Web Search and Text Mining

CS 8803 WST: Web Search and Text Mining

Fall, 2007

Lecture: 3 hours, TR 3:05pm - 4:25pm, Howey (Physics) L3

Office hours: T 1:30pm - 2:30pm.

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

Course Description

We all have experience using search engines: typing a query into the search box and browsing the result sets to narrow down to the documents we need. In fact, Web search is the most popular online activities second only to email use, and it drives the business of some of the most successful Web companies such as Google and Yahoo! Commercial search engines are complicated engineering systems, and one of the purposes of this course is to take you behind the scenes to explore the enabling scientific and algorithmic advances. Besides issues in Web search, we will also explore other text mining methods such as document clustering and classification, information extraction, and many other ways to process and analyze free-text data and their use in bioscience and health information technology. We will start with very basic notions in information retrieval at a fairly slow pace, explain some of the fundamental algorithms, and eventually touch upon the research frontiers. The prerequisites for this course are very modest, basic exposure to computing and algorithms, and basic knowledge of calculus, linear algebra and statistics. The course will also have some programming assignments.

List of Topics

Introductory IR: inverted indices, query processing, tf-idf weighting, scoring, precision and recall, DCG
IR models: vector space models, probabilistic models, and language modeling methods
Machine learning methods for designing ranking functions
Link analysis: PageRank and HITS algorithms
Implicit relevance feedback using user click data
Social search, community discovery, exploring user tags
Search results summarization and clustering
Query re-writing, spelling corrections
Question answering
Document classification and clustering, applications in ED chief complaints and bio-surveillance
Information extraction, applications in electronic medical records management
Spam filtering methods

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