Media Summary: 04:11 Standing queries 07:55 Text Classification 22:48 Categorization/Classification 27:27 Machine Learning : supervised ... 00:45 Recap 18:30 Computing cosine scores 25:00 Tf-Idf variants 28:06 tf-idf example 37:43 Introducing a bug 47:00 Efficient ... 00:00 Recap 07:40 Initial stages of text processing 09:18 Indexer steps :Dictionary and Postings 11:45 How to process a query ...
Web Information Retrieval Prof L - Detailed Analysis & Overview
04:11 Standing queries 07:55 Text Classification 22:48 Categorization/Classification 27:27 Machine Learning : supervised ... 00:45 Recap 18:30 Computing cosine scores 25:00 Tf-Idf variants 28:06 tf-idf example 37:43 Introducing a bug 47:00 Efficient ... 00:00 Recap 07:40 Initial stages of text processing 09:18 Indexer steps :Dictionary and Postings 11:45 How to process a query ... 00:11 Recall the basic indexing pipelining 02:12 Parsing a document 03:45 Classification Problem 05:27 Character encoding ... 00:00 SpamAssassin 04:08 Evaluating Categorization 13:50 Classification using Vector Spaces 31:00 Definition of centroid 34:24 ... 00:00 Some problems with PageRank 02:53 Trust Rank 04:40 Hubs and Authorities 10:13 Counting in-links :Authority 14:13 ...
00:00 Links as votes 07:31 PageRank :Matrix Formulation 12:41 Why power iteration works?(2) 13:54 pageRank :3 Questions ... 00:00 Analysis 04:06 Some Problems with page Rank 15:16 Random Teleports(\beta = 0.8)&The complete algorithm 15:31 ... 00:00 Solution :AlwaysTeleport 08:41 Why is this Analogy useful? 26:13 Make M Stochastic 30:50 Make M Aperiodic 30:59 Make ... 02:36 Analysis of large graphs : Link Analysis,page Rank 07:06 Graph Data:Media Networks 11:10 Broad Question 16:48 00:00 Visualization 04:20 General Variants 04:52 Parametric and zone indexes 08:00 Example on zone indexes 10:16 Example ... 00:00 Continue Bayes' law for text classification 16:05 The Multivariate Bernouli NB classifier 27:12 Learning the Model 37:05 ...
