An information retrieval system based on a user profile

In this era of information explosion, providing the right information to the right person within reasonable time duration is a very important goal for today's information retrieval (IR) systems. Due to the characteristics of retrieving methods, the conventional IR models often suffer from inaccurate and incomplete queries as well as inconsistent document relevance. Moreover, each user has his/ her own interpretation of the semantic meaning of query terms during the retrieving process. Thus, high accuracy of retrieved information is somewhat hard to achieve. However, accuracy can be improved by designing an IR model that can adapt to the diverse needs of an individual and can perform a personalized search. In this paper, an adaptive information retrieval system embedded in an intelligent feedback tuning mechanism is proposed to capture the personal notions of query terms. This mechanism together with a correlation table is used as a user profile to 'simulate' the user's notions of terms. This correlation table includes the degrees of semantic relevance (SR) and co-occurrence (CO) among terms. By using the personal profile during retrieval, the system can obtain a better match between the information needs and the retrieved results. It is also shown that the recall/precision rates for our system are approximately 91% and 81%, respectively, on average. (C) 2000 Elsevier Science Inc. All rights reserved.