Knowledge-based query expansion to support

scenario(s). We compared the proposed method with traditional statistical expansion that expands terms which are statistically correlated but not necessarily scenario specific. Our study on two standard testbeds shows that the knowledge-based method, by providing scenario-specific expansion, yields notable

In retrieving medical free text, users are often interested in answers relevant to certain scenarios, scenarios that correspond to common tasks in medical practice, e.g., “treatment ” or “diagnosis” of a disease. Consequently, the queries they pose are often scenario-specific, e.g., “lung cancer

Medical free-text queries often share the same scenario. A scenario represents a repeating task in healthcare. For example, a specific scenario is searching for treatment methods for a specific dis-ease, where “treatment ” is a term indicating the scenario. To support scenario-specific retrieval

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) User models for customization of retrieved information and result presentation. A digital medical library is currently being constructed using these technologies to provide customized information for the user. The technologies are general in nature and can provide custom and scenario-specific

Retrieval (CBIR) systems. Basically, these systems try to retrieve images similar to a user-defined specification or pattern (e.g., shape sketch, image example). Their goal is to support image retrieval based on content properties (e.g., shape, color, texture), usually encoded into feature vectors. One

outperform the non-overlap runs, and the heuristic which favours less specific over more specific result elements performs best. Importantly, we present results which show that, in a scenario where users prefer compound and non-overlapping answers to their queries, the choice of using a plain full

experiments show that—when each of the three systems is evaluated against different retrieval scenarios (such as different cases of relevance assessments, different topic categories and different choices of evaluation metrics)—the XML retrieval systems exhibit varying behaviour and the best performance can

retrieval for queries incorporating place names in applications employing online gazetteers and geographical thesauri. We then employ a set of experimental scenarios to investigate key issues affecting use of the associative (RT) thesaurus relationships in semantic distance measures. Previous work has noted