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464.561A / Models and Technologies for Information Services, Spring 2011
♦ CALENDAR
WEEK # TOPICS DETAILS
1 Course overview/Paper assignment
Mathematical foundations
2 Mathematical foundations
A vector space approach to tag cloud similarity ranking
Online Video Recommendation through Tag-Cloud Aggregation
3 SimRank: A Measure of Structural-Context Similarity
Automatic Generation of Overview Timelines
Hidden Markov Models
4 Hidden Markov Models
Learning Hidden Markov Model Structure for Information Extraction
Credit Card Fraud Detection Using Hidden Markov Model
5 Fast Inference and Learning in Large-State-Space HMMs
A Hidden Markov Model of Customer Relationship Dynamics
VOGUE: A Variable Order Hidden Markov Model with Duration Based on Fre-quent Sequence Mining
Bursty and Hierarchical Structure in Streams
6 Linear Discrimination and SVMs
7 Searching Social Media Streams on the Web
Finding Advertising Keywords on Web Pages
Optimizing Search Engines using Clickthrough Data
Hierarchical Document Categorization with Support Vector Machines
8 Predicting Structured Objects with Support Vector Machines
Hidden Markov Support Vector Machines
Latent Dirichlet Allocation
9 Dynamic Topic Models
Topics over Time: A Non-Markov Continuous-Time Model of Topical Trends
Continuous Time Dynamic Topic Models
Characterizing Microblogs with Topic Models
10 Latent Semantic Analysis
Cluster-Based FAQ Retrieval Using Latent Term Weights
Latent Semantic Models for Collaborative Filtering
11 Term Project Proposals
12 (Near) Final Exam
Mining Correlated Bursty Topic Patterns from Coordinated Text Streams
Tracking Dynamics of Topic Trends Using a Finite Mixture Model
13 Applications of Statistical Learning Methods in Practice
14 Applications of Text Mining Techniques in Practice
15 Final Term Project Presentations & Demo
Seoul National University, San 56-1. Sillim-dong, Gwanak-gu.Seoul 151-742 Korea
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