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Search Engine: Approaches and Performance

Search Engine: Approaches and Performance

Eliana Campi, Gianluca Lorenzo
Copyright: © 2009 |Pages: 27
ISBN13: 9781605660349|ISBN10: 1605660345|ISBN13 Softcover: 9781616925512|EISBN13: 9781605660356
DOI: 10.4018/978-1-60566-034-9.ch004
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MLA

Campi, Eliana, and Gianluca Lorenzo. "Search Engine: Approaches and Performance." Semantic Knowledge Management: An Ontology-Based Framework, edited by Antonio Zilli, et al., IGI Global, 2009, pp. 74-100. https://doi.org/10.4018/978-1-60566-034-9.ch004

APA

Campi, E. & Lorenzo, G. (2009). Search Engine: Approaches and Performance. In A. Zilli, E. Damiani, P. Ceravolo, A. Corallo, & G. Elia (Eds.), Semantic Knowledge Management: An Ontology-Based Framework (pp. 74-100). IGI Global. https://doi.org/10.4018/978-1-60566-034-9.ch004

Chicago

Campi, Eliana, and Gianluca Lorenzo. "Search Engine: Approaches and Performance." In Semantic Knowledge Management: An Ontology-Based Framework, edited by Antonio Zilli, et al., 74-100. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-034-9.ch004

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Abstract

This chapter presents technologies and approaches for information retrieval in a knowledge base. We intend to show that the use of ontology for domain representation and knowledge search offers a more efficient approach for knowledge management. This approach focuses on the meaning of the word, thus becoming an important element in the building of the Semantic Web. The search based on both keywords and ontology allows more effective information retrieval exploiting the Semantic of the information in a variety of data. We present a method for taxonomy building, annotating, and searching documents with taxonomy concepts. We also describe our experience in the creation of an informal taxonomy, the automatic classification, and the validation of search results with traditional measures, such as precision, recall and f-measure.

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