Enriching wordnet to index and retrieve semantic information.

The work illustrated in this paper is part of the DART search engine. Its main goal is to index and retrieve information both in a generic and in a specific context where documents can be mapped or not on ontologies, vocabularies and thesauri. To achieve this goal, a semantic analysis process on structured and unstructured parts of documents is performed. The unstructured parts need a linguistic analysis and a semantic interpretation performed by means of Natural Language Processing (NLP) techniques, while the structured parts need a specific parser. Semantic keys are extracted from documents starting from the semantic net of WordNet and enriching it of new nodes, links and attributes.

@TechReport{ADT09a,
  author       = {Angioni, M. and Demontis, R. and Tuveri, F.},
  title        = {Enriching wordnet to index and retrieve semantic information.},
  institution  = {CRS4, Center for Advanced Studies, Research and Development in Sardinia},
  number       = {09/14},
  month        = {january},
  year         = {2009},
  address      = {Cagliari, Italy},
  type         = {techreport},
  keywords     = {Search, Ontologies, NLP},
  url          = {https://publications.crs4.it/pubdocs/2009/ADT09a},
}