基于访问行为规则挖掘的网站搜索引擎优化研究

发布时间：2018-03-04 19:08

本文选题：数据挖掘　切入点：搜索引擎优化　出处：《湖北工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：在当今信息时代,互联网的雪崩式发展改变了人们的生活方式、工作方式、学习方式乃至思维方式,而这其中Web起到了关键性作用。而越来越多的商户也开始在互联网上建立起自己的主页,期望能通过在线上获取更多的关注,从而促进产品的销售。为此提高网站在搜索引擎中的排名、获取更多的关注则成为商家开展自身网站优化建设的首要问题。搜索引擎算法的核心功能是根据客户输入的关键字寻找对应的网页,并以排序的方式展现给客户。在搜索引擎中改进网站的排名对于网站本身的价值以及对应的商业活动而言,都具有十分重要的意义。而在对网页排序的过程中,搜索引擎有其对应的规则,例如关键字出现的频次以及网站的链接等。因此在既定的规则下,对网站中文本内容的合理整理、网站中网站链接结构进行对应的优化则有利于网站在搜索引擎的排序上升。这也是目前大多数商业网站或者门户网站在提高搜索引擎排序中所常用的办法。本文在此背景下以玉都商城网站为例开展搜索引擎优化研究,分别从数据的预处理,用户访问行为规则的挖掘以及基于访问行为的链接优化三个方面进行了研究。首先,数据预处理。分析了用户网络访问行为数据的来源,介绍了数据的清理、用户的识别以及数据的补全三个处理步骤。而后根据搜集得到的数据进行整理形成了用户浏览矩阵。其次,基于数据挖掘的用户访问行为分析,采用Apriori算法作为关联规则挖掘的方法,对于用户访问行为数据进行分析。以行向量的均值以及方差作为计算阈值的参数来实施关联规则的剪枝。再次,根据挖掘得到的用户访问行为关联规则对网站结构进行优化。通过新增和删除链接的方式改变网站的链接结构,为用户提供更加符合其使用习惯的链接结构。最后,本文采用玉都商城作为实例进行了分析,采用该网站2016年9月的数据进行了数据挖掘和网站结构优化。并搜集了网站结构优化以后2016年10月的用户访问数据统计结果。根据对比结果显示,本文提出的优化方法,可以有效改善用户的网站访问体验,同时提高搜索引擎对于网站的排名。
[Abstract]:In the information age, the avalanche of the Internet has changed the way people live, work, learn and even think. And Web plays a key role. And more and more businesses are starting to set up their own home pages on the Internet, hoping to get more attention online. In order to promote the sales of products. In order to improve the ranking of websites in search engines, The core function of search engine algorithm is to find the corresponding web page according to the keywords entered by the customer. Improve the ranking of websites in search engines is very important for the value of the site itself and the corresponding business activities. And in the process of ranking the pages, Search engines have their corresponding rules, such as the frequency of keywords and links to websites. Site link structure in the corresponding optimization is conducive to the ranking of the site in the search engine. This is also the majority of commercial websites or portals in order to improve the search engine ranking commonly used in this article. Under this background, take the Yudu Mall website as an example to carry out the search engine optimization research, The data preprocessing, the mining of user access behavior rules and the link optimization based on access behavior are studied respectively. Firstly, the data preprocessing is analyzed, and the source of user network access behavior data is analyzed. This paper introduces three processing steps of data cleaning, user identification and data completion, and then forms a user browsing matrix according to the collected data. Secondly, the user access behavior analysis based on data mining is introduced. Using Apriori algorithm as association rule mining method, the user access behavior data is analyzed. The average value and variance of row vector are used as parameters to calculate threshold value to implement pruning of association rules. The structure of the web site is optimized according to the user access behavior association rules. The link structure of the website is changed by adding and deleting the link, and the link structure is more suitable for the user. Finally, This article uses the Yudu Mall as an example to carry on the analysis, The data of the website on September 2016 are used to mine the data and optimize the structure of the website. The statistical results of the user visit data on October 2016 after the optimization of the website structure are collected. According to the comparison results, the optimization method proposed in this paper is presented. Can effectively improve the user's site visit experience, at the same time improve the search engine for the site ranking.
【学位授予单位】：湖北工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP393.092;TP391.3

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