Wong, Shik Kam Michael <br/><br/>
On modeling information retrieval with probabilistic inference 

<br/><br/>This article examines and extends the logical models of information retrieval in the context of probability theory. The fundamental notions of term weights and relevance are given probabilistic interpretations. A unified framework is developed for modeling the retrieval process with probabilistic inference. This new approach provides a common conceptual and mathematical basis for many retrieval models, such as the Boolean, fuzzy set, vector space, and conventional probabilistic models. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>INFORMATION STORAGE AND RETRIEVAL<br/>ARTIFICIAL INTELLIGENCE
<br/><br/><label>Universal Decimal Class. No.: </label>H004.414 INF