Intelligent information systems

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Abstract
Natural language processing techniques developed for Artificial Intelligence programs can aid in constructing powerful information retrieval systems in at least two areas. Automatic construction of new concepts allows a large body of information to be organized compactly and in a manner that allows a wide range of queries to be answered. Also, using natural language processing techniques to conceptually analyze the documents being stored in a system greatly expands the effectiveness of queries about given pieces of text. However, only robust conceptual analysis methods are adequate for such systems. This paper will discuss approaches to both concept learning, in the form of Generalization-Based Memory, and powerful, robust text processing achieved by Memory-Based Understanding. These techniques have been implemented in the computer systems IPP, a program that reads, remembers and generalizes from news stories about terrorism, and RESEARCHER, currently in the prototype stage, that operates in a very different domain (technical texts, patent abstracts in particular).

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