WordNet: a lexical database for English
Communications of the ACM
Content-based text querying with ontological descriptors
Data & Knowledge Engineering - NLDB2002
Using a semantic concordance for sense identification
HLT '94 Proceedings of the workshop on Human Language Technology
Database summarization using fuzzy ISA hierarchies
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A fuzzy k-modes algorithm for clustering categorical data
IEEE Transactions on Fuzzy Systems
A Multicriteria Approach to Data Summarization Using Concept Ontologies
IEEE Transactions on Fuzzy Systems
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One approach to deal with large query answers or large collections of text documents is to impose some kind of structure to the collection for instance by a grouping into clusters of somehow related or close items. Another approach is to consider characteristics of the collection for instance by considering central and/or as a frequent keywords possibly taken from a background vocabulary or a more thorough structuring of background knowledge, like taxonomies or ontologies. In this paper we present a preliminary approach to combine these directions. More specifically we address an approach where conceptual summaries can be provided as answers to queries or survey over a document collection. The general idea is to apply a background knowledge ontology in connection with a combined clustering and generalization of keywords. Preliminary experiments with Wordnet as background knowledge and excerpts from Semcor as data are presented and discussed.