A Cross-language Information Retrieval System Based On Linguistic And Statistical Approaches

Abstract

As the number of non-English documents that are available on the World Wide Web and in corporate repositories increases, the ability to quickly and effectively search and view documents across language boundaries will continue to grow in importance. Cross-language information retrieval techniques allow searchers access to a wider range of material without requiring specialized knowledge of the content or the languages in the database. We present in this paper a cross-language information retrieval system based on a deep linguistic analysis of documents and queries and a statistical model which assigns a weight to each word in the database according to discriminating power. A comparison tool is used to evaluate all possible intersections between queries and documents and order documents by their relevance.