Trust and Recommendations



Recommendation technologies and trust metrics constitute the two pillars of trust-enhanced recommender systems. We discuss and illustrate the basic trust concepts such as trust and distrust modeling, propagation and aggregation. These concepts are needed to fully grasp the rationale behind the trust-enhanced recommender techniques that are discussed in the central part of the chapter, which focuses on the application of trust metrics and their operators in recommender systems. We explain the benefits of using trust in recommender algorithms and give an overview of state-of-the-art approaches for trust-enhanced recommender systems. Furthermore, we explain the details of three well-known trust-based systems and provide a comparative analysis of their performance. We conclude with a discussion of some recent developments and open challenges, such as visualizing trust relationships in a recommender system, alleviating the cold start problem in a trust network of a recommender system, studying the effect of involving distrust in the recommendation process, and investigating the potential of other types of social relationships.


Root Mean Square Error Recommender System Trust Propagation Target User Trust Network 
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  1. 1.
    Abdul-Rahman, A., Hailes, S.: Supporting trust in virtual communities. In: Proc. of the 33rd Hawaii International Conference on System Sciences, pp. 1769-1777 (2000)Google Scholar
  2. 2.
    Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17, 734–749 (2005)CrossRefGoogle Scholar
  3. 3.
    Almenárez, F., Marín, A., Campo, C., García, C.: PTM: A pervasive trust management model for dynamic open environments. In: Proc. of the First Workshop on Pervasive Security, Privacy and Trust, in conjuntion with Mobiquitous (2004)Google Scholar
  4. 4.
    Arazy, O., Elsane, I., Shapira, B., Kumar, N.: Social relationships in recommender systems. In: Proc. of the 17th Workshop on Information Technologies & Systems (2007)Google Scholar
  5. 5.
    Arazy, O., Kumar, N., Shapira, B.: Improving social recommender systems. IT Professional May/June, 31–37 (2009)Google Scholar
  6. 6.
    Artz, D., Gil, Y.: A survey of trust in computer science and the semantic web. Journal of Web Semantics 5, 58–71 (2007)Google Scholar
  7. 7.
    Avesani, P., Massa, P., Tiella, R.: a trust-aware recommender system for ski mountaineering. International Journal for Infonomics (2005) 20 Trust and Recommendations 673Google Scholar
  8. 8.
    Cacioppo, J., Berntson, G.: Relationship between attitudes and evaluative space: a critical review, with emphasis on the separability of positive and negative substrates. Psychological Bulletin 115, 401–423 (1994)CrossRefGoogle Scholar
  9. 9.
    Constantinople, A.: An eriksonian measure of personality development in college students. Development Psychology 1, 357–372 (1969)CrossRefGoogle Scholar
  10. 10.
    Cofta, P.: Distrust. In: Proc. of the International Conference on Electronic Commerce, pp. 250-258 (2006)Google Scholar
  11. 11.
    De Cock, M., Pinheiro da Silva, P.: A many-valued representation and propagation of trust and distrust. In: Bloch, I., Petrosino, A., Tettamanzi, A. (eds.) Lecture Notes in Computer Science 3849, pp. 108-113 (2006)Google Scholar
  12. 12.
    Falcone, R., Pezzulo, G., Castelfranchi, C.: A fuzzy approach to a belief-based trust computation. In: Eder, J., Haav, H-M., Kalja, A., Penjam, J. (eds.) Lecture Notes in Artificial Intelligence 2631, pp. 73-86 (2003)Google Scholar
  13. 13.
    Gans, G., Jarke, M., Kethers, S., Lakemeyer, G.: Modeling the impact of trust and distrust in agent networks. In: Proc. of the ThirdWorkshop on Agent-oriented Information Systems, pp. 45-58 (2001)Google Scholar
  14. 14.
    Ginsberg, M.: Multi-valued logics: A uniform approach to reasoning in artificial intelligence. Computational Intelligence 4, 265–316 (1988)Google Scholar
  15. 15.
