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MIS 510 "Web Computing and Mining"

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This course introduces web computing and mining algorithms that are suitable for developing web-based information systems in e-commerce, search engines, digital libraries, knowledge management systems, web/data/text mining, business intelligence, national security, and biomedical informatics. The course contains lectures, readings, programming assignment, lab sessions, and a large hands-on group system development project. The course will cover web mining, data mining, and text mining. In web mining, we will introduce web architecture, search engines, search algorithms, web services, Web 2.0, and virtual worlds.

State of the art data and text mining algorithms are discussed in the context of modern and emerging information systems in business, engineering, intelligence, and biomedical informatics. Selected data mining algorithms such as neural networks, decision trees, genetic algorithms, statistical learning, and social network analysis will be presented for clustering, database segmentation, classification, open analytics, and collaboration problems. Information retrieval, natural language processing, sentiment analysis, and authorship analysis will be discussed in text mining, especially for emerging business and market intelligence applications.

Web Mining Project Resources (Past Classes)

Projects and presentations from past classes

Syllabus and Other Important Materials (Spring 2012)

1. MIS 510 Syllabus



2. TA Office Hours:
   Jonathan: Room 433 Tu/Th 4:00-5:00PM, and Room 424 Fr 12:00-3:00PM
   Julian: Room 433 Mo/We 12:30-3:00PM
   Please note that the office hours for MIS510 are only available during the following days:
   Feb. 1 to Feb. 15 (Mainly for programming assignment questions)
   Mar. 26 to Apr. 2 (Mainly for project questions)
   Apr. 16 to May. 2 (Mainly for project questions)



3. Class Photos
   Section 1          Section 2



4. Project Presentation/Demo 1.0 (Session1, Session 2)



5. Hsinchun Chen, (2001), Knowledge Management Systems: A Text Mining Perspective


6. Hsinchun Chen, (2002), Trailblazing a Path Towards Knowledge and Transformation


7. IEEE Intelligent Systems, Trends & Controversies; with introductions by Dr. Hsinchun Chen (2009, 2010, 2011):
   - AI and Global Science and Technology Assessment, by Hsinchun Chen (July/August 2009)
   - AI, E-Government, and Politics 2.0, by Hsinchun Chen (September/October 2009)
   - AI for Global Disease Surveillance, by Hsinchun Chen and Daniel Zeng (November/December 2009)
   - Business and Market Intelligence 2.0, by Hsinchun Chen (January/February 2010)
   - AI and Opinion Mining, by Hsinchun Chen and David Zimbra (May/June 2010)
   - A Lexicon Enhanced Method for Sentiment Classification, by Yan Dang, Yulei Zhang, and Hsinchun Chen (July/August 2010)
   - AI and Security Informatics, by Hsinchun Chen, (September/October 2010)
   - AI, Virtual Worlds, and Massively Multiplayer Online Games, by Hsinchun Chen and Yulei Zhang (January/February 2011)
   - Smart Health and Wellbeing, by Hsinchun Chen (September/October 2011)
   - Smart Market and Money, by Hsinchun Chen (November/December 2011)

Other Course-Related Materials (Papers)

1. MISQ BI Special Issue: Business intelligence and analytics: From big data to big impact, By Hsinchun Chen et al. (2012)
2. Harvard Business Review (October 2012)
   - Big Data: The Management Revolution
   - Data Scientist: The Sexiest Job Of the 21st Century
   - Making Advanced Analytics Work For You
   
3. The Anatomy of a Large-Scale Hypertextual Web Search Engine, S. Brin and L. Page (1998)
4. AI, Chapter 4, Winston (1984)
5. GA Handout (27M)
6. Assignment 1: GA (Spring 2012)
7. A Smart Itsy Bitsy Spider for the Web
8. Web 2.0 ... The Machine is Us/ing Us (YouTube)
9. Tim O'Reilly,(2005), What Is Web 2.0? Design Patterns and Business Models for the Next Generation of Software
10. Web 2.0 (Wikipedia)
11. The Long Tail, by Chris Anderson, WIRED Magazine (December 2004)
12. The Great Giveaway (25M), by Erick Schonfeld, Business 2.0 (April 2005)
13. Using Open Web APIs in Teaching Web Mining, by Hsinchun Chen et al. (2001)
14. The Economist A Special Report on Social Networking---A World of Connections (January 30th 2010):
    - A world of connections
    - Global swap shops
    - Twitter's transmitters
    - Profiting from friendship
    
