个性化搜索引擎中的用户兴趣模型分析与研究.doc
约41页DOC格式手机打开展开
个性化搜索引擎中的用户兴趣模型分析与研究,2.24万字自己原创的毕业论文，已经通过校内系统检测，重复率低，仅在本站独家出售，大家放心下载使用 摘要 快速发展的现代互联网技术，沟通了世界各地的信息交流，也致使了互联网信息资源的爆炸式增长，同时不可避免地产生了难以让用户快速获取有效信息的问题。传统的搜索引擎提供的信息检索服务...
内容介绍
此文档由会员 jiji888 发布
个性化搜索引擎中的用户兴趣模型分析与研究
2.24万字
自己原创的毕业论文，已经通过校内系统检测，重复率低，仅在本站独家出售，大家放心下载使用
摘要 快速发展的现代互联网技术，沟通了世界各地的信息交流，也致使了互联网信息资源的爆炸式增长，同时不可避免地产生了难以让用户快速获取有效信息的问题。传统的搜索引擎提供的信息检索服务职能被动地接受用户的请求，并反馈一定相关度的信息，无法自主地感知用户的需求。而这些问题可能的缘由是现代的搜索引擎采用了全文检索的匹配方法，使得用户往往会得到相当多的查询结果网页，而用户一般只会访问其中感兴趣的网页，抑或是有检索倾向的网页。在面临用户输入的检索词意向模糊、不全面的情况下 ，不同的个性化需求用户，在输入相同的检索词的时候也往往得到相同的结果，更甚者得到相同的网页排序。显然，这样传统的信息检索无法在信息膨胀的互联网上满足用户愈加复杂和差异化的需求。所以，迫切需要一种能迎合不用的用户需求差异的个性化信息检索服务。本文的方向在于搜索引擎提供个性化信息检索服务的关键——用户兴趣模型。
首先，阐述了搜索引擎的研究背景，介绍个性化信息服务的发展和体系结构。总结了国内为搜索引擎的发展现状和其基本理论。简述了他的定义以及其组成的各个部分功能，阐述了现有搜索引擎的缺陷和不足。
基于向量空间模型表示的用户兴趣在准确性和全面性上存在问题，在不考虑用户兴趣多样性的前提下提出了层次性向量空间模型表示用户的兴趣。
采用xml存储用户兴趣，并建立“用户--xml”的映射关系，使得搜索引擎通过用户名找到用户的兴趣文件，保证个性化搜索。
提出一种改进的用户兴趣模型方案，通过搭载nutch搜索引擎，将用户兴趣模型运用于搭载的搜索引擎中实验。
关键词：个性化信息搜索 层次性向量空间模型 用户兴趣建模
Abstract The rapid development of modern Internet technology, communication and the exchange of information around the world, has also led to the explosion of Internet information resource growth, also produced inevitably difficult to give the user quick access to effective information problem.Information retrieva l service function of traditional search engines provide a passive acceptance of the user's request, and certain relevance feedback information, not self perceived user requirements.And the reason of these problems may be modern search engines by full text retrieva l, users tend to get quite a lot of query results Webpage, while users usually access the interested Webpage, or are prone Webpage retrieva l.In the face of the user input query intention fuzzy, not overall situation, not the individual needs of users, in the same input to retrieve the same result also often get the word, even get the same Webpage sort.Obviously, the traditional information retrieva l can not meet the user more and more complex and differentiated demands in the expansion of the information on the internet.Therefore, the urgent need of personalized information a user needs to do not have different retrieva l service.In this paper, the key lies in the direction of search engines provide personalized information retrieva l services -- the user interest model.
Firstly, it elaborates the research background of search engine, introduces the development of personalized information service and system structure.Summarized the domestic development status of search engine and its basic theory.In his definition as well as its composition function of every part, expounds the defects and deficiencies of the existing search engine.
User interest based on vector space model problems in accuracy and comprehensiveness, presents hierarchical vector space model to represent the interests of users without considering the user interest diversity premise.
Based on the analysis of the basic user residence time in the Webpage and repeated browsing Webpage times to calculate interest concentration on Webpage users, considering the size of the Webpage, put forward to calculate the user interest concentration Webpage algorithm based on browsing speed.
Using XML to store the user interest, and establish the "mapping between user --xml", allows the search engine to find the user interest file by name, ensure personalized
search.
Proposes an improved user interest model, search engine by playing in the nutch, the user interest model used in the flight search engine experiment.
