DocumentCode
234810
Title
Focused crawling with ontology using semi-automatic tagging for relevancy
Author
Gaur, Risha ; Sharma, D.K.
Author_Institution
Comput. Eng. & Applic., GLA Univ., Mathura, India
fYear
2014
fDate
7-9 Aug. 2014
Firstpage
501
Lastpage
506
Abstract
World Wide Web (WWW) is considered to be the most important source of information now a days but it´s difficult to decide which resources are useful and which are more important. Thus to make a specific part of web leading to only the required resources is searched for. The focused crawler crawl a specific part of the web to retrieve the relevant resources. Here in this paper the focused crawler is applied on social network having ontology dependent tags. The ontology here is also used in preprocessing step of focused crawlers to make the search more specific by expanding the search topic semantically. Further the relevancy of manually tagged and semi-automatically tagged resource is compared. Then finally the harvest rate is evaluated for focused crawlers with ontology and using semi-automatic tagging to check for the relevance.
Keywords
Internet; ontologies (artificial intelligence); relevance feedback; search engines; social networking (online); WWW; World Wide Web; focused crawling; ontology dependent tags; relevant resource retrieval; search topic; semiautomatic tagging; social network; Context; Crawlers; Ontologies; Semantics; Tagging; Taxonomy; Web pages; Concept ontology; Crawling; Semantic relevance; Semi-automatic Tags; Topic specific;
fLanguage
English
Publisher
ieee
Conference_Titel
Contemporary Computing (IC3), 2014 Seventh International Conference on
Conference_Location
Noida
Print_ISBN
978-1-4799-5172-7
Type
conf
DOI
10.1109/IC3.2014.6897224
Filename
6897224
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