[1]闫兴龙,刘奕群,马少平,等.面向浏览推荐的网页关键词提取[J].智能系统学报,2012,7(05):398-403.
 YAN Xinglong,LIU Yiqun,MA Shaoping,et al.Study on website keyword extraction for browsing recommendation[J].CAAI Transactions on Intelligent Systems,2012,7(05):398-403.
点击复制

面向浏览推荐的网页关键词提取(/HTML)
分享到:

《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第7卷
期数:
2012年05期
页码:
398-403
栏目:
出版日期:
2012-10-25

文章信息/Info

Title:
Study on website keyword extraction for browsing recommendation
文章编号:
1673-4785(2012)05-0398-06
作者:
闫兴龙123刘奕群123马少平123张敏123茹立云123
1.清华大学 计算机科学与技术系,北京 100084;
2.清华大学 智能技术与系统国家重点实验室,北京 100084;
3.清华大学 清华信息科学与技术国家实验室(筹),北京 100084
Author(s):
YAN Xinglong123 LIU Yiqun123 MA Shaoping123 ZHANG Min123 RU Liyun123
1.Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;
2.State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084, China;
3.Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China
关键词:
浏览推荐关键词推荐关键词提取网页关键词
Keywords:
browsing recommendation keyword recommendation keyword extraction web keywords
分类号:
TP391
文献标志码:
A
摘要:
在网页浏览推荐任务中,如何利用网页内容选取合适的推荐关键词是具有挑战性的研究热点.为了实现有效的关键词推荐方法,利用大规模的真实网络用户浏览行为数据,以及相关提取算法和新词发现算法实现并比较了基于领域关键词提取技术和基于查询词候选集合的关键词推荐方法.实验结果证明,2种方法都能够有效地表征用户信息需求,而第1种推荐方法的准确率更高,具有更好的推荐性能.
Abstract:
It is very challenging when conducting research and it is especially difficult as it pertains to website browsing and recommendation system task for selection of suitable keyword usage. This research study will focus on proper use of website browsing and recommendations on how to select keywords for conducting research. The challenge is to leverage user behavior features, as well as develop an effective keyword’s recommendation content page. The implementation of a comprehensive user browsing data, relevant extraction algorithm and algorithm finding methods for new keywords were examined in the research study. The research study also proposed additional, keyword recommendation methods utilizing largescale and related algorithm approaches for domainspecific keyword extraction technology and a query keyword candidate set were compared. The experiment results confirm both methods demonstrate that they satisfy users’ information demand. However, the keyword recommendation methods show a significant performance improvement in effectiveness. The keyword recommendation method has a higher accuracy and better recommendation performance.

参考文献/References:

[1]许海玲,吴潇,李晓东,等.互联网推荐系统比较研究[J].软件学报, 2009, 20(2): 350362. 
XU Hailing, WU Xiao, LI Xiaodong, et al. Comparison study of internet recommendation system[J]. Journal of Software, 2009, 20(2): 350362.
[2]张培颖.基于Web内容和日志挖掘的个性化网页推荐系统[J].计算机系统应用, 2008, 17(9): 912. 
ZHANG Peiying. Personalized web page recommendation system based on web content and log mining[J]. Computer System and Applications, 2008, 17(9): 912.
[3]YANG Qingyan, FAN Ju, WANG Jianyong, et al. Personalizing web page recommendation via collaborative filtering and topicaware Markov model[C]//IEEE International Conference on Data Mining. Sydeny, Australia, 2010: 11451150.
[4]SUMATHI C P, VALLI R P, SANTHANAM T. Automatic recommendation of web pages in web usage mining[J]. International Journal of Computer Science and Engineering, 2010, 2(9): 30463052.
[5]刘强,郭景峰.基于用户访问路径分析的页面推荐模型[J].计算机技术与发展, 2007, 17(1): 151154.
 LIU Qiang, GUO Jingfeng. A web page recommendation model based on analyzing user access pattern[J]. Computer Technology and Development, 2007, 17(1): 151154.
[6]WU Y H, CHEN Y C, CHEN A L P. Enabling personalized recommendation on the web based on user interests and behaviors[C]//Proceedings of the 11th International Workshop on Research Issues in Data Engineering. Washington, DC, USA: IEEE Computer Society, 2001: 1724.
[7]邵华,高凤荣,邢春晓,等.基于VSM的分层网页推荐算法[J].计算机科学, 2006, 33(11): 8588, 105. 
SHAO Hua, GAO Fengrong, XING Chunxiao, et al. A hierarchical webpage recommendation algorithm based on vector space model[J]. Computer Science, 2006, 33(11): 8588, 105.
[8]杨学明,蒋云良.基于语义的自适应个性化网页推荐[J].情报理论与实践, 2009, 32(3): 9396. 
YANG Xueming, JIANG Yunliang. Based on semantic adaptive personalized pages recommendation[J]. Information Studies: Theory and Application, 2009, 32(3): 9396.
[9]梁邦勇,李涓子,王克宏.基于语义Web的网页推荐模型[J].清华大学学报:自然科学版, 2004, 44(9): 12721276, 1281. 
LIANG Bangyong, LI Juanzi, WANG Kehong. Web page recommendation model for the semantic web[J]. Journal of Tsinghua University: Science and Technology, 2004, 44(9): 12721276, 1281.
[10]袁燚,张璟,李军怀.基于网页关键词的个性化Web推荐算法[J].西安理工大学学报, 2007, 23(1): 5961. 
YUAN Yan, ZHANG Jing, LI Junhuai. A personal web recommendation algorithm based on web page key words[J]. Journal of Xi′an University of Technology, 2007, 23(1): 5961.
[11]杨学明.基于本体学习的个性化网页推荐[J].情报杂志, 2009, 28(3): 171174, 198. 
YANG Xueming. Personalized web recommending based on ontology learning[J]. Journal of Intelligence, 2009, 28(3): 171174, 198.
[12]赵银春,付关友,朱征宇.基于Web浏览内容和行为相结合的用户兴趣挖掘[J].计算机工程, 2005, 31(12): 9394, 198.
ZHAO Yinchun, FU Guanyou, ZHU Zhengyu. User interest mining of combining web content and behavior analysis[J]. Computer Engineering, 2005, 31(12): 9394, 198.

备注/Memo

备注/Memo:
收稿日期: 2012-03-29.
网络出版日期:2012-09-25.
基金项目:国家自然科学基金资助项目(60736044,60903107,61073071);高等学校博士学科点专项科研基金资助项目(20090002120005).
通信作者:闫兴龙.
E-mail: yanxinglong@163.com.
作者简介:
闫兴龙,男,1986年生,硕士研究生,主要研究方向为信息检索、推荐系统.  
刘奕群,男,1981年生,助理研究员,博士,中国人工智能学会知识工程专委会副秘书长.主要研究方向为网络搜索与性能评价、面向搜索引擎的用户行为分析.2010年获“钱伟长中文信息处理科学技术奖”青年创新一等奖.申请专利13项,其中6项已获得授权.发表学术论文50余篇,出版教材1部. 
马少平,男,1961年生,教授,博士生导师,博士,中国人工智能学会副理事长、知识工程专业委员会主任,中国中文信息学会理事、信息检索与内容安全专业委员会副主任.主要研究方向为智能信息处理,包括模式识别、文本信息检索、图像信息检索、中文古籍的数字化与检索等.作为项目负责人承担“973”计划、“863”计划、国家自然科学基金和国际合作项目多项.发表学术论文70余篇,出版专著2部.
更新日期/Last Update: 2012-11-13