15. The Economist, A Special Report on Managing Information---Data, Data, Everywhere (February 25th 2010):
    - A different game
    - All too much
    - Clicking for gold
    - Data, data everywhere
    - Handling the cornucopia
    - Needle in a haystack
    - New rules for big data
    - Show me
    - Sources and acknowledgments
    - The open society
    
16. The Economist, A Special Report on Personal Technology---Beyond the PC (October 8th 2011):
    - The Power of Many
    - The Beauty of Bite-sized Software
    - It's Arab Spring
    - Up Close
    - It's Arab Spring
    
17. Communications of the ACM (2011):
    -Reflecting on the DARPA Red Balloon Challenge, by John C. Tang et al. (April 2011)
    -Crowdsourcing Systems on the World-Wide Web, by Anhai Doan et al. (April 2011)
    -An Overview of Business Intelligence Technology, by Surajit Chaudhuri et al. (August 2011)
    
18. IEEE Spectrum (June 2011):
    -5 Technologies that will Shape the Web, by Elise Ackerman and Erico Guizzo
    -China's Social Networking Problem, by Sky Canaves
    -Welcome to the Surveillance Society, by Siva Vaidhyanathan
    -The Revolution will not be Monetized, by Bob Garfield
    
19. Big Data, by Doug Henschen, InformationWeek (Oct. 2011)
20. Magic Quadrant for Business Intelligence Platforms, by Rita L. Sallam et al., Gartner Report (Jan. 27 2011)
21. Hype Cycle for Business Intelligence, 2011, by Andreas Bitterer, Gartner Report (Aug. 12 2011)
22. The 2011 IBM Tech Trends Report, by IBM (Nov. 15th, 2011)
23. The Scientific Research Potential of Virtual Worlds, by William Sims Bainbridge, Science (July 27th 2007)
24. Web Mining: Machine Learning for Web Applications, by Hsinchun Chen and Michael Chau (2004)
25. Top 10 Algorithms in Data Mining (PDF)
26. ID3 Handout
27. Backpropagation Neural Network Handout
28. Expert Prediction, Symbolic Learning, and Neural Networks-An Experiment on Greyhound Racing, by Hsinchun Chen et al., IEEE Expert (December 1994)
29. Sports Data Mining Book (Dr. Hsinchun Chen)
30. Self-organizing Maps Handout
31. SIGKDD explorations 2009:
    -What is Analytic Infrastructure and Why Should You Care?, by Robert L. Grossman
    -What's PMML and What's New in PMML 4.0?, by Rick Pechter
    -The WEKA Data Mining Software: An Update, by Mark Hall et al.
    
32. Reynard: Broad Agency Announcement IARPA-BAA-09-05, issued by the Intelligence Advanced Research Projects Activity (IARPA), Incisive Analysis Office. This funding opportunity description "sets forth research areas of interest in the area of identifying behavioral indicators in Virtual Worlds (VWs) and Massive Multiplayer Online Games (MMOGs) that are predictive of real world characteristics of the users." (April 2009)
33. Assignment 2: Neural Network (Spring 2009)
34. Assignment 2: Iris dataset (Spring 2009)
35. Prim's and Kruskal's Minium Spanning Tree Algorithms
36. Credit Rating Analysis with Support Vector Machines and Neural Network: A Market Comparative Study,by Zan Huang et al. (PPT)
37. An Automatic Classification Approach to Business Stakeholder Analysis on the Web, by Wingyan Chung et al. (PPT)
38. Major Web Intelligence Tools , by AI Lab
39. Web Marketing Research (Dr. Hsinchun Chen)

Guest Lectures (Slides)

