Bridging Information Retrieval and Databases

For bridging the gap between information retrieval (IR) and databases (DB), this article focuses on the logical view. We claim that IR should adopt three major concepts from DB, namely inference, vague predicates and expressive query languages. By regarding IR as uncertain inference, probabilistic versions of relational algebra and Datalog yield very powerful inference mechanisms for IR as well as allowing for more flexible systems. For dealing with various media and data types, vague predicates form a natural extension of text retrieval methods to attribute values, thus switching from propositional to predicate logic. A more expressive IR query language should support joins, be able to compute aggregated results, and allow for restructuring of the result objects.