JOURNAL ARTICLE

Using social annotations to enhance document representation for personalized search

Abstract

In this paper, we present a contribution to IR modeling. We propose an approach that computes on the fly, a Personalized Social Document Representation (PSDR) of each document per user based on his social activities. The PSDRs are used to rank documents with respect to a query. This approach has been intensively evaluated on a large public dataset, showing significant benefits for personalized search.

Keywords:
Computer science Personalized search Information retrieval Representation (politics) Rank (graph theory) World Wide Web Search engine

Metrics

24
Cited By
8.17
FWCI (Field Weighted Citation Impact)
16
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Recommender Systems and Techniques
Physical Sciences →  Computer Science →  Information Systems
Information Retrieval and Search Behavior
Physical Sciences →  Computer Science →  Information Systems
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
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