    Golbeck, J.: Computing and applying trust in web-based social networks. PhD thesis (2005)Google Scholar
  16. 16.
    Golbeck, J.: Generating predictive movie ratings from trust in social networks. In: Stølen, K, Winsborough, W.H., Martinelli, F., Massacci, F. (eds.) Lecture Notes in Computer Science 3986, pp. 93-104 (2006)Google Scholar
  17. 17.
    Golbeck, J.: Computing with Social Trust. Springer, London (2009)Google Scholar
  18. 18.
    Golbeck, J., Mannes, A.: Using trust and provenance for content filtering on the semantic web. In: Proc. of the WWW06 Models of Trust for the Web Workshop (2006)Google Scholar
  19. 19.
    Golbeck, J., Parsia, B., Hendler, J.: Trust networks on the semantic web. In: Klusch, M., Omicini, A., Ossowski, S., Laamanen, H. (eds.) Lecture Notes in Artificial Intelligence 2782, pp. 238-249 (2003)Google Scholar
  20. 20.
    Guha, R.: Open rating systems. Technical report, Stanford Knowledge Systems Laboratory (2003)Google Scholar
  21. 21.
    Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proc. of the World Wide Web Conference, pp. 403-412 (2004)Google Scholar
  22. 22.
    Herlocker, J., Konstan, J., Terveen, L., Riedl, J.: Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems 22, 5–53 (2004)CrossRefGoogle Scholar
  23. 23.
    Hess, C., Schiedler, C.: Trust-based recommendations for documents. AI Communications 21, 145–153 (2008)zbMATHMathSciNetGoogle Scholar
  24. 24.
    Jøsang, A.: A logic for uncertain probabilities. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 9, 279-311 (2001).MathSciNetGoogle Scholar
  25. 25.
    Jøsang, A., Knapskog, S.: A metric for trusted systems. In: Proc. of the National Computer Security Conference, pp. 16-29 (1998)Google Scholar
  26. 26.
    Jøsang, A., Gray, E., Kinateder, M.: Simplification and analysis of transitive trust networks. Web Intelligence and Agent Systems 4, 139–161 (2006)Google Scholar
  27. 27.
    Jøsang, A., Marsh, S., Pope, S.: Exploring different types of trust propagation. In: Stølen, K, Winsborough, W.H., Martinelli, F., Massacci, F. (eds.) Lecture Notes in Computer Science 3986, pp. 179-192 (2006)Google Scholar
  28. 28.
    Kamvar, S., Schlosser, M., Garcia-Molina, H.: The eigentrust algorithm for reputation management in P2P networks. In: Proc. of the World Wide Web Conference, pp. 640-651 (2003)Google Scholar
  29. 29.
    Klir, G., Yuan, B.: Fuzzy sets and systems: theory and applications. Prentice Hall PTR, New Jersey (1995)Google Scholar
  30. 30.
    Lathia, N., Hailes, S., Capra, L.: Trust-based collaborative filtering. In: Karabulut, Y., Mitchell, J., Herrmann, P., Damsgaard Jensen, C. (eds.) IFIP International Federation for Information Processing 263, 119–134 (2008)Google Scholar
  31. 31.
    Lesani, M., Bagheri, S.: Applying and inferring fuzzy trust in semantic web social networks. In: Kodé, M.T., Lemire, D. (eds.) Semantic Web and Beyond 2, pp. 23-43 (2006) 674 Patricia Victor, Martine De Cock, and Chris CornelisGoogle Scholar
  32. 32.
    Levien, R.: Attack-resistant trust metrics. In: Golbeck, J. (ed.) Computing With Social Trust, pp. 121-132 (2009)Google Scholar
  33. 33.
    Lewicki, R., McAllister, D., Bies, R.: Trust and distrust: new relationships and realities. Academy of Management Review 23, 438–458 (1998)CrossRefGoogle Scholar
  34. 34.
    Marsh, S., Briggs, P.: Examining trust, forgiveness and regret as computational concepts. In: Golbeck, J. (ed.) Computing With Social Trust, pp. 9-43 (2009)Google Scholar
  35. 35.
