U. Niranjan, V. V. Krishna, Kanduri Srividya, V. Khanaa
{"title":"An efficient web recommendation system based on modified IncSpan algorithm","authors":"U. Niranjan, V. V. Krishna, Kanduri Srividya, V. Khanaa","doi":"10.1504/IJKWI.2011.044118","DOIUrl":null,"url":null,"abstract":"Web recommendation systems are used to assist the user to access the most appropriate web pages that can satisfy their needs. This paper provides the web recommendation system which is based on incremental database. The incremental database contains the new navigational sequences from the user and this incremental database can be added with the existing sequence database. We have proposed a novel algorithm, called modified IncSpan, for the effectual mining of the sequential patterns from the incremental database. Finally, the performance of the proposed recommendation system is evaluated with precision, applicability and hit ratio.","PeriodicalId":113936,"journal":{"name":"Int. J. Knowl. Web Intell.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Knowl. Web Intell.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJKWI.2011.044118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Web recommendation systems are used to assist the user to access the most appropriate web pages that can satisfy their needs. This paper provides the web recommendation system which is based on incremental database. The incremental database contains the new navigational sequences from the user and this incremental database can be added with the existing sequence database. We have proposed a novel algorithm, called modified IncSpan, for the effectual mining of the sequential patterns from the incremental database. Finally, the performance of the proposed recommendation system is evaluated with precision, applicability and hit ratio.