Semantic Web Mining: An Amalgamation for Knowledge Extraction

International Journal of Computer Science and Engineering
© 2015 by SSRG - IJCSE Journal
Volume 2 Issue 8
Year of Publication : 2015
Authors : Karan Sukhija

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Citation:
MLA Style:

Karan Sukhija, "Semantic Web Mining: An Amalgamation for Knowledge Extraction" SSRG International Journal of Computer Science and Engineering 2.8 (2015): 14-17.

APA Style:

Karan Sukhija, (2015). Semantic Web Mining: An Amalgamation for Knowledge Extraction. SSRG International Journal of Computer Science and Engineering 2.8, 14-17.

Abstract:

Semantic Web Mining is an emerging research area, aimed as amalgamation of two most rising arenas of research: the Web Mining and Semantic Web (SW). SW is an expansion of existing web where result knowledge is specified the distinct meaning. It enhances the web search. Web mining, as a mounting area of data mining, has three operations of interests in terms of data mining techniques– Clustering (i.e. find out the natural clustering between the pages of web, operators etc.),Association (i.e. the requested web addresses collectively inclined) and chronological scrutiny (i.e. the sort in which web address tendency to be salvaged). Semantic Web Mining purpose is to enhance the domino effect of Web Mining by exploring the novel-fangled semantic assemblies in the Web. It also makes usage of Web Mining for assembling up the Semantic Web.Both these arenas’ distillate on the prevailing encounters of the World Wide Web: spinning amorphous data into machinecomprehensible data by means of Semantic Web tools.

References:

[1] Semantic Web Mining: State of the art and future directions, Stumme.G, Hotho. A, Berendt B, Web Semantics: Science, Services and Agents on the World Wide Web 4(2) (2006) 124 – 143 Semantic Grid – The Convergence of Technologies.
[2] Web Mining in Soft Computing Framework: Relevance, State of the Art and Future Directions, Sankar K. Pal, VarunTalwar, and PabitraMitra, IEEE transactions on neural networks, vol. 13, no. 5, september 2002.
[3] V. Kolovski ,J. Galletly,”Towards E-Learning via the Semantic Web”,International Conference on Computer Systems and Technologies - CompSysTech’2003.
[4] H. W. Malik ,”Visual semantic web: ontology based Elearning management system”, January 2009.
[5] Towards Knowledge Discovery in the Semantic Web, Krcmar H (2004), Informations management (German Edition). Springer, Berlin.
[6] Towards Semantic Web Mining, Berendt B, Hotho A, Stumme G (2002). ISWC 2002, First International Semantic Web Conference, Sardinia, Italy, June 9-12, 2002, Springer.
[7] Application based semantic web mining technique, Mahindra Pratap Singh Dohare*1 and Sanjaydeep Singh Lodhi, VinodMahor, Volume 2, No. 3, March 2011, JGRCS.
[8] A Roadmap for Web Mining: From Web to Semantic Web, Berendt, B., Hotho, A., Mladenic, D., van Someren, M., Spiliopoulou, M., Stumme, G. Web Mining: From Web to Semantic Web Volume 3209/2004 (2004) 1–22.
[9] Using Semantic Web Mining Technologies for Personalied ELearning Experiences, P. Markellou, I. Mousourouli, S. Spiros, and A. Tsakalidis (Greece),Proceeding (461) Webbased Education, 2005.
[10] Aguado, B., Merceron, A., Voisard, A.: Extracting information from structured exercises. In: Proceedings of the 4th International Conference on Information Technology Based Higher Education and Training ITHET03, Marrakech, Morocco. (2003).
[11] Tane, J., Schmitz, C., Stumme, G.: Semantic resource management for the web: An elearning application. In: Proc. 13th InternationalWorldWideWeb Conference (WWW 2004).
[12] K Sukhija, Web Content Mining equipped Natural Language Processing for handling web data, International Journal of Computer ApplicationsTechnology and Research, Volume 4– Issue3,209-213,2015.

Key Words:

 Web Mining, Semantic web, Ontology, Semantic web mining.