Keywords: personalized information search, hierarchical vector space model, user interest modeling
目录
引言-----------------------------------------------------------------------------------1
第一章 绪论------------------------------------------------------------------------------------2
1.1搜索引擎---------------------------------------------------------------------------------2
1.2兴趣模型---------------------------------------------------------------------------------3
1.3研究现状及课题意义-----------------------------------------------------------------4
1.4课题内容---------------------------------------------------------------------------------5
1.5本章小结---------------------------------------------------------------------------------5
第二章 搜索引擎相关理论-------------------..
2.24万字
自己原创的毕业论文，已经通过校内系统检测，重复率低，仅在本站独家出售，大家放心下载使用
摘要 快速发展的现代互联网技术，沟通了世界各地的信息交流，也致使了互联网信息资源的爆炸式增长，同时不可避免地产生了难以让用户快速获取有效信息的问题。传统的搜索引擎提供的信息检索服务职能被动地接受用户的请求，并反馈一定相关度的信息，无法自主地感知用户的需求。而这些问题可能的缘由是现代的搜索引擎采用了全文检索的匹配方法，使得用户往往会得到相当多的查询结果网页，而用户一般只会访问其中感兴趣的网页，抑或是有检索倾向的网页。在面临用户输入的检索词意向模糊、不全面的情况下 ，不同的个性化需求用户，在输入相同的检索词的时候也往往得到相同的结果，更甚者得到相同的网页排序。显然，这样传统的信息检索无法在信息膨胀的互联网上满足用户愈加复杂和差异化的需求。所以，迫切需要一种能迎合不用的用户需求差异的个性化信息检索服务。本文的方向在于搜索引擎提供个性化信息检索服务的关键——用户兴趣模型。
首先，阐述了搜索引擎的研究背景，介绍个性化信息服务的发展和体系结构。总结了国内为搜索引擎的发展现状和其基本理论。简述了他的定义以及其组成的各个部分功能，阐述了现有搜索引擎的缺陷和不足。
基于向量空间模型表示的用户兴趣在准确性和全面性上存在问题，在不考虑用户兴趣多样性的前提下提出了层次性向量空间模型表示用户的兴趣。
采用xml存储用户兴趣，并建立“用户--xml”的映射关系，使得搜索引擎通过用户名找到用户的兴趣文件，保证个性化搜索。
提出一种改进的用户兴趣模型方案，通过搭载nutch搜索引擎，将用户兴趣模型运用于搭载的搜索引擎中实验。
关键词：个性化信息搜索 层次性向量空间模型 用户兴趣建模
Abstract The rapid development of modern Internet technology, communication and the exchange of information around the world, has also led to the explosion of Internet information resource growth, also produced inevitably difficult to give the user quick access to effective information problem.Information retrieva l service function of traditional search engines provide a passive acceptance of the user's request, and certain relevance feedback information, not self perceived user requirements.And the reason of these problems may be modern search engines by full text retrieva l, users tend to get quite a lot of query results Webpage, while users usually access the interested Webpage, or are prone Webpage retrieva l.In the face of the user input query intention fuzzy, not overall situation, not the individual needs of users, in the same input to retrieve the same result also often get the word, even get the same Webpage sort.Obviously, the traditional information retrieva l can not meet the user more and more complex and differentiated demands in the expansion of the information on the internet.Therefore, the urgent need of personalized information a user needs to do not have different retrieva l service.In this paper, the key lies in the direction of search engines provide personalized information retrieva l services -- the user interest model.
Firstly, it elaborates the research background of search engine, introduces the development of personalized information service and system structure.Summarized the domestic development status of search engine and its basic theory.In his definition as well as its composition function of every part, expounds the defects and deficiencies of the existing search engine.
User interest based on vector space model problems in accuracy and comprehensiveness, presents hierarchical vector space model to represent the interests of users without considering the user interest diversity premise.
Based on the analysis of the basic user residence time in the Webpage and repeated browsing Webpage times to calculate interest concentration on Webpage users, considering the size of the Webpage, put forward to calculate the user interest concentration Webpage algorithm based on browsing speed.
Using XML to store the user interest, and establish the "mapping between user --xml", allows the search engine to find the user interest file by name, ensure personalized
search.
Proposes an improved user interest model, search engine by playing in the nutch, the user interest model used in the flight search engine experiment.
Keywords: personalized information search, hierarchical vector space model, user interest modeling
目录
引言-----------------------------------------------------------------------------------1
第一章 绪论------------------------------------------------------------------------------------2
1.1搜索引擎---------------------------------------------------------------------------------2
1.2兴趣模型---------------------------------------------------------------------------------3
1.3研究现状及课题意义-----------------------------------------------------------------4
1.4课题内容---------------------------------------------------------------------------------5
1.5本章小结---------------------------------------------------------------------------------5
第二章 搜索引擎相关理论-------------------..
