@article{castells_adaptation_2007,
  abstract = {Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontology-based knowledge bases to improve search over large document repositories. In our view of Information Retrieval on the Semantic Web, a search engine returns documents rather than, or in addition to, exact values in response to user queries. For this purpose, our approach includes an ontology-based scheme for the semiautomatic annotation of documents and a retrieval system. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with conventional keyword-based retrieval to achieve tolerance to knowledge base incompleteness. Experiments are shown where our approach is tested on corpora of significant scale, showing clear improvements with respect to keyword-based search.},
  added-at = {2009-03-16T20:30:03.000+0100},
  author = {Castells and Fernandez, M and Vallet, D},
  biburl = {http://www.bibsonomy.org/bibtex/28dc7f08659eb792e26e902885f36c7d7/davidlan},
  interhash = {45ed1e91a3c32d82055e938f8d323d30},
  intrahash = {8dc7f08659eb792e26e902885f36c7d7},
  issn = {1041-4347},
  journal = {{IEEE} {TRANSACTIONS} {ON} {KNOWLEDGE} {AND} {DATA} {ENGINEERING}},
  keywords = {ir ontologies semantic vector-space},
  month = {February},
  number = 2,
  pages = {261--272},
  timestamp = {2009-03-16T20:30:03.000+0100},
  title = {An adaptation of the vector-space model for ontology-based information retrieval},
  url = {http://apps.isiknowledge.com.proxy.library.ucsb.edu:2048/full_record.do?product=WOS&colname=WOS&search_mode=CitingArticles&qid=53&SID=4DdmdNEJmOggp6O6N3k&page=2&doc=15},
  volume = 19,
  year = 2007
}