    Massa, P., Avesani, P.: Trust-aware collaborative filtering for recommender systems. In: Proc. of the Federated International Conference On The Move to Meaningful Internet, pp. 492-508 (2004)Google Scholar
  36. 36.
    Massa, P., Avesani, P.: Trust-aware recommender systems. In: Proc. of ACM Recommender Systems, pp. 17-24 (2007)Google Scholar
  37. 37.
    Massa, P., Avesani, P.: Trust metrics in recommender systems. In: Golbeck, J. (ed.) Computing with Social Trust, pp. 259-285 (2009)Google Scholar
  38. 38.
    Massa, P., Avesani, P.: Trust metrics on controversial users: balancing between tyranny of the majority and echo chambers. International Journal on SemanticWeb and Information Systems 3, 39–64 (2007)Google Scholar
  39. 39.
    Massa, P., Bhattacharjee, B.: Using trust in recommender systems: an experimental analysis. In: Jensen, C., Poslad, S., Dimitrakos, T. (eds.) Lecture Notes in Computer Science 2995, pp. 221-235 (2004)Google Scholar
  40. 40.
    Mayer, R., Davis, J., Schoorman, D.: An integrative model of organizational trust. The Academy of Management Review 20, 709–734 (1995)CrossRefGoogle Scholar
  41. 41.
    McAllister, D.: Affect- and cognition-based trust as foundations for interpersonal cooperation in organizations. The Academy of Management Journal 38, 24–59 (1995)CrossRefGoogle Scholar
  42. 42.
    Moskovitch, R., Elovici, Y., Rokach, L., Detection of unknown computer worms based on behavioral classification of the host, Computational Statistics and Data Analysis, 52(9): 4544– 4566 (2008)zbMATHCrossRefMathSciNetGoogle Scholar
  43. 43.
    Mui, L., Mohtashemi, M., Halberstadt, A.: A computational model of trust and reputation. In: Proc. of the 35th Hawaii International Conference on System Sciences, pp. 2431-2439 (2002)Google Scholar
  44. 44.
    Noh, S.: Calculating trust using aggregation rules in social networks. In: Xiao, B., Yang, L., Ma, J., Muller-Schloer, C., Hua, Y. (eds.) Lecture Notes in Computer Science 4610, pp. 361-371 (2007)Google Scholar
  45. 45.
    O’Donovan, J.: Capturing trust in social web applications. In: Golbeck, J. (ed.) Computing With Social Trust, pp. 213-257 (2009)Google Scholar
  46. 46.
    O’Donovan, J., Smyth, B.: Trust in recommender systems. In: Proc. of the 10th International Conference on Intelligent User Interfaces, pp. 167-174 (2005)Google Scholar
  47. 47.
    O’Donovan, J., Smyth, B.: Mining trust values from recommendation errors. International Journal on Artificial Intelligence Tools 15, 945–962 (2006)CrossRefGoogle Scholar
  48. 48.
    O’Reilly, T.: What is web 2.0. Available at (2005)
  49. 49.
    Papagelis, M., Plexousakis, D., Kutsuras, T.: Alleviating the sparsity problem of collaborative filtering using trust inferences. In: Herrmann, P., Issarny, V., Shiu, S. (eds.) Lecture Notes in Computer Science 3477, pp. 224-239 (2005)CrossRefGoogle Scholar
  50. 50.
    Petty, R., Wegener, D., Fabrigar, L.: Attitudes and attitude change. Annual Review of Psychology 48, 609–647 (1997)CrossRefGoogle Scholar
  51. 51.
    Pitsilis, G., Marshall, L.: A trust-enabled P2P recommender system. In: Proc. of the 15th Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises, pp. 59- 64 (2006)Google Scholar
  52. 52.
    Priester, J., Petty, R.: The gradual threshold model of ambivalence: relating the positive and negative bases of attitudes to subjective ambivalence. Journal of Personality and Social Psychology 71, 431–449 (1996)CrossRefGoogle Scholar
  53. 53.
