Ranking, Trust, and Recommendation Systems: An Axiomatic Approach

نویسنده

  • Moshe Tennenholtz
چکیده

In the classical theory of social choice, a theory developed by game-theorists and theoretical economists, we consider a set of agents (voters) and a set of alternatives. Each agent ranks the alternatives, and the major aim is to find a good way to aggregate the individual preferences into a social preference. The major tool offered in this theory is the axiomatic approach: study properties (termed axioms) that characterize particular aggregation rules, and analyze whether particular desired properties can be simultaneously satisfied. In a ranking system [1] the set of voters and the set of alternatives coincide, e.g. they are both the pages in the web; in this case the links among pages are interpreted as votes: pages that page p links to are preferable by page p to pages it does not link to; the problem of preference aggregation becomes the problem of page ranking. Trust systems are personalized ranking systems [3] where the ranking is done for (and from the perspective of) each individual agent. Here the idea is to see how to rank agents from the perspective of a particular agent/user, based on the trust network generated by the votes. In a trust-based recommendation system the agents also express opinions about external topics, and a user who has not expressed an opinion should be recommended one based on the opinions of others and the trust network [6]. Hence, we get a sequence of very interesting settings, extending upon classical social choice, where the axiomatic approach can be used. On the practical side, ranking, reputation, recommendation, and trust systems have become essential ingredients of web-based multi-agent systems (e.g. [9, 13, 7, 14, 8]). These systems aggregate agents’ reviews of products and services, and of each other, into valuable information. Notable commercial examples include Amazon and E-Bay’s recommendation and reputation systems (e.g. [12]), Google’s page ranking system [11], and the Epinions web of trust/reputation system (e.g. [10]). Our work shows that an extremely powerful way for the study and design of such systems is the axiomatic approach, extending upon the classical theory of social choice. In this talk we discuss some representative results of our work [14, 1, 2, 4, 5, 3, 6].

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Consistent Continuous Trust-Based Recommendation Systems

The goal of a trust-based recommendation system is to generate personalized recommendations from known opinions and trust relationships. Prior work introduced the axiomatic approach to trust-based recommendation systems, but has been extremely limited by considering binary systems, while allowing these systems to be inconsistent. In this work we introduce an axiomatic approach to deal with cons...

متن کامل

Group Recommendations: Axioms, Impossibilities, and Random Walks

We introduce an axiomatic approach to group recommendations, in line of previous work on the axiomatic treatment of trust-based recommendation systems, ranking systems, and other foundational work on the axiomatic approach to internet mechanisms in social choice settings. In group recommendations we wish to recommend to a group of agents, consisting of both opinionated and undecided members, a ...

متن کامل

A Novel Trust Computation Method Based on User Ratings to Improve the Recommendation

Today, the trust has turned into one of the most beneficial solutions to improve recommender systems, especially in the collaborative filtering method. However, trust statements suffer from a number of shortcomings, including the trust statements sparsity, users' inability to express explicit trust for other users in most of the existing applications, etc. Thus to overcome these problems, this ...

متن کامل

Improving top-K recommendation with truster and trustee relationship in user trust network

Due to the data sparsity problem, social network information is often additionally used to improve the performance of recommender systems. While most existing works exploit social information to reduce the rating prediction error , e.g., RMSE, a few had aimed to improve the top-k ranking prediction accuracy . This paper proposes a novel top-k ranking oriented recommendation method, TRecSo , whi...

متن کامل

A Novel Approach to Propagating Distrust

Trust propagation is a fundamental topic of study in the theory and practice of rankingand recommendation systems on networks. The Page Rank [9] algorithm ranks web pagesby propagating trust throughout a network, and similar algorithms have been designed forrecommendation systems. How might one analogously propagate distrust as well? This is aquestion of practical importance and...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009