Towards a probabilistic modal logic for semantic-based information retrieval

摘要

Semantic-based approaches to Information Retrieval make a query evaluation similar to an inference process based on semantic relations. Semantic-based approaches find out hidden semantic relationships between a document and a query, but quantitative estimation of the correspondence between them is often empiric. On the other hand, probabilistic approaches usually consider only statistical relationships between terms. It is expected that improvement may be brought by integrating these two approaches. This paper demonstrates, using some particular probabilistic models which are strongly related to modal logic, that such an integration is feasible and natural. A new model is developed on the basis of an extended modal logic. It has the advantages of : (1) augmenting a semantic-based approach with a probabilistic measurement, and (2) augmenting a probabilistic approach with finer semantic relations than just statistical ones. It is shown that this model verifies most of the conditions for an absolute probability function.