Learning in Intelligent Information Retrieval

Information retrieval (IR) systems are used for finding, within a large text database, those documents containing information needed by a user. The complex and poorly understood semantics of documents and user queries has made feedback and adaptation important characteristics of IR systems. In this paper we briefly survey previous research on machine learning in IR systems and discuss promising areas for future research at the intersection of these two fields. 1 Introduction The goal of information retrieval (IR) techniques is to find, within a large database of documents, those documents which satisfy a user information need. Typically the stored documents are composed of natural language text, though IR techniques have also been applied to databases of stored speech, images, computer source code, and other forms of information. In contrast to conventional database techniques, IR techniques are most useful when the semantics of the objects to be retrieved is unclear, and the relation..