Abstract
Most of the researchers have widely explored the use of link-context to determine the theme of target web-page. Link-context has been applied in areas such as search engines, focused crawlers, and automatic classification. Therefore, extraction of precise link-context may be considered as an important parameter for extracting more relevant information from the web-page. In this paper, we have proposed a rule-based approach for the extraction of the link-context from anchor-text (AT) structure using bottom-up simple LR (SLR) parser. Here, we have considered only named entity (NE) anchor-text. In order to validate our proposed approach, we have considered a sample of 4 ATs. The results have shown that, the proposed LCEA has extracted 100% actual link-context of each considered AT.
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References
Jing, T., Ping, T., Zuo, W.: Deriving Link Context through Dependency Analysis. In: IEEE International Conference on Education Technology and Computer (2009)
Java, A., et al.: Using a Natural Language Understanding System to Generate Semantic Web Content. International Journal on Semantic Web and Information Systems 3(4) (2007)
Chauhan, N., Sharma, A.K.: Analyzing Anchor- Links to Extract Semantic Inference of a Web page. In: 10th IEEE International Conference on Information Technology (2007)
Xu, Q., Zuo, W.: Extracting Precise Link Context Using NLP Parsing Technique. In: Proceeding of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004 (2004)
Pant, G.: Deriving Link-context from HTML Tag Tree. In: Proceedings of 8th SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (2003)
Henzinger, M., et al.: Link Analysis in Web Information Retrieval. IEEE Data Engineering Bulletin 23(3), 3–8 (2000)
Aho, A.V., Ullman, J.D.: Principals of Compiler Design, pp. 197–214. Narosa Publishing House (25th reprint 2003)
Fensal, D., Van Harmelen, Horrocks, I., McGuinness, Patel-Scheider: OIL: An ontology Infrastructure for the Semantic Web. IEEE Intelligent Systems 16(2), 38–45 (2001)
Klein, M.: Tutorial: The Semantic Web- XML, RDF, and Relatives. IEEE Intelligent Systems 16(2), 26–28 (2001)
Hebeler, J., Fisher, M., Blace, R., Lopez, A.P.: Semantic Web Programming, pp. 63–139. Wiley Publication (2009)
Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems 30(1-7), 107–117 (1998)
Aggarwal, C.C., AI-Garawi, F., Yu, P.S.: Intelligent crawling on the World Wide Web with arbitrary predicates. In: WWW 10, Hong Kong (May 2001)
Chauhan, N., Sharma, A.K.: A framework to derive web page context from hyperlink structure. International Journal of Information and Communication Technology 1(3/4), 329–346
Attardi, G., Gulli, A., Sebastini, F.: Automatic Web page categorization by link and context analysis. In: Proceeding of THAI 1999, 1st European Symposium on Telematics, Hypermedia and Artificial Intelligence (1999)
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Kumar, S., Kumar, N., Singh, M., De, A. (2013). A Rule-Based Approach for Extraction of Link-Context from Anchor-Text Structure. In: Abraham, A., Thampi, S. (eds) Intelligent Informatics. Advances in Intelligent Systems and Computing, vol 182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32063-7_28
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DOI: https://doi.org/10.1007/978-3-642-32063-7_28
Publisher Name: Springer, Berlin, Heidelberg
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