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[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(5):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(5):398-403.

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面向浏览推荐的网页关键词提取

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《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 7 期数: 2012年第5期页码: 398-403 栏目: 学术论文—自然语言处理与理解出版日期: 2012-10-25

Title:: Study on website keyword extraction for browsing recommendation

文章编号:: 1673-4785(2012)05-0398-06

作者:: 闫兴龙^1,2,3，刘奕群^1,2,3，马少平^1,2,3，张敏^1,2,3，茹立云^1,2,3; 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^1,2,3, LIU Yiqun^1,2,3, MA Shaoping^1,2,3， ZHANG Min^1,2,3, RU Liyun^1,2,3; 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.

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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

面向浏览推荐的网页关键词提取 PDF下载HTML

备注/Memo

面向浏览推荐的网页关键词提取

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