Application of Webpage Optimization for Clustering System on Search Engine V Google Study

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.