1. Course Summary (Lecture for CS410 Intro Text Info Systems)
April 25, 2007
ChengXiang Zhai
Department of Computer Science
University of Illinois, Urbana-Champaign

2. Elements of Text Information Management Technology
Retrieval
Applications
Summarization
Visualization
Mining
Applications
Filtering
Mining
Information
Organization
Information
Access
Knowledge
Acquisition
Search
Extraction
Categorization
Clustering
Natural Language Content Analysis
Text

3. Topics Covered in the Course
Applications
Web Search Engines, Inteface/visulization
Structured IR (intra-doc, inter-doc, link analysis)
Text Access Techniques
Text Mining Techniques
Retrieval models
(VS, Prob., LM)
IR system implementation
Feedback (Rocchio, Mixture)
Filtering(Adaptive, Collab.)
HMMs
Categorization (Naïve Bayes)
Clustering (Mixture model)
Statistical LMs, Smoothing, EM
NLP Techniques
Text

4. A quick review of all the topics…

5. What We Haven’t Covered
Read literature
Go & Build Tools!
Applications
Many Web Applications, Digital Libraries
Domain-Specific Content Management (Legal & Bioinformatics)
Text Access Techniques
Text Mining Techniques
Discriminative Classifiers (SVM,..)
Information Extraction
(e.g., definition/hyponym mining)
Sophisticated Statistical Models
and Parameter Estimation
Multimedia Retrieval (Image, Video…)
Cross-Language Retrieval
Distributed/P2P Retrieval
Read IR Literature
In-depth NLP Techniques
(e.g., sense disambiguation, parsing)
NLP Techniques
Take a Machine
Learning Course
(& a Statistics Course)
Text
Take an NLP Course

6. Data/Info Integration
What to Learn/Do Next?
Applications
Applications
Models
Applications
Web, Bioinformatics…
User Models
Machine Learning
Pattern Recognition
Data Mining
Library & Info
Science
Statistics
Optimization
Foundation
Information
Retrieval
Data/Info Integration
Databases
Natural
Language
Processing
System Development
Software engineering
Computer systems
Algorithms
Systems

7. What to Read? Learning/Mining Applications Info. Science
ICML
ISMB
WWW
ICML, NIPS, UAI
RECOMB, PSB
Info. Science
KDD, ICDM, SDM
Info Retrieval
Statistics ??
ASIS
JCDL
AAAI
ACM SIGIR
HLT
Databases
NLP
ACM CIKM, TREC
ACL
ACM SIGMOD
COLING, EMNLP, ANLP
VLDB, PODS, ICDE
Software/systems ??

8. Some Relevant UIUC Courses
CS 446: Machine Learning and Pattern Recognition
ECE 494: Mathematical Models of Language
CS598 DNR: Machine Learning and Natural Language
CS412: An Introduction to Data Warehousing and Data Mining
CS512: Data Mining: Principles and Algorithms
CS511: Design of Database Management Systems
Many “advanced topics” courses by DAIS/AI faculty
Also, check out courses in statistics, ECE, GSLIS, and Linguistics…

9. How to… Get a job in Google/Yahoo/Microsoft/…?
Get to a top graduate program?
Publish papers in related areas?
Information retrieval
Natural language processing
Data mining
Databases
World wide web … ?

10. Good Luck!