【作者】 刘靖媛；

【导师】 印桂生；

【作者基本信息】 哈尔滨工程大学 ， 计算机应用技术， 2010， 硕士

【摘要】 随着网络资源数量的不断增长,信息更新的不断加快,信息冗余、主题参杂等问题相继出现,人们想高效地搜索到自己想要的信息变得越发困难。在解决这些问题的过程中,提供个性化服务的搜索引擎提高了检索效率,是人们一直在研究的热点。将用户感兴趣的信息反馈给用户,对不同的用户提供不同的服务模式,即个性化服务的信息方式。本文对个性搜索中的建模技术进行研究,并将sprint分类算法和Agent技术结合到一起应用到建模过程当中,提高建模的速度和准确度,使兴趣模型更贴近用户的实际喜好。该模型对用户将要执行的操作行为进行分析,预测其兴趣所在,优化用户的查询语句,最终达到提高人们检索信息的效率的目的。本文给出了兴趣模型的建立过程。首先设计数据结构,要想运用sprint算法构建用户的兴趣模型,必须对构建兴趣模型所需要的数据源信息进行分析学习,根据sprint算法的执行需求,设计出了有特定结构的三张表,用来存放建模不同阶段所需要的数据。然后,研究基于sprint算法的信息抽取过程。算法如何协助兴趣模型的建立,以及每一步执行是如何对知识库中的数据进行抽取学习,是本文研究的重点内容。最后,建立兴趣模型。对于兴趣模型,本文提出了兴趣模型的建立方法和模型结构。将数据挖掘算法充分应用于建模过程当中,通过用户的链接操作构造兴趣树,从中提取兴趣模型。研究的最终目的是快速建立一个准确的、贴近用户需求的兴趣模型。这种兴趣模型针对不同用户的兴趣取向,提供不同的个性化服务。当用户在面对杂乱繁多的网络资源而不知所措时,帮助用户高效精准的找到自己想到的信息。更多还原

【Abstract】 Network capacity growing and information update accelerating, redundant information, mixed themes occur one after another, and people find it difficult to retrieve the information they want efficiently. In the process of solving these problems, search engine providing personalized services which enhances retrieval efficiency come into focus. The search engine provides information which users are interested in initiatively, and offers different service strategies and content for different users, i.e. personalized service mode of information.In this paper, not only modeling technology of personalized search has been studied, but also sprint algorithm and agent technology together have been applied to the modeling process, which improve the speed and accuracy of modeling. Thus, interest model is closer to the user’s actual preferences. The model analyzes the user’s performance, forecasts their interest, and optimizes their query statements, so it finally can raise the efficiency of information retrieval.This paper provide the process interest model. First, data structure design. According to the implementation requirement of sprint, three tables of special structure have been designed which store required data in different modeling stages. Then, sprint algorithm application. The algorithm applied in data modeling is an innovative point of this article. The establishment of interest model as well as the implementation of data extraction leaning in each step is the main focus of this paper. Finally, interest model establishment. For the interest model, this paper proposes a unique establishment method and a model structure. Data mining algorithm is fully applied in the modeling process, and interest model is extracted while building interest tree with the user’s link operation.The essence of this thesis is to establish an interest model which is accurate and close to the user’s requirement. This interest model provides different user’s orientations with different personalized services. When users lose in messy network resources, the model can help them find what they want effectively and efficiently.更多还原