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CSA3080Adaptive Hypertext Systems I
Lecture 9Representing Data, Information, and
Knowledge I

• Dr. Christopher Staff
• Department of Computer Science AI
• University of Malta

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Aims and Objectives

• Weve discussed the aims and objectives of IR and
  hypertext
• Both enable the user to find information
• If the user knows how to describe it, or
• If the user knows where to find it
• Adaptive systems actively assist the user to
  locate information
• Later, well see how are users interests may be
  represented

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Aims and Objectives

• If we assume that a users interests are known to
  an adaptive system
• the adaptive system needs to know something
  about the domain to know how to adapt it sensibly
• We will return to this in CSA4080 when we discuss
  Intelligent Tutoring Systems, but here we give an
  informal introduction

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Data, Information, and Knowledge

• Data
• simple/complex structures
• Arbitrary sequences
• Chris, 280963, b47y3
• Information
• Data in Context
• Authors name Chris
• Boeing left wing Part no b47y3

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Data, Information, and Knowledge

• Knowledge
• Knowing when to use information
• When ordering a replacement part, specify the
  part number and quantity required

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Surface-based to Deep SemanticRepresentations

• Surface-based models tend to use data/information
• Deep semantic models tend to use knowledge
• Information retrieval systems (Extended/Boolean,
  Statistical) know about term features within
  documents
• Additionally, statistical models know the
  distribution of terms throughout the collection
• Using NL statistics about the distribution of
  terms in language may give further information
  (not about terminology, though)

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Surface-based to Deep Semantic

• Dumb IR systems can find documents containing
  John, loves, Mary, but cannot answer the
  question Does John love Mary?
• John loves Mary will miss Mary is loved by
  John, John cares deeply for Mary, etc.
• Sometimes complex reasoning is also needed

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Surface-based to Deep Semantic

• Normal hypertext (e.g., WWW) knows that some
  documents are linked
• Lack of link semantics
• Why/for what reason have these documents been
  linked?
• Can make assumptions
• Can deduce link types (e.g., navigational,
  contextual, etc), but better if type was explicit

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Surface-based to Deep Semantic

• Semantic networks connect data nodes using typed
  links (e.g., isa, part_of, )
• Can do complex reasoning by examining
  relationships between nodes
• If a hypertext had typed links, would it be a
  semantic network?
• Knowledge and information are largely
  embedded within unstructured text
• If exposed, then, potentially, a hypertext can be
  used to represent and reason with information and
  knowledge

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Semantic Web

• The Semantic Web is an extension of the
  current web in which information is given
  well-defined meaning, better enabling computers
  and people to work in cooperation.
• Berners-Lee2001
• References
• Tim Berners-Lee, James Hendler, Ora Lassila, The
  Semantic Web, in Scientific American, May 2001
• http//www.w3.org/2001/sw/

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Semantic Web

• Semantic Web,and Web technologies are covered in
  more detail by Matthew
• Well later return to solutions to AHS which are
  closer to surface-based, but well spend some
  time considering the Semantic Web

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Semantic Web Architecture
From http//mail.ilrt.bris.ac.uk/cmdjb/talks/sw-v
ienna/slide10.html
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Back to surface-based approaches

• One of the challenges facing the Semantic Web is
  making the knowledge and information contained in
  existing Web pages explicit
• Partly concerned with exposing relational data in
  textual documents
• But also, opinions, beliefs, facts,