile recommender system. International Journal of Computer Information Systems and Industrial Management Applications, 5, 354-364.
Bell, R. M. & Koren, Y. (2007, October). Scalable collaborative filtering with jointly derived neighborhood interpolation weights. In Seventh IEEE International Conference on Data Mining (ICDM 2007) (pp. 43-52). IEEE.
Cosley, D. Lam, S. K. Albert, I. Konstan, J. A. & Riedl, J. (2003, April). Is seeing believing? how recommender system interfaces affect users' opinions. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 585-592). ACM.
Ekstrand, M. D. Riedl, J. T. & Konstan, J. A. (2011). Collaborative filtering recommender systems. Foundations and Trends in Human-Computer Interaction, 4(2), 81-173.
Goldberg, D. Nichols, D. Oki, B. M. & Terry, D. (1992). Using collaborative filtering to weave an information tapestry. Communications of the ACM,35(12), 61-70.
Herlocker, J. L. Konstan, J. A. Borchers, A. & Riedl, J. (1999, August). An algorithmic framework for performing collaborative filtering. InProceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval (pp. 230-237). ACM.
Herlocker, J. Konstan, J. A. & Riedl, J. (2002). An empirical analysis of design choices in neighborhood-based collaborative filtering algorithms.Information retrieval, 5(4), 287-310.
Hill, W. Stead, L. Rosenstein, M. & Furnas, G. (1995, May). Recommending and evaluating choices in a virtual community of use. InProceedings of the SIGCHI conference on Human factors in computing systems (pp. 194-201). ACM Press/Addison-Wesley Publishing Co...
Nilashi, M. bin Ibrahim, O. & Ithnin, N. (2014). Multi-criteria collaborative filtering with high accuracy using higher order singular value decomposition and Neuro-Fuzzy system. Knowledge-Based Systems, 60, 82-101.
Potter, G. (2008, August). Putting the collaborator back into collaborative filtering. In Proceedings of the 2nd KDD Workshop on Large-Scale Recommender Systems and the Netflix Prize Competition (p. 3). ACM.
Resnick, P. Iacovou, N. Suchak, M. Bergstrom, P. & Riedl, J. (1994, October). GroupLens: an open architecture for collaborative filtering of netnews. In Proceedings of the 1994 ACM conference on Computer supported cooperative work (pp. 175-186). ACM.
Shardanand, U. & Maes, P. (1995, May). Social information filtering: algorithms for automating “word of mouth”. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 210-217). ACM Press/Addison-Wesley Publishing Co...
Tang, J. Gao, H. & Liu, H. (2012, February). mTrust: discerning multi-faceted trust in a connected world. In Proceedings of the fifth ACM international conference on Web search and data mining (pp. 93-102). ACM.
Ziegler, C. N. (2004, March). Semantic web recommender systems. InInternational Conference on Extending Database Technology (pp. 78-89). Springer Berlin Heidelberg.
 
 
حقیقی، الهام؛ و منتظر، غلامعلی. (1394)، شناسایی عوامل مؤثر بر اعتمادسازی در شبکه‌های اجتماعی برخط به کمک روش الکترۀ فازی، نشریه مدیریت فناوری اطلاعات، دوره 7، شماره 4، زمستان 1394، صفحه 715-740.
روشنی، سعید. رضایی نیک، نفیسه؛ و شجاعی، محمدحسین. (1392)، مطالعه مقایسه‌ای قابلیت سازی و جامعه‌پذیری شبکه‌های اجتماعی عمومی و تخصصی، نشریه مدیریت فناوری اطلاعات، دوره 2، شماره 5، تابستان 1392، صفحه 97-132.
کریمی علویجه، محمدرضا. عسکری، شیوا؛ و پرسته، سیروان. (1394)، فروشگاه اینترنتی هوشمند: سیستم پیشنهاددهندۀ مبتنی بر تحلیل رفتار کاربران، نشریه مدیریت فناوری اطلاعات، دوره 7، شماره 2، تابستان 1394، صفحه 385-406.
