Web数据挖掘与Web使用分析进展/Advances in web mining and web usage analysis 下载 kindle 电子版 pdf mobi pmlz 夸克云 caj

Web数据挖掘与Web使用分析进展/Advances in web mining and web usage analysis精美图片
》Web数据挖掘与Web使用分析进展/Advances in web mining and web usage analysis电子书籍版权问题 请点击这里查看《

Web数据挖掘与Web使用分析进展/Advances in web mining and web usage analysis书籍详细信息

  • ISBN:9783540463467
  • 作者:暂无作者
  • 出版社:暂无出版社
  • 出版时间:2006-12
  • 页数:176
  • 价格:417.60
  • 纸张:胶版纸
  • 装帧:平装
  • 开本:暂无开本
  • 语言:未知
  • 丛书:暂无丛书
  • TAG:暂无
  • 豆瓣评分:暂无豆瓣评分
  • 豆瓣短评:点击查看
  • 豆瓣讨论:点击查看
  • 豆瓣目录:点击查看
  • 读书笔记:点击查看
  • 原文摘录:点击查看

内容简介:

This book constitutes the thoroughly refereed post-proceedings of the 7th International Workshop on Mining Web Data, WEBKDD 2005, held in Chicago, IL, USA in August 2005 in conjunction with the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2005.

The 9 revised full papers presented together with a detailed preface went through two rounds of reviewing and improvement and were carfully selected for inclusion in the book. The enhanced papers show that Web mining techniques and applications have to more effectively integrate a variety of types of data across multiple channels and from different sources in addition to usage, such as content, structure, and semantics. Thus a next generation of intelligent applications is stimulated for more effective exploitation and mining of multi-faceted data. The papers express also the need to study and design robust recommender systems that can resist various malicious manipulations.


书籍目录:

Mining Significant Usage Patterns from Clickstream Data

Using and Learning Semantics in Frequent Subgraph Mining

Overcoming Incomplete User Models in Recommendation Systems Via an Ontology

Data Sparsity Issues in the Collaborative Filtering Framework

USER: User-Sensitive Expert Recommendations for Knowledge-Dense Environments

Analysis and Detection of Segment-Focused Attacks Against Collaborative Recommendation

Adaptive Web Usage Profiling

On Clustering Techniques for Change Diagnosis in Data Streams

Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks

Author Index


作者介绍:

暂无相关内容,正在全力查找中


出版社信息:

暂无出版社相关信息,正在全力查找中!


书籍摘录:

暂无相关书籍摘录,正在全力查找中!



原文赏析:

暂无原文赏析,正在全力查找中!


其它内容:

编辑推荐

The LNAI series reports state-of-the-art results in artificial intelligence re-search, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNAI has grown into the most comprehensive artificial intelligence research forum available.

The scope of LNAI spans the whole range of artificial intelligence and intelli- gent information processing including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes.

proceedings (published in time for the respective conference);

post-proceedings (consisting of thoroughly revised final full papers);

research monographs (which may be based on PhD work).



书籍真实打分

  • 故事情节:7分

  • 人物塑造:6分

  • 主题深度:5分

  • 文字风格:7分

  • 语言运用:4分

  • 文笔流畅:9分

  • 思想传递:5分

  • 知识深度:7分

  • 知识广度:9分

  • 实用性:4分

  • 章节划分:7分

  • 结构布局:9分

  • 新颖与独特:8分

  • 情感共鸣:3分

  • 引人入胜:6分

  • 现实相关:7分

  • 沉浸感:4分

  • 事实准确性:9分

  • 文化贡献:3分


网站评分

  • 书籍多样性:6分

  • 书籍信息完全性:8分

  • 网站更新速度:7分

  • 使用便利性:9分

  • 书籍清晰度:3分

  • 书籍格式兼容性:9分

  • 是否包含广告:9分

  • 加载速度:9分

  • 安全性:5分

  • 稳定性:4分

  • 搜索功能:7分

  • 下载便捷性:4分


下载点评

  • 值得下载(196+)
  • azw3(337+)
  • 赞(639+)
  • 章节完整(652+)
  • mobi(236+)
  • 体验还行(82+)
  • 一般般(407+)
  • 图文清晰(632+)

下载评价

  • 网友 常***翠:

    哈哈哈哈哈哈

  • 网友 薛***玉:

    就是我想要的!!!

  • 网友 步***青:

    。。。。。好

  • 网友 师***怡:

    说的好不如用的好,真心很好。越来越完美

  • 网友 汪***豪:

    太棒了,我想要azw3的都有呀!!!

  • 网友 屠***好:

    还行吧。

  • 网友 邱***洋:

    不错,支持的格式很多

  • 网友 陈***秋:

    不错,图文清晰,无错版,可以入手。

  • 网友 瞿***香:

    非常好就是加载有点儿慢。

  • 网友 隗***杉:

    挺好的,还好看!支持!快下载吧!

  • 网友 丁***菱:

    好好好好好好好好好好好好好好好好好好好好好好好好好

  • 网友 寿***芳:

    可以在线转化哦

  • 网友 冉***兮:

    如果满分一百分,我愿意给你99分,剩下一分怕你骄傲

  • 网友 晏***媛:

    够人性化!


随机推荐