A Bilingual Linking Service for the Web
The aim of Cross-Language Information Retrieval (CLIR) area is to address situations where a query is made in one language and the application is able to return documents in another. Many CLIR techniques attempt to translate the user’s query to the language of the target documents using translation dictionaries. However, these techniques have limitations in terms of lexical coverage of the dictionary adopted. For some applications, the dictionaries are manually edited towards improving the results — but this may require much effort to represent a large collection of information.
In this article we propose an infrastructure for defining automatically relationships between Web documents written in different languages. Our approach is based on the Latent Semantic Indexing Technique, which tries to overcome the problems common to the lexical approach due to words with multiple meanings and multiple words with the same meaning. LSI automatically organizes text objects into a semantic structure appropriate for matching . To support the identification of relationships among documents in different languages, the proposed infrastructure manipulates the stem portion of each word in order to index the corresponding Web documents when building the information space manipulated by LSI. To experiment this proposal, we studied the creation of links among news documents in English and Spanish in three different categories: entertainment, technology and world. The results were positive.
KeywordsLatent Semantic Indexing Storage Level Link Level Target Document Semantic Matrix
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