Toward the design of a methodology to predict relevance through multiple sources of evidence

Textual queries, often short and ambiguous, can be insufficient when describing complex user information needs. Since users are reluctant or unable to provide long or precise descriptions, a possible solution to the low Information Retrieval (IR) system relevance prediction capability is to exploit diverse sources of evidence which are available during the search process. One of the open problems of the combination of diverse sources of evidence is the need of a uniform formalism which seamlessly describes the sources and the document ranking function within a single model. To this end, this paper discusses an IR view which explicitly considers other sources in addition to the information need and the document, and proposes a methodology to exploit them to support feedback. The IR view is described using the Entity-Relationship (ER) model which allows us to view the sources as properties of entities -- e.g. of the entity information need, document, or user -- or of their relationships.