【作者】 陈都；

【导师】 郑玲；

【作者基本信息】 华北电力大学（北京） ， 计算机软件与理论， 2008， 硕士

【摘要】 在互联网飞速发展的环境下,互联网上信息数量的快速增加、信息内容的大量冗余等问题都给网络用户带来了很多困扰,也对搜索引擎服务提出了更高的质量要求。本文对搜索引擎智能化领域中的大量文献资料与研究成果进行了学习,分析比较了主要的分词算法和文档分类算法,提出并设计了一种自适应的个性化搜索引擎系统。该系统基于对用户历史搜索行为及当前反馈的分析学习,提供了对用户查询条件进行扩展和根据用户浏览情况自动调节搜索结果的功能,从而有效的满足用户的查询需求。论文中对系统的总体设计方案及关键技术进行了详细介绍,对各模块的主要功能及实现算法作了详细论述,最后对所开发的系统进行了测试,实验结果表明,能够满足系统的设计目标,具有很好的使用价值和应用前景。更多还原

【Abstract】 Because of the Internet’s rapid development, a lot of problems are bought to users by the information’s increasing and redundant. These problems also put higher quality requirements to the search engine.In this paper, we studied a lot of literature for information and research results in the field of intelligent search engines, analysis and compared of mainly segmentation algorithm and documents classification algorithm, designed an adaptive personalized search engine system. Based on the user search history behavior and the current feedback analysis, provided the expansion of user’s query and automatically adjust search results function, The system can effectively meet the needs of user enquiries.In this paper, we have given the general scheme and its key technology in detail of the system, provide the key module’s main functions and algorithms, and test the system. The results of experiment show that the system can meet the design goals and has good value and prospects.更多还原