期刊文献+

面向用户兴趣的Web信息过滤系统 被引量:3

Web Information Filtering System Based on User-Oriented Interests
下载PDF
导出
摘要 研究了面向用户兴趣的Web信息过滤系统的主要技术,包括用户兴趣表示、度量和更新、网页内容识别和网页信息过滤等技术,并在此基础上设计和实现了一个Web信息过滤系统。该系统能够进行一定的信息过滤,能够进行自学习,并随着用户兴趣的变化渐渐更新,基本能够实现用户的个性化信息服务需求。 This paper studied some basic techniques in order to develop the Web information filtering system user-oriented interests, which are the methods of user interest describing ,measurement and updating,Web page recoginzing and Web information filtering etc. At the same time,a Web information filtering system is designed and developed. The system can perform these tasks of information filtering based on user interest ,acquire and update user interest automatically. So it can satisfy the people's requirement of personalized information service.
出处 《广西师范大学学报(自然科学版)》 CAS 北大核心 2006年第4期171-174,共4页 Journal of Guangxi Normal University:Natural Science Edition
基金 江西省自然科学基金资助项目(0311101) 江西省教育厅科技资助项目(赣教技字[2006]178号)
关键词 WebI信息过滤 用户兴趣 强化学习 Web information filtering user interest reinforcement learning
  • 相关文献

参考文献10

二级参考文献33

  • 1Watkins C J C H. Learning from Delayed Rewards:[Ph.D.thesis]. Cambridge University, 1989. 被引量:1
  • 2Watkins C J C H. Dayan P. Technical not:Q-learning. Machine Learning, 1992,8:279~292. 被引量:1
  • 3Ohashi T ,et al. State transition rate based reinforcement learning Systems, Man, and Cybernetics. In: 2000 IEEE Intl. Cord.Volume: 1, 2000. 236~241. 被引量:1
  • 4Yamagnchi T,et al. Propagating learned behaviors from a virtual agent to a physical robot in reinforcement learnins, In..Proe. IEEE Int. Conf. on Evolutionary Computation, 1996. 855~859. 被引量:1
  • 5Yamagnchi T,et al. Reinforcement learning for a real robot in a real environment. In: European Conf. on Artificial Intelligence,Aug. 1996. 694~698. 被引量:1
  • 6Hailu G. Sommer G. Embedding knowledge in reinforcement·learning. In: Proc. 8^th Int. Conf. on Artificial Neural Networks.Sep. 1998. 1133~1138. 被引量:1
  • 7Huber M. A hybrid architecture for hierarchical reinforcement learning. In: Proc. IEEE Int. Conf. on Robotics & Automation,April 2000. 3290~3295. 被引量:1
  • 8Peng J, Bhanu B. Closed loop object recognition using reinforcement learning. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1998,20(2) : 139~154. 被引量:1
  • 9Schwartz J T,Shirir M. A survey of motion planning and related geometric algorithm. Artif. Intell. J. , 1988,37 : 157~169. 被引量:1
  • 10Canny 3 F. The Complexity of Robot Motion Planning.Cambridge, MA: MIT Press, 1988. 被引量:1

共引文献51

同被引文献18

  • 1刘远超,王晓龙,徐志明,关毅.文档聚类综述[J].中文信息学报,2006,20(3):55-62. 被引量:65
  • 2乐兵,王明文.基于遗传算法的动态文本聚类[J].江西师范大学学报(自然科学版),2006,30(3):278-281. 被引量:3
  • 3曲德祥,唐新亭,徐连诚,石磊.网络信息过滤系统研究综述[J].山东师范大学学报(自然科学版),2007,22(2):23-26. 被引量:9
  • 4ROCCHIO J J. Relevance feedback in information retrieval[C]//SALTON G. The SMART Retrieval System. Englewood Cliffs ,NJ :Prentice-Hall, 1971 : 313-323. 被引量:1
  • 5JOACHIMS T. Text categorization with support vector machine :Learning with many relevant features[C]//Nedellec C,Rouveirol C. Proc. of the 10th European Conf. on Machine Learning (ECML-98). Chemnitz: Springer-Verlag, 1998: 137-142. 被引量:1
  • 6GRUBER T R. A translation approach to portable ontology specifications[J]. Knowledge Acquisition, 1993 (5):199-220. 被引量:1
  • 7CHAUDHRI V K,FARQUHAR A,FIKES R,et al. OKBC:A progammatic foundation for knowledge base interoperability[C]//Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence. Menlo Park CA:American Association for Artificial Intelligence, 1998,600-607. 被引量:1
  • 8BOLLACKER K D,LAWRENCE S,GILES C L.Discovering relevant scientific literature on the Web[J].IEEE Intelligent Systems,2000,15 (2):42-47. 被引量:1
  • 9MLADENIC D.Machine learning for better Web browsing[C]//ROGERS S,IBA W.AAAI 2000 Spring Symposium Technical Reports on Adaptive User Interfaces.Menlo Park,CA:AAAI Press,2000:82-84. 被引量:1
  • 10FOOTE J.An overview of audio information retrieval[J].Multimedia Systems,1999,7 (1):2-10. 被引量:1

引证文献3

二级引证文献12

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部