A content-based approach for document representation and retrieval

ABSTRACT

In the last few years, the problem of defining efficient techniques for knowledge representation is becoming a challenging topic in both academic and industrial community. The large amount of available data creates several problems in terms of information overload. In this framework, we assume that new approaches for knowledge definition and representation may be useful, in particular the ones based on the concept of ontology. In this paper we propose a suitable model for knowledge representation purposes using linguistic concepts and properties. We implement our model in a system which, using novel techniques and metrics, analyzes documents from a semantic point of view using as context of interest the Web. Experiments are performed on a test set built using a directory service to have information about analyzed documents. The obtained results compared with other similar systems show an effective improvement.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Dictionaries

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Thesauruses; Linguistic processing
      H.3.3 Information Search and Retrieval

General Terms:
Algorithms, Experimentation, Performance

Keywords:
WordNet, ontologies, semantic relatedness metrics