Modelling Degrees of Item Interest for a General Database Query System.

摘要

Many databases support decision-making. Often this means choices between alternatives according to partly subjective or conflicting criteria. Database query languages are generally designed for precise, logical specification of the data of interest, and tend to be awkward in the aforementioned circumstances. Information retrieval research suggests several solutions, but there are obstacles to generalizing these ideas to most databases. To address this problem the authors propose a methodology for automatically deriving and monitoring degrees of interest among alternatives for a user of a database system. This includes a decision theory model of the value of information to the user, and inference mechanisms, based in part on ideas from artificial intelligence, that can tune the model to observed user behavior. This theory has important applications to improving efficiency and cooperativeness of the interface between a decision-maker and a database system. (Author)