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題名 Application of webpage optimization for clustering system on search engine v google study
作者 Lin, Tsung Fu;Chi, Yan-Ping
季延平
貢獻者 資管系
關鍵詞 Behavioral research; Data mining; Websites; Browsing behavior; Click-through rate; E-marketing; EC; K-means clustering; Search engine optimizations; Search Engine-Google; SEO; Search engines
日期 2014-07
上傳時間 16-Jun-2015 15:54:49 (UTC+8)
摘要 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. © 2014 IEEE.
關聯 Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014, 2014, 論文編號 6845978, Pages 698-701, 2nd International Symposium on Computer, Consumer and Control, IS3C 2014; Taichung; Taiwan; 10 June 2014 到 12 June 2014; 類別編號E5201; 代碼 106413
資料類型 conference
DOI http://dx.doi.org/10.1109/IS3C.2014.186
dc.contributor 資管系
dc.creator (作者) Lin, Tsung Fu;Chi, Yan-Ping
dc.creator (作者) 季延平zh_TW
dc.date (日期) 2014-07
dc.date.accessioned 16-Jun-2015 15:54:49 (UTC+8)-
dc.date.available 16-Jun-2015 15:54:49 (UTC+8)-
dc.date.issued (上傳時間) 16-Jun-2015 15:54:49 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/75839-
dc.description.abstract (摘要) 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. © 2014 IEEE.
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014, 2014, 論文編號 6845978, Pages 698-701, 2nd International Symposium on Computer, Consumer and Control, IS3C 2014; Taichung; Taiwan; 10 June 2014 到 12 June 2014; 類別編號E5201; 代碼 106413
dc.subject (關鍵詞) Behavioral research; Data mining; Websites; Browsing behavior; Click-through rate; E-marketing; EC; K-means clustering; Search engine optimizations; Search Engine-Google; SEO; Search engines
dc.title (題名) Application of webpage optimization for clustering system on search engine v google study
dc.type (資料類型) conferenceen
dc.identifier.doi (DOI) 10.1109/IS3C.2014.186
dc.doi.uri (DOI) http://dx.doi.org/10.1109/IS3C.2014.186