期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：4
页码：7030
DOI：10.15680/IJIRCCE.2017.0504068
出版社：S&S Publications
摘要：Distribution of textual documents on the internet is ever changing in various forms. Instead of miningcharacteristics of users from published document streams, here we concentrated on browsed document streams. Usersare browsing various textual documents from various sources. To understand their personal interests and behaviours areone of the innovative applications of the User-aware Rare Sequential Topic Patterns (URSTPs). STPs can characterisecomplete browsing behaviours of readers, so compared to statistical methods mining URSTPs better to discover specialinterests and browsing habits of internet users. Hence, it is capable to give effective and efficient context awarerecommendation for them.
关键词：STPs; web data mining; LDA; hash map; Twitter LDA; PLSI
