Representing information need with semantic relations

Information retrieval systems can be made more effective by providing more expressive query languages for users to specify their information need. This paper argues that this can be achieved through the use of semantic relations as query primitives, and describes a new technique for extracting semantic relations from an online dictionary. In contrast to existing research, this technique involves the composition of basic semantic relations, a process akin to constrained spreading activation in semantic networks. The proposed technique is evaluated in the context of extracting semantic relations that are relevant for retrieval from a corpus of pictures.