Recent trends in automatic information retrieval

ABSTRACT

Substantial successes were achieved in the early years in automatic indexing and retrieval using single term indexing theories with term weight assignments based on frequency considerations. The development of more refined indexing systems using thesaurus aids and automatically constructed term association maps changed the retrieval effectiveness only slightly. The recent introduction of the relevance concept in the form of probabilistic retrieval models provided a firm basis for term weighting and document ranking practices. However, the probabilistic methods were not helpful in substantially enhancing the retrieval effectiveness. At the present time, attempts are made to add artificial intelligence concepts to the document retrieval environment in the form of fancy graphics interfaces, learning systems for query and document indexing and for collection searching, extended logic models relating documents and information requests, and analysis methods based on the use of semantic maps and other kinds of knowledge structures. Using the earlier developments and evaluation results as guidelines, an attempt is made to outline the information retrieval environment of the future and to assess the usefulness of some of the currently proposed search and retrieval methods.

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