Building Effective Queries In Natural Language Information Retrieval

In this paper we report on our natural language information retrieval (NLIR) project as related to the recently concluded 5th Text Retrieval Conference (TREC-5). The main thrust of this project is to use natural language processing techniques to enhance the effectiveness of full-text document retrieval. One of our goals was to demonstrate that robust if relatively shallow NLP can help to derive a better representation of text documents for statistical search. Recently, we have turned our attention away from text representation issues and more towards query development problems. While our NLIR system still performs extensive natural language processing in order to extract phrasal and other indexing terms, our focus has shifted to the problems of building effective search queries. Specifically, we are interested in query construction that uses words, sentences, and entire passages to expand initial topic specifications in an attempt to cover their various angles, aspects and contexts. B...

• Type: Conference
• Year: 1997
• Where: ANLP
• Authors: Tomek Strzalkowski, Fang Lin, Jose Perez Carballo, Jin Wang
• Keywords: ANLP 1997, Information Retrieval, Natural Language, Natural Language Processing