مطهری نژاد، مریم. ذوالفقار زاده، محمدمهدی؛ و خدنگی، احسان. (1395)، طراحی مدلی برای بهبود سیستم‌های پیشنهاددهندۀ بانکی بر اساس پیش‌بینی علایق مشتریان: کاربرد روش‎های داده‌کاوی، نشریه مدیریت فناوری اطلاعات، دوره 8، شماره2، تابستان 1395، صفحه 393-314.
Abbasi, M. A. Tang, J. & Liu, H. (2014). Trust-aware recommender systems. Machine Learning book on computational trust, Chapman & Hall/CRC Press.
Adomavicius, G. Bockstedt, J. Curley, S. & Zhang, J. (2014, September). De-biasing user preference ratings in recommender systems. In RecSys 2014 Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2014), Foster City, CA, USA (pp. 2-9).
Adomavicius, G. & Tuzhilin, A. (2011). Context-aware recommender systems. In Recommender systems handbook (pp. 217-253). Springer US.
Artz, D. & Gil, Y. (2007). A survey of trust in computer science and the semantic web. Web Semantics: Science, Services and Agents on the World Wide Web, 5(2), 58-71.
Bedi, P. & Agarwal, S. K. (2013). Aspect-Oriented trust based mobile recommender system. International Journal of Computer Information Systems and Industrial Management Applications, 5, 354-364.
Bell, R. M. & Koren, Y. (2007, October). Scalable collaborative filtering with jointly derived neighborhood interpolation weights. In Seventh IEEE International Conference on Data Mining (ICDM 2007) (pp. 43-52). IEEE.
Cosley, D. Lam, S. K. Albert, I. Konstan, J. A. & Riedl, J. (2003, April). Is seeing believing? how recommender system interfaces affect users' opinions. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 585-592). ACM.
Ekstrand, M. D. Riedl, J. T. & Konstan, J. A. (2011). Collaborative filtering recommender systems. Foundations and Trends in Human-Computer Interaction, 4(2), 81-173.
Goldberg, D. Nichols, D. Oki, B. M. & Terry, D. (1992). Using collaborative filtering to weave an information tapestry. Communications of the ACM,35(12), 61-70.
Herlocker, J. L. Konstan, J. A. Borchers, A. & Riedl, J. (1999, August). An algorithmic framework for performing collaborative filtering. InProceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval (pp. 230-237). ACM.
Herlocker, J. Konstan, J. A. & Riedl, J. (2002). An empirical analysis of design choices in neighborhood-based collaborative filtering algorithms.Information retrieval, 5(4), 287-310.
Hill, W. Stead, L. Rosenstein, M. & Furnas, G. (1995, May). Recommending and evaluating choices in a virtual community of use. InProceedings of the SIGCHI conference on Human factors in computing systems (pp. 194-201). ACM Press/Addison-Wesley Publishing Co...
Nilashi, M. bin Ibrahim, O. & Ithnin, N. (2014). Multi-criteria collaborative filtering with high accuracy using higher order singular value decomposition and Neuro-Fuzzy system. Knowledge-Based Systems, 60, 82-101.
Potter, G. (2008, August). Putting the collaborator back into collaborative filtering. In Proceedings of the 2nd KDD Workshop on Large-Scale Recommender Systems and the Netflix Prize Competition (p. 3). ACM.
Resnick, P. Iacovou, N. Suchak, M. Bergstrom, P. & Riedl, J. (1994, October). GroupLens: an open architecture for collaborative filtering of netnews. In Proceedings of the 1994 ACM conference on Computer supported cooperative work (pp. 175-186). ACM.
Shardanand, U. & Maes, P. (1995, May). Social information filtering: algorithms for automating “word of mouth”. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 210-217). ACM Press/Addison-Wesley Publishing Co...
Tang, J. Gao, H. & Liu, H. (2012, February). mTrust: discerning multi-faceted trust in a connected world. In Proceedings of the fifth ACM international conference on Web search and data mining (pp. 93-102). ACM.
Ziegler, C. N. (2004, March). Semantic web recommender systems. InInternational Conference on Extending Database Technology (pp. 78-89). Springer Berlin Heidelberg.