Ontology-Based Information Retrieval Model for the Semantic Web. Feng, S., Ming, Z., Dong, X., Hui, L., & Ning, X. e-Technology, e-Commerce, and e-Services, IEEE International Conference on, 2005.
Ontology-Based Information Retrieval Model for the Semantic Web [link]Paper  doi  abstract   bibtex   
In this paper, we describe ontology-based information retrieval model for the Semantic Web. By using OWL Lite as standard ontology language, which is a suitable tradeoff between expressivity of knowledge and complexity of reasoning problems, ontology is generated through translating and integrating domain ontologies. The terms defined in ontology are used as metadata to markup the Web's content; these semantic markups are semantic index terms for information retrieval. We can obtain the equivalent classes of semantic index terms by using description logic reasoner. The logical views of documents and user information needs, generated in terms of the equivalent classes of semantic index terms, can represent documents and user information needs well, so the performance of information retrieval can be improved effectively when suitable ranking function is chosen. The practicability of this model is discussed. Finally, the related works are introduced, and the conclusion and our future work are given.
@article{ feng_ontology-based_2005,
  title = {Ontology-Based Information Retrieval Model for the Semantic Web},
  url = {http://dx.doi.org/10.1109/EEE.2005.98},
  doi = {10.1109/EEE.2005.98},
  abstract = {In this paper, we describe ontology-based information retrieval model for the Semantic Web. By using {OWL} Lite as standard ontology language, which is a suitable tradeoff between expressivity of knowledge and complexity of reasoning problems, ontology is generated through translating and integrating domain ontologies. The terms defined in ontology are used as metadata to markup the Web's content; these semantic markups are semantic index terms for information retrieval. We can obtain the equivalent classes of semantic index terms by using description logic reasoner. The logical views of documents and user information needs, generated in terms of the equivalent classes of semantic index terms, can represent documents and user information needs well, so the performance of information retrieval can be improved effectively when suitable ranking function is chosen. The practicability of this model is discussed. Finally, the related works are introduced, and the conclusion and our future work are given.},
  journal = {e-Technology, e-Commerce, and e-Services, {IEEE} International Conference on},
  author = {Feng, Song and Ming, Zhang and Dong, Xiao and Hui, Li and Ning, Xu},
  year = {2005},
  keywords = {information_retrieval, ontologies},
  pages = {152--155}
}

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