Title :
Application of Webpage Optimization for Clustering System on Search Engine V Google Study
Author :
Tsung Fu Lin ; Yan Ping Chi
Author_Institution :
Dept. of Manage. Inf. Syst., Nat. Chengchi Univ., Taipei, Taiwan
Abstract :
As of March 2012, there are over six hundred and forty million active websites [5], amid such immense data in the ocean of network; user´s browsing behavior to retrieve information will affect the level of webpage exposure directly. Benjamin Edelman, Michael Ostrovsky and Michael Schwarz reckoned that once obtained a more advanced ranking on search engine, one can obtain higher click through rate [1]. The objective of this study - “Application of webpage optimization for clustering system on search engine - Google study” is to utilize the technologies of TF-IDF, K-means clustering and indexing quality examination to identify the combination of key words that will benefit search engine optimization. The study demonstrated that it can effectively enhance the website´s advancement of ranking on search engine, increase website´s exposure level and click through rate.
Keywords :
Web sites; data mining; indexing; information retrieval; pattern clustering; search engines; statistical analysis; Google study; TF-IDF technology; Web page optimization; Web site exposure level; click through rate; data mining; indexing quality examination; information retrieval; k-means clustering system; search engine optimization; term frequency inverse document frequency technology; user browsing behavior; Context; Couplings; Google; HTML; Optimization; Search engines; Testing; EC; SEO; data mining; eMarketing; search engine;
Conference_Titel :
Computer, Consumer and Control (IS3C), 2014 International Symposium on
Conference_Location :
Taichung
DOI :
10.1109/IS3C.2014.186
