DocumentCode :
3409399
Title :
Ontology-Supported Web Recommender for Scholar Information
Author :
Yang, Sheng-yuan ; Hsu, Chun-liang
Author_Institution :
Dept. of Comput. & Commun. Eng., St. John´´s Univ., Rome, Italy
Volume :
1
fYear :
2009
fDate :
12-14 Aug. 2009
Firstpage :
271
Lastpage :
276
Abstract :
In this quickly developed and shifting era of Internet, how to make use of webpage indexing structure or search engines which let information demanders fast and precisely search and extract out advantage information has become extremely important capability in users on the Web. This paper combined a data mining tool SPSS Clementine with the domain ontology to mine out usefully important information from huge datum, and then to employ Java to develop an information recommender for scholars--- Onto Recommender, in which can recommend suitably important information to scholars. The preliminary experiment outcomes proved the reliability and validation of the recommender achieving the regular-level outcomes of information recommendation, and accordingly proved the feasibility of the related techniques proposed in this paper.
Keywords :
Internet; Web sites; data mining; indexing; information filters; ontologies (artificial intelligence); Java; SPSS Clementine; Web page indexing structure; data mining; domain ontology; information recommendation; ontology-supported Web recommender; scholar information; search engines; Artificial neural networks; Data mining; Hybrid intelligent systems; Information analysis; Information systems; Internet; Java; Mathematical model; Ontologies; Statistical analysis; Ontology; SPSS Clementine; Web Recommender;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-0-7695-3745-0
Type :
conf
DOI :
10.1109/HIS.2009.61
Filename :
5254340
Link To Document :
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