The use of phrases and structured queries in information retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
WordNet: a lexical database for English
Communications of the ACM
Semantics of quotient operators in fuzzy relational databases
Fuzzy Sets and Systems
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Information Processing and Management: an International Journal - The sixth text REtrieval conference (TREC-6)
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Generating, integrating, and activating thesauri for concept-based document retrieval
IEEE Expert: Intelligent Systems and Their Applications
OntoSeek: Content-Based Access to the Web
IEEE Intelligent Systems
Semantic cores for representing documents in IR
Proceedings of the 2005 ACM symposium on Applied computing
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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The paper proposes an approach to information retrieval based on the use of a structure (ontology) that is used both for document (resp. query) indexing and query evaluating. The conceptual structure is hierarchical and it encodes the knowledge of the topical domain of the considered documents. It is formally represented as a tree. In this approach, the query evaluation is based on the comparison of minimal sub-trees containing the two sets of nodes corresponding to the concepts expressed in the document and the query respectively. The comparison is based on the computation of a degree of inclusion of the query tree in the document tree. Experiments undertaken on MuchMore benchmark showed the effectiveness of the approach.