Multi-lingual Indexing Support for CLIR using Language Modeling

An indexing model is the heart of an Information Retrieval (IR) system. Data structures such as term based inverted indices have proved to be very effective for IR using vector space retrieval models. However, when functional aspects of such models were tested, it was soon felt that better relevance models were required to more accurately compute the relevance of a document towards a query. It was shown that language modeling approaches [[1]] in monolingual IR tasks improve the quality of search results in comparison with TFIDF [[2]] algorithm. The disadvantage of language modeling approaches when used in monolingual IR task as suggested in [[1]] is that they would require both the inverted index (term-todocument) and the forward index (document-to-term) to be able to compute the rank of document for a given query. This calls for an additional space and computation overhead when compared to inverted index models. Such a cost may be acceptable if the quality of search results are signi...

• Type: Journal
• Year: 2007
• Where: DEBU
• Authors: Prasad Pingali, Vasudeva Varma
• Keywords: DEBU 2007, Indexing Model, Inverted Index, Monolingual Ir Task