Recent results in artificial intelligence research are of prime interest in various fields of computer science; in particular we think information retrieval may benefit from significant advances in this approach. Expert systems seem to be valuable tools for components of information retrieval systems related to semantic inference. The query component is the one we consider in this paper. IOTA is the name of the resulting prototype presented here, which is our first step toward what we call an intelligent system for information retrieval. After explaining what we mean by this concept and presenting current studies in the field, the presentation of IOTA begins with the architecture problem, that is, how to put together a declarative component, such as an expert system, and a procedural component, such as an information retrieval system. Then we detail our proposed solution, which is based on a procedural expert system acting as the general scheduler of the entire query processing. The main steps of natural language query processing are then described according to the order in which they are processed, from the initial parsing of the query to the evaluation of the answer. The distinction between expert tasks and nonexpert tasks is emphasized. The paper ends with experimental results obtained from a technical corpus, and a conclusion about current and future developments.
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