Inforadar @ UPRM

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Inforadar _at_ UPRM

• Computing Systems Research Group
• Prof. Bienvenido Vélez-Rivera Leader
• José Enseñat Graduate student
• Juan Torres Undergraduate student
• University of Puerto Rico
• Mayagüez Campus
• PRECISE Project
• Mayagüez, October 07, 2000

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Problem Statement
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Query-based Web Search
short query
large result-set

• BUT
• - queries hard to write
• sequential access to result set inadequate

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Proposed Solution
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Proposed Solution
Inforadars Interactive query hierarchies
seed query
selected query
result set for selected query
dynamic categories are queries
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Inforadars Interactive query hierarchies
colors indicate node status
level 2 categories
icons mark documents read or in-basket
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Theoretical Formulation
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Coverage-based Category Evaluation MetricGoal
Avoid Redundancy and Information Loss
q
seed
q1
q2
(a) low information loss high redundancy
(b) high information loss low redundancy
(c) better
Ideal Select categories that best approximate a
partition But This is an NP-complete problem
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CTS A greedy approximation algorithm for
category selection
Goal Pick best term among t1, t2, t3
C set of documents covered by previously
selected terms
low coverage
D(q t3)
winning category!
D(q)
D(q t2)
D(q t1)
high redundancy
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Experimental Plan

• Implement Inforadar site indexing ALL website
  data at UPRM
• Make Inforadar the official search engine for the
  UPRM web site
• Conduct usability study
• Analyze real user feedback
• Incorporate feedback into an improved design

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References

• Query Lookahead for Query-Based Document
  Categorization.
• Ph.D. Thesis
• Massachusetts Institute of Technology
• September 1999 
• Fast and Effective Query Refinement
• Bienvenido Vélez, Ron Weiss, Mark Sheldon and
  David K. Gifford
• ACM Conference in Research and Development in
  Information Retrieval (SIGIR 97) 
• HyPursuit A network search engine exploiting
  concent-link similarity
• R. Weiss, B. Vélez, M. Sheldon, C. Namprempre, P.
  Szilagy and D. K. Gifford..
• ACM Conference on Hypertext (HyperText 96)