网络信息的特点在于: Query: "IBM" --> "Computer" --> documentIDs. In degree i 正比于 1/iα ,  例如: α = 2.1 即:i越大,量越少. Query processing §  First retrieve all pages meeting the text query (say venture capital). §  Order these by their link popula…

http://blog.csdn.net/pipisorry/article/details/48579435 海量数据挖掘Mining Massive Datasets(MMDs) -Jure Leskovec courses学习笔记之链接分析:PageRank算法 链接分析与PageRank {大图分析the Analysis of Large Graphs} how the class fits together 图数据的例子 社交网络Social Networks(Facebook so…

Ref: [IR] Compression Ref: [IR] Link Analysis Planar Graph From: http://www.csie.ntnu.edu.tw/~u91029/PlanarGraph.html#1 由於缺乏優美規律,因此談論對偶圖時,習慣忽略同構. 最特別的對偶圖例子,就是橋( bridge )與自環( loop ). 舉例來說,原圖是一棵樹,對偶圖是一個點以及一大堆自環:各種樹對應各種自環包覆方式. Spanning Tree From: http:/…

Relevant Readable Links Name Interesting topic Comment Edwin Chen 非参贝叶斯   徐亦达老板 Dirichlet Process 学习目标:Dirichlet Process, HDP, HDP-HMM, IBP, CRM Alex Kendall Geometry and Uncertainty in Deep Learning for Computer Vision 语义分割 colah's blog Feature Visu…

阶段性总结 Boolean retrieval 单词搜索 [Qword1 and Qword2]               O(x+y) [Qword1 and Qword2]- 改进: Galloping Search   O(2a*log2(b/a)) [Qword1 and not Qword2]        O(m*log2n)  [Qword1 or not Qword2]           O(m+n) [Qword1 and Qword2 and Qword3 and ...…

***Search Engine Basics*** *Understanding How Vertical Results Fit into the SERPs* As a direct consequence, site owners and web marketers must take into account how this incorporation of vertical search results may impact their rankings and traffic.…

http://exploredegrees.stanford.edu/coursedescriptions/cs/ CS 101. Introduction to Computing Principles. 3-5 Units. Introduces the essential ideas of computing: data representation, algorithms, programming "code", computer hardware, networking, s…

中心词抽取项目总结 B2B国际站Query重写.ppt 达观数据搜索引擎的Query自动纠错技术和架构详解 Natural Language Processing Simrank++ Query rewriting through link analysis of the click graph Probabilistic Query Rewriting for Efficient and Effective Keyword Search on Graph Data.1642-1653 Deep…

10月15日,Cellebrite公司对旗下产品进行了更新,包括UFED Classic.UFED Touch.Physical Analyzer.Logical Analyzer.Phone Detective. UFED Reader以及Link Analysis. Release Note下载…

一.前沿 数据挖掘就是从大量的.不完全的.有噪声的.模糊的.随机的数据中,提取隐含在其中的.人们事先不知道的但又是潜在有用的信息和知识的过程.数据挖掘的任务是从数据集中发现模式,可以发现的模式有很多种,按功能可以分为两大类:预测性(Predictive)模式和描述性(Descriptive)模式.在应用中往往根据模式的实际作用细分为以下几种:分类,估值,预测,相关性分析,序列,时间序列,描述和可视化等. 数据挖掘涉及的学科领域和技术很多,有多种分类法.根据挖掘任务分,可分为分类或预测模型发现.数…