1. Programming with Amazon, Google, and eBay (Chun-Ju Tseng)
2. Web Programming and Web Services (Chun-Ju Tseng)
3. Software Agents, Multi-Agent Systems, and Data Mining (Dr. Daniel Zeng)
4. Pattern Recognition using Support Vector Machine and Principal Component Analysis (Ahmed Abbasi)
5. TimelyBid (Sean Humphreys)
6. iDog (Chris Chang)
7. Smart Gift Card (Gavin Zhang)
8. Introduction to Web APIs (T.J. Fu)
9. Introduction to Web Application and APIs (Revised by Jonathan Jiang and Julian Guo)
10. Sample Codes for Web Application and APIs (Jonathan Jiang and Julian Guo)
11. Cloud Computing Platforms (Jonathan Jiang and Julian Guo)

Class Lectures (Slides)

1. UA MIS Program Overview (846K)
2. Journals, Conferences, and Funding Sources for MIS Researchers and Educators: A Resource Guide (846K)
3. Cloud Computing and Web Mining Projects, January 2012
4. Page Rank and Google Story
5. Facebook Story
6. Inside Internet Search Engines: Fundamentals (398K)
7. Inside Internet Search Engines:  Spidering and Indexing (41K)
8. Inside Internet Search Engines: Search (553K)
9. Inside Internet Search Engines: Products (75K)
10. Inside Internet Search Engines: Business (37K)
11. Introduction to Web Applications & APIs
12. Web 2.0: Introduction (Dr. Hsinchun Chen)
13. From Search Engines to Web Mining
14. An Introduction to Virtual World
15. Android Overview, by Josh Dehlinger and Siddharth Kaza
16. World (Patent) War, from the BloombergBusinessweek Technology section, March 12, 2012.
17. Taiwan Semiconductor Manufacturing Company: Competitor Analysis, by Dr. Hsinchun Chen
18. Dark Web-Collection, Search, and Analysis, by Dr. Hsinchun Chen
19. CyberGate: A Design Framework and System for Text Analysis of CMC, by Ahmed Abbasi and Hsinchun Chen
20. Detecting Fake Websites: The Contribution of Statistical Learning Theory, by Abbasi, Zhang, Zimbra, Chen, and Nunamaker
21. Web Mining: Machine Learning for Web Applications
22. A Graph-based Recommender System
23. A Lexicon Enhanced Method for Sentiment Classification
24. Business Intelligence and Analytics: Overview and Examples
25. Analytical and Visual Data Mining (5.29M)
26. Introduction to Weka and NetDraw
27. Introduction to Support Vector Machine (SVM) and Conditional Random Field (CRF) (long version, short version)
28. Homeland Security Data Mining using Social (Dark) Network Analysis, ISI 2008, Keynote Address, by Dr. Chen (18.4M)
29. Healthcare Informatics, by Dr. Chen (2012)
30. Infectious Disease Informatics: Overview and The BioPortal Experience, by Dr. Chen (2012)
31. Predicting Market, by Dr. Chen (2012)
32. Information Visualization for Digital Library (2.26M)
33. Information Visualization
34. Data Mining: Part I (1.96M)
35. Data Mining: Part II (3.83M)
36. Data Mining: Part III (3.35M)
37. Knowledge Management Systems: Development and Applications Part I: Overview and Related Fields (1.91M)
38. Knowledge Management Systems: Development and Applications Part II: Techniques and Examples (2.46M)
39. Knowledge Management Systems: Development and Applications Part III: Case Studies and Future (13.91M)
40. Internet Searching and Browsing in a Multilingual World (2.23M)
41. An Automatic Text Mining Framework for Knowledge Discovery on the Web (3.43M)
42. Achieving Information Resources Empowerment: A Digital Library and Knowledge Management Perspective (10.9M)
43. Digital Library Development in the Asia Pacific (16.9M)
44. What is Visual Analytics? Part I, by Jim Thomas (7 MB)
45. What is Visual Analytics? Part II, by Jim Thomas (3 MB)
46. From Search Engines to Web Mining.

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