CLUSTER-BASED RETRIEVAL USING LANGUAGE MODELING APPROACH: AN EXPLANATION
Gloria Virginia · 2011
Nowadays, one of the demands for computer system is capability to process text md natural language automatically. Consequently, the development of algolithms that €nabl€ computers to do such task has been one of the great challenges. Hence, any mbstantial progress in this domain will have a strong impact on numeious applicationi r.nging from information retrieval, information filtering, and intelligent agentiJo speech rcmgnition, machine translation, and human-machine interaction [ro]. Information retrieval is a task to retrieve relevant documents in response to a qurr-s b1'measuring similarity between documents in repositories and the query. In ryaen-t !'ears, the meaning of the term 'similar' between documents and query has been der oped. At first, a document is judged similar with the query merely bised on lexical nnrtching sf the word between documents and query. Now, the term 'similar' is expanded b 6e meening of the query. It means that the query is not necessarily expressed in the dment, to come up with thejudgment that a document is similar with the query. Tn_ this paper I'm going to explain how it can be done, that the query is not ttrPtssarib e>rpressed in the document, in text retrieval. But before it, I'll briefly describe re methods I used here. I'll close this paperby summarizing the explanation.