Visit www.benjamins.com

Determining semantic equivalence of terms in information retrieval

MyBook is a cheap paperback edition of the original book and will be sold at uniform, low price.
This Chapter is currently unavailable for purchase.
Abstract

An important issue in Information Retrieval is determining the semantic equivalence between terms in a query and terms in a document. We propose an approach based on context distance and morphology. Context distance is a measure we use to assess the closeness of word meanings. This context distance model compares the similarity of the contexts where a word appears, using the local document information and the global lexical co-occurrence information derived from the entire set of documents to be retrieved. We integrate this context distance model with morphological analysis in determining semantic equivalence of terms so that the two operations can enhance each other. Using the standard vector-space model, we evaluated the proposed method on a subset of TREC-4 corpus (AP88 and AP90 collection, 158,240 documents, 49 queries). Results show that this method improves the 11-point average precision by 8.6%.

References

/content/books/9789027298164-13jin
dcterms_subject,pub_keyword
6
3
Loading
This is a required field
Please enter a valid email address