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https://doi.org/10.2498/cit.2005.04.04

Simple Classification into Large Topic Ontology of Web Documents

Marko Grobelnik
Dunja Mladenić

Puni tekst: engleski, pdf (3 MB) str. 279-285 preuzimanja: 1.006* citiraj
APA 6th Edition
Grobelnik, M. i Mladenić, D. (2005). Simple Classification into Large Topic Ontology of Web Documents. Journal of computing and information technology, 13 (4), 279-285. https://doi.org/10.2498/cit.2005.04.04
MLA 8th Edition
Grobelnik, Marko i Dunja Mladenić. "Simple Classification into Large Topic Ontology of Web Documents." Journal of computing and information technology, vol. 13, br. 4, 2005, str. 279-285. https://doi.org/10.2498/cit.2005.04.04. Citirano 17.10.2019.
Chicago 17th Edition
Grobelnik, Marko i Dunja Mladenić. "Simple Classification into Large Topic Ontology of Web Documents." Journal of computing and information technology 13, br. 4 (2005): 279-285. https://doi.org/10.2498/cit.2005.04.04
Harvard
Grobelnik, M., i Mladenić, D. (2005). 'Simple Classification into Large Topic Ontology of Web Documents', Journal of computing and information technology, 13(4), str. 279-285. https://doi.org/10.2498/cit.2005.04.04
Vancouver
Grobelnik M, Mladenić D. Simple Classification into Large Topic Ontology of Web Documents. Journal of computing and information technology [Internet]. 2005 [pristupljeno 17.10.2019.];13(4):279-285. https://doi.org/10.2498/cit.2005.04.04
IEEE
M. Grobelnik i D. Mladenić, "Simple Classification into Large Topic Ontology of Web Documents", Journal of computing and information technology, vol.13, br. 4, str. 279-285, 2005. [Online]. https://doi.org/10.2498/cit.2005.04.04

Sažetak
The paper presents an approach to classifying Web documents into large topic ontology. The main emphasis is on having a simple approach appropriate for handling a large ontology and providing it with enriched data by including additional information on the Web page context obtained from the link structure of the Web. The context is generated from the in-coming and out-going links of the Web document we want to classify (the target document), meaning that for representing a document we use, not only text of the document itself, but also the text from the documents pointing to the target document, as well as the text from the documents the target document is pointing to. The idea is that providing enriched data is compensating for the simplicity of the approach while keeping it efficient and capable of handling large topic ontology.

Hrčak ID: 44678

URI
https://hrcak.srce.hr/44678

Posjeta: 1.138 *