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Description: 主要关于web使用挖掘的介绍，非常不错的文章。-mainly on the use of web mining, a very good article.
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Size: 13426 |
Author: 杨颂 |
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Description: 介绍数据挖掘中的web挖掘，基本含义，策略及步骤-introduced the Data Mining web mining, basic meaning, strategy and steps
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Size: 388170 |
Author: kiki |
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Description: 基于svm的WEB数据挖掘的文档，SVM的方法开辟了学习高维数据新的天地，为WEB数据开发提供了一个先进的思路。-svm Web-based data mining documents, SVM method opened up a high-dimensional data learning new vista for the development of Web data provided an advanced ideas.
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Size: 1837056 |
Author: 邢军 |
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Description: 主要关于web使用挖掘的介绍，非常不错的文章。-mainly on the use of web mining, a very good article.
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Size: 13312 |
Author: 杨颂 |
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Description: 一个基于Web 链接挖掘和内容相关性分析的智能信息检索系统-links to a Web-based mining and content analysis of the Intelligent Information Retrieval System
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Size: 131072 |
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Description: 主要应用Java进行的的web data Mining 的参考资料，有XSLT/XSL/XPath相关技术！-major applications for the Java web Mining reference data, XSLT/XSL/XPath related technology!
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Size: 535552 |
Author: 徐广贤 |
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Description: 用于数据挖掘，根据日志文件的格式把web日志导入到数据库中，-for data mining, according to the log file format on the web log into the database,
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Size: 39936 |
Author: 陈妍 |
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Description: 介绍数据挖掘中的web挖掘，基本含义，策略及步骤-introduced the Data Mining web mining, basic meaning, strategy and steps
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Size: 388096 |
Author: kiki |
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Description: Web数据挖掘ID3算法源码,使用C++语言编写而成，具有高效性。-Web data mining ID3 algorithm source, the use of C language, prepared with high efficiency.
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Size: 538624 |
Author: 武夷河 |
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Description: 一个关于web mining的ppt ,是中科院计算所的-one on the web mining ppt, is calculated by the Chinese Academy of Sciences
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Size: 13312 |
Author: 陈颍 |
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Description: 挖掘Web中的信息，经典的数据挖掘和文本挖掘书籍，为亚马逊书刊中数据挖掘类畅销书。
其中介绍如何在超文本格式下挖掘文本信息，抓取网页，机器学习，等进行网页挖掘的关键技术-Mining Web information, classical data mining and text mining books, Amazon books for Data Mining Bestsellers. Describing how the hypertext format text mining information, crawls website, machine learning, Mining and other web key technologies
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Size: 1516544 |
Author: 甘亮 |
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Description: Web使用挖掘技术研究-Web Usage Mining Research
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Size: 184320 |
Author: chen |
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Description: 讲述数据挖掘的理论，以及关联规则的详细介绍和实现算法-On data mining theory, association rules, as well as a detailed introduction and realization of algorithms
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Size: 14336 |
Author: 王鱼 |
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Description: 这是一篇博士论文,主要描述Web挖掘中涉及对一些经典问题的看法,是写得比较细的论文.-This is a doctoral thesis, the main description of Web mining involves a number of classic issues, is written in relatively thin paper.
