A hybrid item-based recommendation ranking algorithm based on user access patterns

Shao Chieh Hu, Cheng Yi Yang, Chien Tsai Liu

研究成果: 書貢獻/報告類型會議貢獻

摘要

Nowadays, most websites provide tremendous information organized in complex structures of web pages. Therefore, how to help users quickly find pages they are looking for is an important issue. Although a sitemap can provide navigation information across sections of the website, it is static and can hardly provide dynamic information based on access patterns and browsing trends. In this paper, we proposed a hybrid approach for improving recommendation ranking of the web pages for the next visit. Our raking strategy considers not only the relevance (correlation to the next page calculated by the collaborative filtering algorithm) but also the level of interest (time spent on a page) and accessibility (the distance to the next page). In order to evaluate the proposed recommendation ranking algorithm, we used the web access log (IIS log) of a website, Health 99, operated by the Bureau of Health Promotion, Taiwan. The log data was divided into training and testing sets. The measurements of the relevance, the level of interest and the distance factor were computed from the training set. The experimental results showed that the possibility of the pages in the recommendation ranking lists by our approach that were accepted by users was much higher than that proposed by the original collaborative filtering algorithm, particular in short recommendation list (<5).
原文英語
主出版物標題Advances in Intelligent and Soft Computing
頁面225-233
頁數9
163 AISC
DOIs
出版狀態已發佈 - 2012
事件2012 International Conference on Teaching and Computational Science, ICTCS 2012 - , 澳门
持續時間: 四月 1 2012四月 2 2012

出版系列

名字Advances in Intelligent and Soft Computing
163 AISC
ISSN(列印)18675662

其他

其他2012 International Conference on Teaching and Computational Science, ICTCS 2012
國家澳门
期間4/1/124/2/12

ASJC Scopus subject areas

  • Computer Science(all)

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