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 [BibTeX] [Marc21]
Inferring Document Similarity from Hyper-links
Type of publication: Idiap-RR
Citation: grangier:2005:idiap-05-21
Number: Idiap-RR-21-2005
Year: 2005
Institution: IDIAP
Abstract: Assessing semantic similarity between text documents is a crucial aspect in Information Retrieval systems. In this paper, we propose a technique to derive a similarity measure from hyper-link information. As linked documents are generally semantically closer than unlinked documents, we use a training corpus with hyper-links to infer a function $a,b \to sim(a,b)$ that assigns a higher value to linked documents than to unlinked ones. Two sets of experiments on different corpora show that this function compares favorably with {\em OKAPI} matching on document retrieval tasks.
Userfields: ipdmembership={speech},
Keywords:
Projects Idiap
Authors Grangier, David
Bengio, Samy
Crossref by grangier:2005:nips_workshop
grangier:2005:cikm
Added by: [UNK]
Total mark: 0
Attachments
  • grangier-rr-05-21.pdf
  • grangier-rr-05-21.ps.gz
Notes