    Resnick, P., Iacovou, N., Suchak, M., Bergstorm, P., Riedl, J.: Grouplens: An open architecture for collaborative filtering of netnews. In: Proc. of Computer Supported Cooperative Work, pp. 175-186 (1994)Google Scholar
  54. 54.
    Resnick, P., Varian, H.R.: Recommender systems. Communications of the ACM 40, 56–58 (1997)CrossRefGoogle Scholar
  55. 55.
    Richardson, M., Agrawal, R., Domingos, P.: Trust management for the semantic web. In: Proc. of the Second International Semantic Web Conference, pp. 351-368 (2003)Google Scholar
  56. 56.
    Schafer, J., Konstan, J., Riedl, J.: E-commerce recommendation applications. Data Mining and Knowledge Discovery 5, 115–153 (2001)zbMATHCrossRefGoogle Scholar
  57. 57.
    Sinha, R., Swearingen, K.: Comparing recommendations made by online systems and friends. Proc. of the DELOS-NSFWorkshop on Personalisation and Recommender Systems in Digital Libraries (2001)Google Scholar
  58. 58.
    Swearingen, K., Sinha, R.: Beyond algorithms: an HCI perspective on recommender systems. Proc. of SIGIR Workshop on Recommender Systems (2001)Google Scholar
  59. 59.
    Tang, W., Ma, Y., Chen, Z.: Managing trust in peer-to-peer networks. Journal of Digital Information Management 3, 58–63 (2005)Google Scholar
  60. 60.
    Victor, P., De Cock, M., Cornelis, C., Pinheiro da Silva, P.: Towards a provenance-preserving trust model in agent networks. In: Proc. of Models of Trust for theWeb WWW2006Workshop (2006)Google Scholar
  61. 61.
    Victor, P., Cornelis, C., De Cock, M., Teredesai, A.M.: Key figure impact in trust-enhanced recommender systems. AI Communications 21, 127–143 (2008)zbMATHMathSciNetGoogle Scholar
  62. 62.
    Victor, P., Cornelis, C., De Cock, M., Pinheiro da Silva, P.: Gradual trust and distrust in recommender systems. Fuzzy Sets and Systems 160 1367–1382 (2009)zbMATHCrossRefGoogle Scholar
  63. 63.
    Victor, P., Cornelis, C., De Cock, M., Teredesai, A.M.: A comparative analysis of trustenhanced recommenders for controversial items. In: Proc. of the International AAI Conference on Weblogs and Social Media, pp. 342-345 (2009)Google Scholar
  64. 64.
    Victor, P., Cornelis, C., De Cock, M., Teredesai, A.M.: Trust- and distrust-based recommendations for controversial reviews. IEEE Intelligent Systems, in press.Google Scholar
  65. 65.
    Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)zbMATHCrossRefMathSciNetGoogle Scholar
  66. 66.
    Zaihrayeu, I., Pinheiro da Silva, P., McGuinness, D.: IWTrust: Improving user trust in answers from the web. In: Proc. of the Third International Conference On Trust Management, pp. 384- 392 (2005)Google Scholar
  67. 67.
    Zhang, S., Ouyang, Y., Ford, J., Makedon, F.: Analysis of a low-dimensional linear model under recommendation attacks. In: Proc. of the International ACM SIGIR Conference, pp. 517-524 (2006)Google Scholar
  68. 68.
    Ziegler, C., Lausen, G.: Propagation models for trust and distrust in social networks. Information System Frontiers 7, 337–358 (2005)CrossRefGoogle Scholar
  69. 69.
    Ziegler, C., Golbeck, J.: Investigating correlations of trust and interest similarity - Do birds of a feather really flock together?. Decision Support Systems 43, 460–475 (2007)CrossRefGoogle Scholar

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© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Dept. of Applied Mathematics and Computer ScienceGhent UniversityGentBelgium
  2. 2.Institute of Technology, University of Washington TacomaTacomaUSA

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