(invited paper) A new theoretical framework for information retrieval
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
Web Work: Information Seeking and Knowledge Work on the World Wide Web
Web Work: Information Seeking and Knowledge Work on the World Wide Web
OntoSeek: Content-Based Access to the Web
IEEE Intelligent Systems
Effective Reformulation of Boolean Queries with Concept Lattices
FQAS '98 Proceedings of the Third International Conference on Flexible Query Answering Systems
Integrating web service and semantic dialogue model for user models interoperability on the web
Journal of Intelligent Information Systems
Interactive ontology-based user knowledge acquisition: a case study
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Neighborhood systems and approximate retrieval
Information Sciences: an International Journal
Enhancing information retrieval using problem specific knowledge
PKAW'06 Proceedings of the 9th Pacific Rim Knowledge Acquisition international conference on Advances in Knowledge Acquisition and Management
Tuning user profiles based on analyzing dynamic preference in document retrieval systems
Multimedia Tools and Applications
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The main problem in traditional information retrieval systems is an ad-hoc modeling of the interaction with users, which results in a very low retrieval's precision regarding a user's information need. In this paper we discuss the knowledge level of that interaction, i.e. how an analysis of a user's knowledge gap (that initiated the retrieval process) can be used for designing an efficient interaction model, especially regarding the query refinement task. Moreover, we indicate the role that the background knowledge (i.e. a domain ontology) plays in that model. We present conceptually a comprehensive query refinement process that enables a user to fulfil his need in a gradual, step-by-step querying process.This research shows that, complementary to the mainstream IR research that is focused on the improvement of retrieval algorithms, there is a lot of playroom for the improvement of the retrieval process by better modelling user's working context, especially his task and the information need that causes that task.