Abstract
As a consequence of the exponential growth of Internet and its services, including social applications fostering collaboration on the Web, information sharing had become pervasive. This caused a crescent need of more powerful tools to help users with the task of selecting interesting resources. Recommender systems have emerged as a solution to evaluate the quality of massively user-generated contents in open environments and provide recommendations based not only on the user interests but also on the opinions of people with similar tastes. In addition to interest similarity, however, trustworthiness is a factor that recommenders have to consider in the selection of reliable peers for collaboration. Most approaches in this regard estimates trust base on global user profile similarity or history of exchanged opinions. In this paper, we propose a novel approach for agent-based recommendation in which trust is independently learned and evolved for each pair of interest topics two users have in common. Experimental results show that agents learning who to trust about certain topics reach better levels of precision than considering interest similarity exclusively.







Similar content being viewed by others
References
Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans Knowl Data Eng 17(6):734–749
Chua FCT, Lim E-P (2010) Trust network inference for online rating data using generative models. In: Proceedings of the 16th ACM SIGKDD international conference on knowledge discovery and data mining (KDD ’10), pp 889–898
Giménez-Lugo GA, Amandi A, Sichman J, Godoy D (2002) Enriching information agents’ knowledge by ontology comparison: a case study. In: Advances in artificial intelligence, vol 2527 of LNCS, Springer, Berlin, pp 546–555
Godoy D, Amandi A (2005) User profiling for Web page filtering. IEEE Internet Comput 9(4):56–64
Godoy D, Amandi A (2006) A conceptual clustering approach for user profiling in personal information agents. AI Commun 19(3):207–227
Godoy D, Amandi A (2008) Collaborative Web search based on user interest similarity. Int J Cooperat Inf Syst Spec Issue Des Implement Groupw 17(4):495–521
Golbeck J (2005) Computing and applying trust in Web-based social networks. PhD thesis, University of Maryland, College Park
Golbeck J (2006) FilmTrust: movie recommendations from semantic Web-based social networks. In: IEEE consumer communications and networking conference, pp 1314–1315
Hang C-W, Singh MP (2010) Trust-based recommendation based on graph similarity. In: Proceedings of the 13th AAMAS workshop on trust in agent societies (Trust)
Heckmann D (2001) Ubiquitous user modeling for situated interaction. In: Proceedings of the 8th international conference on user modeling (UM’2001), Sonthofen, pp 280–282
Jamali M, Ester M (2009) TrustWalker: a random walk model for combining trust-based and item-based recommendation. In: Proceedings of the 15th ACM SIGKDD international conference on knowledge discovery and data mining (KDD ’09), pp 397–406
Jonker CM, Treur J (1999) Formal analysis of models for the dynamics of trust based on experiences. In: Proceedings of the 9th European workshop on modelling autonomous agents in a multi-agent world, pp 221–231
Kim HR, Chan PK (2003) Learning implicit user interest hierarchy for context in personalization. In: Proceedings of the 8th international conference on intelligent user interfaces, pp 101–108
Lee DH, Brusilovsky P (2009) Does trust influence information similarity?. In: ACM RecSys’09 workshop on recommender systems & the social Web
Li Y, Zhong N (2006) Mining ontology for automatically acquiring Web user information needs. IEEE Trans Knowl Data Eng 18(4):554–568
Lorenz A (2005) A specification for agent-based distributed user modelling in ubiquitous computing. In: Proceedings of the 1st workshop on decentralized, agent based and social approaches to user modelling (DASUM 2005), Edinburgh, pp 31–40
Massa P, Avesani P (2007) Trust-aware recommender systems. In Proceedings of the 2007 ACM conference on recommender systems, pp 17–24
Middleton S, Shadbolt N, Roure D (2004) Ontological user profiling in recommender systems. ACM Trans Inf Syst 22(1):54–88
Mitchell TM (1997) Machine learning. McGraw-Hill, New York
Montaner M, López B, de la Rosa JL (2002) Opinion-based filtering through trust. In Springer, editor, Proceedings of the 6th International Workshop on cooperative information agents (CIA 2002), vol 2446 of LNCS, pp 164–178
Nanas N, Uren V, De Roeck A (2003) Building and applying a concept hierarchy representation of a user profile. In: Proceedings of the 26th annual international ACM SIGIR conference on research and development in information retrieval, pp 198–204
O’Donovan J, Smyth B (2005) Trust in recommender systems. In: Proceedings of the 10th international conference on intelligent user interfaces, pp 167–174
O’Donovan J, Smyth B (2005) Trust no one: evaluating trust-based filtering for recommenders. In: Proceedings of the 19th international joint conference on artificial intelligence (IJCAI’05), pp 1663–1665
Papagelis M, Plexousakis D, Kutsuras T (2005) Alleviating the sparsity problem of collaborative filtering using trust inferences. In: Trust management, vol 3477 of LNCS, pp 224–239
Pitsilis G, Knapskog SJ (2009) Social trust as a solution to address sparsity-inherent problems of recommender systems. In: ACM RecSys’09 workshop on recommender systems & the social Web
Rodríguez MA, Egenhofer MJ (2003) Determining semantic similarity among entity classes from different ontologies. IEEE Trans Knowl Data Eng 15(2):442–456
Weng J, Miao C, Goh A (2006) Improving collaborative filtering with trust-based metrics. In: Proceedings of the 2006 ACM symposium on applied computing (SAC ’06), pp 1860–1864
Zhang F, Xu S (2007) Topic-level trust in recommender systems. In: International conference on management science and engineering (ICMSE 2007), pp 156–161
Ziegler C, Golbeck J (2007) Investigating interactions of trust and interest similarity. Decis Support Syst 43(2):460–475
Acknowledgments
This research was supported by the National Scientific and Technical Research Council (CONICET) under grant PIP No. 114-200901-00381.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Godoy, D., Amandi, A. Enabling topic-level trust for collaborative information sharing. Pers Ubiquit Comput 16, 1065–1077 (2012). https://doi.org/10.1007/s00779-011-0440-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00779-011-0440-y