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Received:October 07, 2011 Revised:November 18, 2011
Received:October 07, 2011 Revised:November 18, 2011
中文摘要: 通过挖掘网页的浏览记录来对用户群体兴趣进行分析。对访问网站的兴趣类别、时间、用户数进行统计,得到规律性的结论。其次提出一种改进的基于HAC和k-means的算法对用户根据兴趣进行聚类,挖掘用户的访问模式。最后验证了主导兴趣的稳定性即随着日志的增加,用户的最大兴趣是趋于稳定的。
Abstract:This paper analyses the users’ group interests by mining the internet browsing history. To count the visiting information of the interests’ categories, visiting time and the number of users, get the regularity of conclusion. Then, it has put forward an improved HAC (hierarchical agglomerative clustering) and k-means algorithm to cluster the users by their interests, to mine the users’ access mode. Finally, it has proved the stability of users’ dominant interests. That means the users’ most important interests are stable as the time increases.
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基金项目:国家自然科学基金(70971089);上海市重点学科建设项目(S30501)
引用文本：
曹易,张宁.挖掘用户浏览网页的兴趣研究.计算机系统应用,2012,21(7):65-68,109
CAO Yi,ZHANG Ning.Study of the Uses’ Interests Based on the Internet Browsing History.COMPUTER SYSTEMS APPLICATIONS,2012,21(7):65-68,109
曹易,张宁.挖掘用户浏览网页的兴趣研究.计算机系统应用,2012,21(7):65-68,109
CAO Yi,ZHANG Ning.Study of the Uses’ Interests Based on the Internet Browsing History.COMPUTER SYSTEMS APPLICATIONS,2012,21(7):65-68,109
