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Lectures
01 7 1 Overview Text Mining And Analytics Part 1 Tm 3 Overview
01 8 1 Syntagmatic Relation Discovery Entropy Tm 9 Syn Relation
01 9 1 Probabilistic Topic Models Mixture Of Unigram Language Models Tm 17 Mixture Model
01 10 1 Text Clustering Motivation Tm 22 Clustering
01 11 1 Text Categorization Discriminative Classifier Part 1 Tm 31 Text Cat Discrim Part1
01 12 1 Opinion Mining And Sentiment Analysis Latent Aspect Rating Analysis Part 1 Tm 38 Sentiment Lara Part1
01 Course Introduction Video 410Dso Intro
01 Lesson 1 1 Natural Language Content Analysis 1.1 Tr Natural Language Content Analysis
01 Lesson 2 1 Vector Space Model Improved Instantiation 2.1 Tr Vector Space Model Improve Instantiation
01 Lesson 3 1 Evaluation Of Tr Systems 3.1 Evaluation Of Tr Systems
01 Lesson 4 1 Probabilistic Retrieval Model Basic Idea 4.1 Probabilistic Retrieval Model Basic Idea
01 Lesson 5 1 Feedback In Text Retrieval 5.1 Feedback In Text Retrieval
01 Lesson 6 1 Learning To Rank Part 1 Optional 6.1 Learning To Rank
02 7 2 Overview Text Mining And Analytics Part 2 Tm 3 Overview 1
02 8 2 Syntagmatic Relation Discovery Conditional Entropy Tm 10 Cond Entropy
02 9 2 Probabilistic Topic Models Mixture Model Estimation Part 1 Tm 18 Mixture Model Est
02 10 2 Text Clustering Generative Probabilistic Models Part 1 Optional Tm 23 Clustering Gen Model Part1
02 11 2 Text Categorization Discriminative Classifier Part 2 Optional Tm 32 Text Cat Discrim Part2
02 12 2 Opinion Mining And Sentiment Analysis Latent Aspect Rating Analysis Part 2 Tm 39 Sentiment Lara Part2
02 Lesson 1 2 Text Access 1.2 Tr Text Access
02 Lesson 2 2 Tf Transformation 2.2 Tr Tf Transformation
02 Lesson 3 2 Evaluation Of Tr Systems Basic Measures 3.2 Evaluation Of Tr Systems Basic Measures
02 Lesson 4 2 Statistical Language Model 4.2 Statistical Language Models
02 Lesson 5 2 Feedback In Vector Space Model Rocchio 5.2 Feedback In Vector Space Model Rocchio
03 7 3 Natural Language Content Analysis Part 1 Tm 4 Nlp
03 8 3 Syntagmatic Relation Discovery Mutual Information Part 1 Tm 11 Mutual Info Corrected
03 9 3 Probabilistic Topic Models Mixture Model Estimation Part 2 Tm 18 Mixture Model Est 1
03 10 3 Text Clustering Generative Probabilistic Models Part 2 Optional Tm 24 Clustering Gen Model Part2
03 11 3 Text Categorization Evaluation Part 1 Tm 33 Text Cat Eval Part1
03 12 3 Text Based Prediction Tm 40 Prediction
03 Lesson 1 3 Text Retrieval Problem 1.3 Tr Text Retrieval Problem
03 Lesson 2 3 Doc Length Normalization 2.3 Tr Doc Length Normalization
03 Lesson 3 3 Evaluation Of Tr Systems Evaluating Ranked Lists Part 1 3.3 Evaluation Of Tr Systems Evaluating Ranked Lists Part 1
03 Lesson 4 3 Query Likelihood Retrieval Function 4.3 Query Likelihood Retrieval Function
03 Lesson 5 3 Feedback In Text Retrieval Feedback In Lm 5.3 Feedback In Language Models For Retrieval
04 7 4 Natural Language Content Analysis Part 2 Tm 4 Nlp 1
04 8 4 Syntagmatic Relation Discovery Mutual Information Part 2 Tm 11 Mutual Info Corrected 1
04 9 4 Probabilistic Topic Models Expectation Maximization Algorithm Part 1 Tm 19 Cond Entropy
04 10 4 Text Clustering Generative Probabilistic Models Part 3 Optional Tm 25 Clustering Gen Model Part3
04 11 4 Text Categorization Evaluation Part 2 Tm 34 Text Cat Eval Part2
04 12 4 Contextual Text Mining Motivation Tm 41 Contextual
04 Lesson 1 4 Overview Of Text Retrieval Methods 1.4 Tr Overview Text Retrieval Methods
04 Lesson 2 4 Implementation Of Tr Systems 2.4 Implementation Of Tr Systems
04 Lesson 3 4 Evaluation Of Tr Systems Evaluating Ranked Lists Part 2 3.4 Evaluation Of Tr Systems Evaluating Ranked Lists Part 2
04 Lesson 4 4 Statistical Language Model Part 1 4.4 Smoothing Of Language Model
04 Lesson 5 4 Web Search Introduction Web Crawler 5.4 Web Search
04 Lesson 6 4 Future Of Web Search 6.4 Future Web Search
05 7 5 Text Representation Part 1 Tm 5 Textrep
05 8 5 Topic Mining And Analysis Motivation And Task Definition Tm 12 Topic Mining Task
05 9 5 Probabilistic Topic Models Expectation Maximization Algorithm Part 2 Tm 19 Cond Entropy 1
