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Trust, authority and popularity in social information retrieval
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Conference on Information and Knowledge Management archive
Proceeding of the 17th ACM conference on Information and knowledge management table of contents
Napa Valley, California, USA
POSTER SESSION: Poster session 3/information retrieval table of contents
Pages 1503-1504  
Year of Publication: 2008
ISBN:978-1-59593-991-3
Authors
Gabriella Kazai  Microsoft Research, Cambridge, United Kingdom
Natasa Milic-Frayling  Microsoft Research, Cambridge, United Kingdom
Sponsors
ACM: Association for Computing Machinery
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

We present a social information retrieval (SIR) model comprising the social network of actors (e.g., authors, publishers, consumers), the graph representing relations in data (e.g., publications), and the links between the social and data network that reflect activities in the network such as search, authoring, annotation, etc. Building on this hybrid network, we describe relevance in terms of the trust propagated through the network and rendered onto a given item. In particular, relevance is a function of the approval votes from the associated sub-graph and the reputation of the sub-graph nodes. We explore a model that differentiates between approval from actors who are perceived authorities by the user and the approval by a wider community, representing the popular opinion.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Gabriella Kazai: colleagues
Natasa Milic-Frayling: colleagues