Christian Fluhr

About reformulation in full-text IRS

Abstract In this paper, we analyze different kinds of reformulation used in Information Retrieval systems where full-text databases are accessed through natural language queries. These reformulations are tested separately on large actual full-text databases managed by the SPIRIT system (Syntactic and Probabilistic Indexing and Retrieval of Information in Texts). Some modifications on the weighted comparison are being tested for taking reformulation into account. At the end, an expert system solution is proposed as a reformulation strategy manager.

Toward a common semantics between media and languages

For a computer to recognize objects, persons, situations or actions in multimedia, it needs to have learned models of each thing beforehand. For the moment, no large, general collection of training examples exists for the wide variety of things that we would want to automatically recognize in multimedia, video and still images. We believe that the WWW and current technology can allow us to automatically build such a resource. This paper describes a methodology for the construction of a grounded, general purpose, multimedia ontology that is instantiated through web processing. In this hierarchically organized ontology, concepts corresponding to concrete objects, persons, situations and actions are linked with still images, videos and sounds that represent exemplars of each concept. These examples are necessary resources for computing discriminating signatures for the recognition of the concepts in still images or videos. Since images retrieved using existing image search engines contain much noise hand are not always representative, we also present here our methodology for finding good representative for each concept.