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Web挖掘

Web Mining
课程网址: http://videolectures.net/ijcai2011_t16_mining/  
主讲教师: Ricardo Baeza-Yates, Aris Gionis
开课单位: 巴塞罗那研究中心
开课时间: 2011-08-23
课程语种: 英语
中文简介:
网络继续发展和快速发展,改变了我们的日常生活。此活动代表了数百万为网络贡献内容的机构和人员以及使用它的10亿人的协作工作。在这个超链接数据的海洋中,存在明确和隐含的信息和知识。 Web挖掘的任务是分析此数据并为许多不同目的提取信息和知识。数据有三种主要形式:内容(文本,图像等),结构(超链接)和用法(导航,查询等),暗示不同的技术,如文本,图形或日志挖掘。每个案例都反映了可以用来改善Web的某些人的智慧,例如,Web 2.0站点中用户生成的标签。在本教程中,我们将介绍挖掘过程,并将展示从Web站点设计到搜索引擎的多个应用程序。主要目标是向人工智能研究人员介绍Web挖掘中的无数挑战,除了机器学习之外,其他AI技术可能也适用。
课程简介: The Web continues to grow and evolve very fast, changing our daily lives. This activity represents the collaborative work of the millions of institutions and people that contribute content to the Web as well as the one billion people that use it. In this ocean of hyperlinked data there is explicit and implicit information and knowledge. Web Mining is the task of analyzing this data and extracting information and knowledge for many different purposes. The data comes in three main flavors: content (text, images, etc.), structure (hyperlinks) and usage (navigation, queries, etc.), implying different techniques such as text, graph or log mining. Each case reflects the wisdom of some group of people that can be used to make the Web better, for example, user generated tags in Web 2.0 sites. In this tutorial we will walk through the mining process and will show several applications, ranging from Web site design to search engines. The main goal is to introduce AI researchers to the myriad of challenges in Web mining, where other AI techniques, in addition to machine learning, might be applicable.
关 键 词: 超链接数据; 贡献内容; 提取信息
课程来源: 视频讲座网
最后编审: 2020-06-12:章泽平(课程编辑志愿者)
阅读次数: 138