Text Mining and Analytics

Topics

• x y can (Confusion: 2453.0)
• paradigmatic/syntagmatic relations (Confusion: 2399.27)
• information entropy (Confusion: 2311.87)
• entropi variabl predict (Confusion: 2267.47)
• generative (Confusion: 1996.98)
• music cours theta (Confusion: 1873.73)
• classification (Confusion: 1735.4)
• probabilistic model (Confusion: 1731.38)
• probabl word distribut (Confusion: 1676.28)
• can represent text (Confusion: 1567.53)
• data model use (Confusion: 1361.11)
• retrieval model (Confusion: 1231.92)
• topic can time (Confusion: 1150.22)
• topic model (Confusion: 1020.08)
• opinion rate can (Confusion: 833.982)

Lectures

• 1.1 Overview Text Mining and Analytics: Part 1 (00:11:43)
• 1.10 Syntagmatic Relation Discovery: Entropy (00:11:00)
• 1.11 Syntagmatic Relation Discovery: Conditional Entropy (00:11:57)
• 1.12 Syntagmatic Relation Discovery: Mutual Information: Part 1 (00:13:55)
• 1.13 Syntagmatic Relation Discovery: Mutual Information: Part 2 (00:09:42)
• 1.2 Overview Text Mining and Analytics: Part 2 (00:11:44)
• 1.3 Natural Language Content Analysis: Part 1 (00:12:48)
• 1.4 Natural Language Content Analysis: Part 2 (00:04:25)
• 1.5 Text Representation: Part 1 (00:10:46)
• 1.6 Text Representation: Part 2 (00:09:29)
• 1.7 Word Association Mining and Analysis (00:15:39)
• 1.8 Paradigmatic Relation Discovery Part 1 (00:14:31)
• 1.9 Paradigmatic Relation Discovery Part 2 (00:17:53)
• 2.1 Topic Mining and Analysis: Motivation and Task Definition (00:07:36)
• 2.10 Probabilistic Topic Models: Expectation-Maximization Algorithm: Part 1 (00:11:05)
• 2.11 Probabilistic Topic Models: Expectation-Maximization Algorithm: Part 2 (00:10:39)
• 2.12 Probabilistic Topic Models: Expectation-Maximization Algorithm: Part 3 (00:06:25)
• 2.13 Probabilistic Latent Semantic Analysis (PLSA): Part 1 (00:10:38)
• 2.14 Probabilistic Latent Semantic Analysis (PLSA): Part 2 (00:10:15)
• 2.15 Latent Dirichlet Allocation (LDA): Part 1 (00:10:20)
• 2.16 Latent Dirichlet Allocation (LDA): Part 2 (00:12:03)
• 2.2 Topic Mining and Analysis: Term as Topic (00:11:31)
• 2.3 Topic Mining and Analysis: Probabilistic Topic Models (00:14:17)
• 2.4 Probabilistic Topic Models: Overview of Statistical Language Models: Part 1 (00:10:25)
• 2.5 Probabilistic Topic Models: Overview of Statistical Language Models: Part 2 (00:13:11)
• 2.6 Probabilistic Topic Models: Mining One Topic (00:12:21)
• 2.7 Probabilistic Topic Models: Mixture of Unigram Language Models (00:12:39)
• 2.8 Probabilistic Topic Models: Mixture Model Estimation: Part 1 (00:10:16)
• 2.9 Probabilistic Topic Models: Mixture Model Estimation: Part 2 (00:08:15)
• 3.1 Text Clustering: Motivation (00:15:52)
• 3.10 Text Categorization: Discriminative Classifier Part 1 (00:20:34)
• 3.11 Text Categorization: Discriminative Classifier Part 2 (00:31:46)
• 3.12 Text Categorization: Evaluation Part 1 (00:14:12)
• 3.13 Text Categorization: Evaluation Part 2 (00:10:51)
• 3.2 Text Clustering: Generative Probabilistic Models Part 1 (00:16:18)
• 3.3 Text Clustering: Generative Probabilistic Models Part 2 (00:08:37)
• 3.4 Text Clustering: Generative Probabilistic Models Part 3 (00:14:55)
• 3.5 Text Clustering: Similarity-based Approaches (00:17:48)
• 3.6 Text Clustering: Evaluation (00:10:11)
• 3.7 Text Categorization: Motivation (00:14:37)
• 3.8 Text Categorization: Methods (00:11:50)
• 3.9 Text Categorization: Generative Probabilistic Models (00:31:18)
• 4.1 Opinion Mining and Sentiment Analysis: Motivation (00:17:51)
• 4.10 Contextual Text Mining: Mining Casual Topics with Time Series Supervision (00:19:37)
• 4.11 Course Summary (00:18:36)
• 4.2 Opinion Mining and Sentiment Analysis: Sentiment Classification (00:11:47)
• 4.3 Opinion Mining and Sentiment Analysis: Ordinal Logistic Regression (00:13:43)
• 4.4 Opinion Mining and Sentiment Analysis: Latent Aspect Rating Analysis Part 1 (00:15:17)
• 4.5 Opinion Mining and Sentiment Analysis: Latent Aspect Rating Analysis Part 2 (00:14:43)
• 4.6 Text-Based Prediction (00:12:08)
• 4.7 Contextual Text Mining: Motivation (00:06:47)
• 4.8 Contextual Text Mining: Contextual Probabilistic Latent Semantic Analysis (00:17:59)
• 4.9 Contextual Text Mining: Mining Topics with Social Network Context (00:14:43)
• Course Prerequisites & Completion (00:09:02)
• Text Mining and Analytics (00:08:15)