Web Search and Text Mining

CSE6240: Web Search and Text Mining

Spring, 2012

Lecture: TR 9:35pm - 10:55pm

Office hours: T 1:00pm - 2:00pm.

Instructor: Hongyuan Zha, Office: 1314 KACB, Phone: 404-385-1491

Course Description

This course will cover the data analytic aspects of three closely related topics: Web search, recommendation systems and social network analysis. The emphasis is on probabilistic and statistical methods, user behavior modeling, and dyanmic behavior and structure co-evolution in social networks. Ideally you should have formal exposure to data mining and machine learning at the level of CSE6740 and be comfortable with using a script and/or high-level language.

List of Topics

Introductoion on IR: inverted indices, query processing, tf-idf weighting, scoring, anchor texts, precision and recall, DCG
Link analysis: PageRank and HITS algorithms
Learning to rank methods
Implicit relevance feedback using user click and behavior data
Search result diversity
Latent dirichlet allocation and extensions
Instroduction on RS: Content-based recommendations, collaborative recommendations, user and item-based methods, matrix factorization, evaluation
Matrix factorization and item/user features
Cold start problems in collaborative filtering
Local, mobile and collaborative filtering
Incorporating multiple data sources in collaborative filtering
Strong and weak ties in social networks
Inferring signed relations from user behavior
Diffusion in nteworks and small-world phenomenon
Survival and event history analysis
Structure and behavior co-evolution
Epidemics and structure discovery from user behavior

Class Policies

Please let me know as soon as possible if you have any special needs during the semester.
Each student must read and abide by the Georgia Tech Academic Honor Code.

Grading