UCSY's Research Repository

Sequential Pattern Mining in Web Log Data using Generalize Sequential Pattern Mining(GSP) Algorithm

Show simple item record

dc.contributor.author Hlaing, Khin Su
dc.contributor.author Tun, Ei Ei
dc.date.accessioned 2019-08-06T11:17:26Z
dc.date.available 2019-08-06T11:17:26Z
dc.date.issued 2009-12-30
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1887
dc.description.abstract The rising popularity of electronic commerce makes data mining an indispensable technology for several applications, especially online business competitiveness. The World Wide Web provides abundant raw data in the form of web access logs. However, without data mining techniques, it is difficult to make any sense out of such massive data. In this paper focus on the mining of web access log, commonly known as Web usage mining. Frequent pattern mining is a heavily researched area in the field of data mining with wide range of applications. One of them is to use frequent pattern discovery methods in Web log data. Discovering hidden information from Web log data is called Web usage mining. The aim of discovering frequent patterns in Web log data is to obtain information about the navigational behavior of the users. This can be used for advertising purposes, for creating dynamic user profiles etc.In this paper, GSP algorithm is used for sequential pattern mining in web log data. en_US
dc.language.iso en en_US
dc.publisher Fourth Local Conference on Parallel and Soft Computing en_US
dc.title Sequential Pattern Mining in Web Log Data using Generalize Sequential Pattern Mining(GSP) Algorithm en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Repository



Browse

My Account

Statistics