05 10 5 Text Clustering Similarity Based Approaches Tm 26 Clustering Similarity
05 11 5 Opinion Mining And Sentiment Analysis Motivation Tm 35 Sentiment
05 12 5 Contextual Text Mining Contextual Probabilistic Latent Semantic Analysis Tm 42 Cplsa
05 Lesson 1 5 Vector Space Model Basic Idea 1.5 Tr Vector Space Model Basic Idea
05 Lesson 2 5 System Implementation Inverted Index Construction 2.5 System Implementation Inverted Index Construction
05 Lesson 3 5 Evaluation Of Tr Systems Multi Level Judgements 3.5 Evaluation Of Tr Systems Multi Level Judgements
05 Lesson 4 5 Statistical Language Model Part 2 4.5 Smoothing Of Language Model
05 Lesson 5 5 Web Indexing 5.5 Web Indexing
05 Lesson 6 5 Recommender Systems Content Based Filtering Part 1 6.5 Recommender Systems Content Based Filtering
06 7 6 Text Representation Part 2 Tm 5 Textrep 1
06 8 6 Topic Mining And Analysis Term As Topic Tm 13 Term As Topic
06 9 6 Probabilistic Topic Models Expectation Maximization Algorithm Part 3 Tm 19 Cond Entropy 2
06 10 6 Text Clustering Evaluation Tm 27 Clustering Eval
06 11 6 Opinion Mining And Sentiment Analysis Sentiment Classification Tm 36 Sentiment Method
06 12 6 Contextual Text Mining Mining Topics With Social Network Context Tm 43 Netplsa
06 Lesson 1 6 Vector Space Retrieval Model Simplest Instantiation 1.6 Tr Vector Space Model Simplest Instantiation
06 Lesson 2 6 System Implementation Fast Search 2.6 System Implementation Fast Search
06 Lesson 3 6 Evaluation Of Tr Systems Practical Issues 3.6 Evaluation Of Tr Systems Practical Issues
06 Lesson 4 6 Smoothing Methods Part 1 4.6 Smoothing Methods Jelinek Mercer And Dirichlet Prior
06 Lesson 5 6 Link Analysis Part 1 5.6 Link Analysis
07 7 7 Word Association Mining And Analysis Tm 6 Word Relation Corrected
07 8 7 Topic Mining And Analysis Probabilistic Topic Models Tm 14 Topic Model
07 9 7 Probabilistic Latent Semantic Analysis Plsa Part 1 Tm 20 Plsa
07 10 7 Text Categorization Motivation Tm 28 Text Cat
07 11 7 Opinion Mining And Sentiment Analysis Ordinal Logistic Regression Optional Tm 37 Sentiment Ordinal
07 12 7 Contextual Text Mining Mining Causal Topics With Time Series Supervision Tm 44 Causal
07 Lesson 4 7 Smoothing Methods Part 2 4.7 Smoothing Methods Jelinek Mercer And Dirichlet Prior
07 Lesson 6 7 Recommender Systems Collaborative Filtering Part 1 6.7 Recommender Systems Collaborative Filtering
08 7 8 Paradigmatic Relation Discovery Part 1 Tm 78 Para Relation
08 8 8 Probabilistic Topic Models Overview Of Statistical Language Models Part 1 Tm 15 Language Model
08 9 8 Probabilistic Latent Semantic Analysis Plsa Part 2 Tm 20 Plsa 1
08 10 8 Text Categorization Methods Tm 29 Text Cat Methods
08 12 8 Summary For Exam 2 Tm 45 Summary
09 7 9 Paradigmatic Relation Discovery Part 2 Tm 78 Para Relation 1
09 8 9 Probabilistic Topic Models Overview Of Statistical Language Models Part 2 Tm 15 Language Model 1
09 9 9 Latent Dirichlet Allocation Lda Part 1 Tm 21 Lda
09 10 9 Text Categorization Generative Probabilistic Models Tm 30 Text Cat Model
10 8 10 Probabilistic Topic Models Mining One Topic Tm 16 One Topic
10 9 10 Latent Dirichlet Allocation Lda Part 2 Tm 21 Lda 1
10 Lesson 6 10 Summary For Exam 1 6.10 Course Summary
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Cs 410
Lecture Video
Cs 410 01_7-1-Overview-Text-Mining-And-Analytics-Part-1_tm-3-Overview Slide0
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Cs 410 : 02 7 2 Overview Text Mining And Analytics Part 2 Tm 3 Overview 1 Slide0
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Cs 410 : 05 7 5 Text Representation Part 1 Tm 5 Textrep Slide0
Cs 410 : 06 7 6 Text Representation Part 2 Tm 5 Textrep 1 Slide0
Cs 410 : 04 12 4 Contextual Text Mining Motivation Tm 41 Contextual Slide0
Cs 410 : 01 10 1 Text Clustering Motivation Tm 22 Clustering Slide0
Cs 410 : 07 7 7 Word Association Mining And Analysis Tm 6 Word Relation Corrected Slide0
Cs 410 : 08 10 8 Text Categorization Methods Tm 29 Text Cat Methods Slide0
Cs 410 : 05 10 5 Text Clustering Similarity Based Approaches Tm 26 Clustering Similarity Slide0