Semantic Web Mining: An Amalgamation for Knowledge Extraction
Karan Sukhija
Abstract
Karan Sukhija
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 machine- comprehensible data by means of Semantic Web tools.
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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 machine- comprehensible data by means of Semantic Web tools.
Key concepts: Social Semantic Web, Data Web, Semantic Web Stack, Web mining, Web intelligence, Computer science, World Wide Web, Web standards