Beyond independent relevance: methods and evaluation metrics for subtopic retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Minimal document set retrieval
Proceedings of the 14th ACM international conference on Information and knowledge management
Text processing through Web services
Bioinformatics
Retrieval of Relevant Concepts from a Text Collection
Current Topics in Artificial Intelligence
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In this paper we present a novel approach for identifying and describing the possible subtopics that can be derived from the result set of a topic-based query. Subtopic descriptions rely on the conceptual indexing of the retrieved documents, which consists of mapping the document terms into concepts of an existing thesaurus (i.e. UMLS meta-thesaurus). Subtopic identification is performed by selecting highly probable concept bigrams whose support sets are homogeneous enough. The evaluation of the method has been carried out on a real biomedical example, which demonstrates both the effectiveness and usefulness of the proposed method.