Social Relation Based Search Refinement: Let Your Friends Help You!

@inproceedings{Ren2010SocialRB,
  title={Social Relation Based Search Refinement: Let Your Friends Help You!},
  author={X. Ren and Yi Zeng and Yulin Qin and N. Zhong and Z. Huang and Y. Wang and C. Wang},
  booktitle={AMT},
  year={2010}
}
  • X. Ren, Yi Zeng, +4 authors C. Wang
  • Published in AMT 2010
  • Computer Science
  • One of the major problems for search at Web scale is that the search results on the large scale data might be huge and the users have to browse to find the most relevant ones. Plus, due to the reason for the context, user requirement may diverse although the input query may be the same. In this paper, we try to achieve scalability for Web search through social relation diversity of different users. Namely, we utilize one of the major context for users, social relations, to help refining the… CONTINUE READING

    Figures, Tables, and Topics from this paper.

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 13 REFERENCES
    GroupLens: an open architecture for collaborative filtering of netnews
    • 5,400
    • PDF
    Unifying Web-Scale Search and Reasoning from the Viewpoint of Granularity
    • 9
    • PDF
    Research Interests: Their Dynamics, Structures and Applications in Web Search Refinement
    • 5
    • PDF
    DBLP-SSE: A DBLP Search Support Engine
    • 21
    • PDF
    The Google Similarity Distance
    • 1,723
    • Highly Influential
    • PDF
    The emerging web of linked data
    • 246
    Formal models for expert finding in enterprise corpora
    • 633
    • PDF
    On six degrees of separation in DBLP-DB and more
    • 149
    • PDF
    Expert-Finding Systems for Organizations: Problem and Domain Analysis and the DEMOIR Approach
    • 268
    • PDF
    Sharing Expertise: Beyond Knowledge Management
    • 339
    • PDF