From del.icio.us to x.qui.site: recommendations in social tagging sites

ABSTRACT

We present X.QUI.SITE, a scalable system for managing recommendations for social tagging sites like del.icio.us. seamlessly incorporates various user behaviors into the recommendations and aims to recommend not only items of interest, but also other relevant information like interesting people and/or topics. Explanations are also provided so that users can obtain a better understanding of the recommendations and decide which recommendations to pursue further. We discuss the technical challenges involved in characterizing different user behaviors and in efficiently computing recommendation explanations.

REFERENCES

• 1: Ronald Fagin , Amnon Lotem , Moni Naor, Optimal aggregation algorithms for middleware, Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, p.102-113, May 2001, Santa Barbara, California, United States [doi>10.1145/375551.375567]
• 2: J. A. Konstan. Introduction to recommender systems. In SIGIR07: Proceedings of the 30th Annual International ACM SIGIR Conference, 2007.
• 3: J. Stoyanovich, S. Amer-Yahia, C. Marlow, and C. Yu. A study of the benefit of leveraging tagging behavior to model users' interests in del.icio.us. In AAAI-SIP, 2008.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.3 Group and Organization Interfaces
          Subjects: Web-based interaction

General Terms:
Algorithms, Human Factors

Keywords:
collaborative tagging sites, recommendation explanation, recommender systems