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Hinting Improbable WordLinkClouds for Cluster Summary and Discovery

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hypernyms: Y is a hypernym of X if every X is a (kind of) Y ... coordinate terms: Y is a coordinate term of X if X and Y share a hypernym ... – PowerPoint PPT presentation

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Title: Hinting Improbable WordLinkClouds for Cluster Summary and Discovery


1
Hinting Improbable Word-Link-Clouds for Cluster
Summary and Discovery
  • Loui CS513 Proposal Fall 06

2
Problem
  • There is too much to read
  • We need skimming tools
  • Text summarization is one way
  • Improbable word and phrase extraction is another
  • Word-Link-Clouds are also neat, e.g. Icosystems
    text visualization

3
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4
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5
Building These Things
  • Which words to extract?
  • Which words get links?
  • How big each word?
  • How thick each link?
  • How can you HINT words?
  • How can you VARY views?

6
Hinting
  • Keywords are a great hint
  • Ontologies such as wordnet are helpful
  • Synonyms, meronyms, hypernyms
  • Domain-specific dictionaries are helpful
  • IBK the interest-background corpus

7
  • Nouns
  • hypernyms Y is a hypernym of X if every X is a
    (kind of) Y
  • hyponyms Y is a hyponym of X if every Y is a
    (kind of) X
  • coordinate terms Y is a coordinate term of X if
    X and Y share a hypernym
  • holonym Y is a holonym of X if X is a part of Y
  • meronym Y is a meronym of X if Y is a part of X
  • Verbs
  • hypernym the verb Y is a hypernym of the verb X
    if the activity X is a (kind of) Y (travel to
    movement)
  • troponym the verb Y is a troponym of the verb X
    if the activity Y is doing X in some manner (lisp
    to talk)
  • entailment the verb Y is entailed by X if by
    doing X you must be doing Y (snoring by sleeping)
  • coordinate terms those verbs sharing a common
    hypernym
  • Adjectives
  • related nouns
  • participle of verb
  • Adverbs
  • root adjectives

8
IBK
  • IBK is a set of documents
  • That are interesting
  • Presumably contain keywords or their relatives
  • Lack of representation Lack of interest
  • Contains implicit information about granularity
  • Lots of fine sports keywords IMPLIES detailed
    interest
  • Variation/Repetition in IBK is as important as
    inclusion

9
Varying
  • Icosystems/MIT/Bonabeau GA/GP feedback
  • Levine/WUSTL my view, your view
  • Loui/WUSTL Reordering a cluster creates a new
    view
  • 513/WUSTL any new ideas?

10
Proposal
  • Working just with BBC news data
  • Write
  • Visualization software (fairly trivial)
  • Ordered clustering engine (many directions
    possible)
  • IBK extraction/matching engine
  • Multiple views

11
Needed
  • People I can supervise who will do my bidding
  • Scripting programmers OR very good UNIX people
  • People who I can communicate with who can get
    things done quickly (not necessarily thoroughly)
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