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NJIT CIS 392 Text Processing, Retrieval, and Mining

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Spring 03. CIS392 Lecture 1. 1. NJIT CIS 392. Text Processing, Retrieval, and Mining ... 6. Routing and Filtering (try msnbc.com, or ACM digital library bookshelf. ... – PowerPoint PPT presentation

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Title: NJIT CIS 392 Text Processing, Retrieval, and Mining


1
NJIT CIS 392 Text Processing, Retrieval, and
Mining
  • Instructor Y. F. Brook Wu, Ph.D.
  • Material
  • Van Rijsbergen Ch1
  • "What do people want from IR" by Bruce Croft

2
Contact the Instructor
  • In person GITC 5502, 1145-1300, Monday and
    Wednesday.
  • By phone (973) 596 5285
  • By e-mail (fastest way to get my attention)
    wu_at_njit.edu Please include CIS 392 in the
    subject of your e-mail.

3
Web Board for CIS 392
  • Instructions of getting a web board account
    http//webboard.njit.edu/
  • Class web board http//webboard.njit.edu8080/S2
    003CIS392-002/  Please check announcements and
    new messages at least three times a week and
    contribute as much as you can.
  • When posting on web board, respect others and be
    considerate. 

4
Class Web Site
  • CIS 392 web site
  • http//web.njit.edu/wu/teaching/sp03/CIS392/CIS39
    2-Sp03.htm

5
www.turnitin.com
6
www.turnitin.com
7
Resources Journals
  • From Korfhage p. xiii
  • JASIST (formally JASIS)
  • ACM (please visit its digital library)
  • Other suggestions
  • IPM (Information Processing and Management)
  • Journal of Documentations

8
Resources Conferences Proceedings
  • TREC Text REtrieval Conference
  • http//trec.nist.gov/
  • ACM/SIGIR
  • http//www.sigir2001.org/
  • ASIST
  • http//www.asis.org
  • JCDL
  • http//www.acm.org/jcdl/
  • CIKM
  • http//www.cikm.org/

9
Exit Requirements
  • You should be familiar with the followings
  • Search strategies
  • Text analysis
  • Retrieval models
  • Retrieval effectiveness measures
  • Retrieval improvement techniques
  • Document Warehousing Techniques
  • Text Mining Applications

10
Importance of Finding the Right Information
  • Personal weather, traffic, investment, etc.
  • Academic prior studies for literature review.
  • Medical symptoms, treatments, etc.
  • Legal precedents to support arguments, etc.

11
What Makes Text Retrieval Difficult?
  • Ill-understood info needs
  • Ill-formed queries
  • Linguistic and semantic complexities
  • Word-sense ambiguity, semantic, syntactic, etc.
  • and many more reasons!

12
Data Retrieval v.s. Info Retrieval (from
Rijsbergen Ch1)
13
What Do People Want from IRby W. Bruce Croft
  • Source D-Lib Magazine, November 1995, or
    http//sunsite.anu.edu.au/mirrors/dlib/dlib/novemb
    er95/11croft.html
  • 10. Relevance Feedback (try Google)
  • 9. Information Extraction (http//www.clearforest.
    com/ )
  • 8. Multimedia Retrieval (try Google image search)

14
What Do People Want from IRby W. Bruce Croft
  • 7. Effective Retrieval
  • 6. Routing and Filtering (try msnbc.com, or ACM
    digital library bookshelf.)
  • 5. Interfaces and Browsing
  • 4. "Magic" (Automatic Query Expansion)

15
What Do People Want from IRby W. Bruce Croft
  • 3. Efficient, Flexible Indexing and Retrieval
  • 2. Distributed IR
  • 1. Integrated Solutions
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