DocumentCode :
1784015
Title :
Sorting Topic Specific Web Pages Based on Ontology Knowledge
Author :
Qiuxia Song ; Jin Liu ; Ming Ni ; Liang Chen ; Jialiang Shen
Author_Institution :
Coll. of Inf. Eng., Shanghai Maritime Univ., Shanghai, China
fYear :
2014
fDate :
27-29 Aug. 2014
Firstpage :
880
Lastpage :
883
Abstract :
Due to the independence of the domain knowledge, general search engine has "theme drift" problem in the search of domain knowledge. Topic specific search engine offers a faster, and more accurate web resources retrieval service, and a good web page sorting algorithm can improve user experience. In this paper, we proposed a new sorting algorithm for topic specific search engine based on ontology knowledge, by using the hierarchy relationship of ontology knowledge to judge the importance of the words in web pages, and sorted web pages with the obtained cumulated score. To verify the effectiveness of the proposed algorithm, we set up an evaluation system and compared it with traditional sorting algorithm based on TF-IDF. The experimental results show that our algorithm is more accurate and have better user experience.
Keywords :
Web sites; information retrieval; ontologies (artificial intelligence); sorting; TF-IDF; Web resource retrieval service; hierarchy relationship; ontology knowledge; theme drift problem; topic specific Web page sorting algorithm; topic specific search engine; user experience; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Ontologies; Search engines; Sorting; Web pages; Topic specific search engine; ontology; topic relevance; web page sorting algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2014 Tenth International Conference on
Conference_Location :
Kitakyushu
Print_ISBN :
978-1-4799-5389-9
Type :
conf
DOI :
10.1109/IIH-MSP.2014.222
Filename :
6998468
Link To Document :
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