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Size: 1008640 |
Author: 张明 |
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Description: Web挖掘技术在搜索引擎中的应用与实现
介绍了PageRange , 结构挖掘器 , 页面分析器,中文分词等技术-Web mining technology in search engine applications and realize the introduction PageRange, structure mining, and Page Analyzer, Chinese word segmentation techniques
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Size: 249856 |
Author: he |
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Description: web分类系统 Web文档分类是Web挖掘中最基本的技术之一,而构造一个按照兴趣分类的分类器,需要做大量的预处理工作,来收集正负的训练样例。但负例的收集是非常困难的。文章提出了一个只有正例没有负例的学习模型。该模型主要是重复执行SVM。实验表明,该学习模型对于Web文档分类的分类精度和速度都是非常理想的-web classification system for Web document classification is a Web mining, one of the most basic skills, but to construct a classifier classified according to interest, need to do a lot of pre-processing work to collect the training sample of plus or minus. However, the collection of negative cases is very difficult. This paper presents a no negative cases only the positive cases of the learning model. The model is mainly repeat the SVM. Experiments show that the learning model for Web document categorization classification accuracy and speed are very good
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Size: 1232896 |
Author: huihui |
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Description: it is method to for web mining
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Size: 172032 |
Author: ashwini |
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Description: Web数据挖掘(世界著名计算机教材精选),作者BingLiu刘冰
刘兵(BingLiu)，伊利诺伊大学芝加哥分校(UIC)教授，他在爱丁堡大学获得人工智能博士学位。刘兵教授是Web挖掘研究领域的国际知名专家，在Web内容挖掘、互联网观点挖掘、数据挖掘等领域有非常高的造诣，他先后在国际著名学术期刊与重要国际学术会议(如KDD、WWW、AAAI、SIGIR、ICML、TKDE等)上发布关于数据挖掘、Web挖掘和文本挖掘论文一百多篇。刘兵教授担任过多个国际期刊的编辑，也是多个国际学术会议(如WWW、KDD与AAAI等)的程序委员会委员。
本书旨在阐述web数据挖掘的概念及其核心算法，使读者获得相对完整的关于web数据挖掘的算法和技术知识。本书不仅介绍了搜索、页面爬取和资源探索以及链接分析等传统的Web挖掘主题，而且还介绍了结构化数据的抽取、信息整合、观点挖掘和Web使用挖掘等内容，这些内容在已有书籍中没有提及过，但它们在Web数据挖掘中却占有非常重要的地位。全书分为两大部分：第一部分包括第2章到第5章，介绍数据挖掘的基础；第二部分包括第6章到第12章，介绍Web相关的挖掘任务。
-Web data mining (world-renowned computer materials selection), the authors BingLiu Liu Bing
Liu Bing (BingLiu), University of Illinois at Chicago (UIC) professor, Ph.D. in Artificial Intelligence at Edinburgh University. Professor Liu Bing is the field of Web mining research internationally renowned expert in Web content mining, Internet, view mining, data mining and other areas have very high attainments, he worked in internationally renowned academic journals and major international conferences (such as KDD, WWW, AAAI, SIGIR, ICML, TKDE, etc.) on the release of data mining, Web mining and text mining papers more than a hundred articles. Professor Liu Bing served as editor of several international journals, but also a number of international conferences (such as WWW, KDD and AAAI, etc.) of the Program Committee.
This book seeks to explain the concept and web data mining of the core algorithm, so that readers gain a relatively complete information on web data mining algorithms
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Size: 3355648 |
Author: 陈东 |
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Description: 这是一本关于web data mining的书籍。既适合初学者，也适合有一定基础的人群。作者刘兵是Web挖掘研究领域的国际知名专家，在Web内容挖掘、互联网观点挖掘、数据挖掘等领域有非常高的造诣。-This is a book about web data mining. Not only for beginners, but also the basis for a certain crowd. Bing is the author of Web mining research internationally renowned expert in Web content mining, Internet, view mining, data mining and other areas have very high attainments.
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Size: 8485888 |
Author: 郑牟 |
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Description: Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user’s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. In this article we present a survey of the use of Web mining for Web personalization. More specifically, we introduce the modules that comprise a Web personalization system, emphasizing the Web usage mining module. A review of the most common methods that are used as well as technical issues that occur is given, along with a brief overview of the most popular tools and applications available from software vendors. Moreover, the most important research initiatives in the Web usage mining and personalization areas are presented.,Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user’s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. In this article we present a survey of the use of Web mining for Web personalization. More specifically, we introduce the modules that comprise a Web personalization system, emphasizing the Web usage mining module. A review of the most common methods that are used as well as technical issues that occur is given, along with a brief overview of the most popular tools and applications available from software vendors. Moreover, the most important research initiatives in the Web usage mining and personalization areas are presented.
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Size: 400384 |
Author: khan |
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