CONCEPT MODELING:

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CONCEPT MODELING
A Proposed Hybrid Approach to Patent Modeling
Ðorde Popovic, Ognjen Šcekic, Veljko Milutinovic
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What is concept modeling?

• A way of modeling reality
• Identifying concepts
• Identifying relations among concepts
• Organizing the concepts in a knowledge-base,
  allowing an "intelligent" way to search and
  process this data.
• Why do we need concept modeling?To make
  electronic resources not only machine-processable,
  but also machine-understandable!

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Challenges

• How to create a model that has a uniform
  structure, and is powerful enough to capture the
  essence of any concept?
• How should these models be linked into an
  efficient structure?
• How can we bridge the gap between natural
  languageand a machine-processable model?

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7 Ws PROs and CONs
Which
When
What
Ultimate Goal From a specific to a general model!
concept
Why
WHAT associations provide general facts about any
concept.
Where
Who
(W)How
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Why start with patents?

• Described by a very formal, structured language
  claims.
• Each patent is a novel concept.
• Definition of one patent is usually based on
  another one.

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Structure of a Patent Document
General info about the patent (can be used for
Which, When, Why, Where, Who and How)
Description not well structured
References to related patents
Claims primary target for What
Abstract of the patent

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Conceptual Indexing (1)

• What is conceptual indexing?
• New technique for organizing information to
  support subsequent access that can dramatically
  improve your ability to find the information you
  need,with less hassle and with better results.
• William A.
  Woods
• Conceptual indexing combines techniques of
• Knowledge representation
• Natural language processing
• Classical techniques for indexing words and
  phrases
• Bridges the gap between natural languageand a
  machine processable model.

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Conceptual Indexing (2)

• Conceptual indexing technology is a combination
  of
• Concept extractor
• Identifies phrases to be indexed.
• Concept assimilator
• Analyzes a concept phrase to determine
• its place in the conceptual taxonomy.
• Conceptual retrieval system
• Uses conceptual taxonomy to make connections
• between requested and indexed items.

Figure 1 Main components of a conceptual indexer
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Hybrid Approach Indices RDF/OWL

• Conceptual indices
• RDF/OWL
• Motivation Use the advantages of one approach
  to eliminate the drawbacks of the other.

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Conceptual Indices vs. RDF/OWL
Conceptual indices RDF/OWL ontologies
Major advantages Linear-complexity structures Very expressive and precise
Major advantages Provide basic subsumption relations Based on First-Order Logic
Major advantages Provide built-in knowledgeon low-level concepts Supported by W3C
Major drawbacks Incapability of establishing explicit relations among high-level concepts Great complexity
Major drawbacks Incapability to create precise models Great complexity
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Why not use ontologies alone?

• If we want to use an ontology we have 2 choices
• Use an existing, well-established ontology that
  might not suite our needs.
• Create a new ontology which does suit our needs
• We can create several different
  ontologies,depending on how we want to capture
  the information.
• Problems arise when we want to merge ontologies.
• This approach works fine within a closed
  communitywith specific needs
• There already exists a well-defined basic
  ontology structure.
• Community members have a good knowledge of how to
  model new conceptsin terms of the existing ones.

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Why not use indices alone?

• For example, let us take the simplest possible
  definition, for a bird
• bird 1 a creature with wings and feathers
  that lays eggs and can usually fly.
• Our index might then contain the following
  associationscreature, wings, feathers, eggs,
  fly.
• A conceptual index does not offer the possibility
  to state the fact that some birds do not fly!

1 - Word definition taken from Longman Dictionary
of Contemporary English, 3rd edition, 1995.
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Hybrid Approach (1)

• An index of associations represents a simple
  model,similar to what humans have on their
  mindwhen they first think of a bird.
• Having enough associations, one can create a
  model with a considerable degree of accuracy.
• RDF/OWL statements provide a means for
  expressing additional (but very important)
  information(e.g. there are birds that cannot
  fly!)
• We believe this is good enough for most
  applications.

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Hybrid Approach (2)

• It is important to keep track of how many times a
  term is mentioned,because it affects its
  descriptive power.
• Example
• U.S. Patent 6,989,179 Synthetic grass
  sport surfaces, claims section
• 1. synthetic grass 10
• 2. playing surface 9
• These terms represent the essence of what is
  being described!

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Hybrid Approach (3)

• However, this is only because we know what
  synthetic grass and playing surface are!
• ? At some level, we need to have some
  intrinsic, built-in knowledge-base of basic
  concepts!
• All the other concepts can then be described in
  terms of these basic concepts.
• Solution Conceptual indexers are equipped with
  a knowledge base of basic terms.

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Patent Model Conceptual Index

• A patents Claims section is scanned and
  processedby a conceptual indexer.
• The result is a descriptive index, associated
  with the patent (it size is approx. 1-5 of the
  full text).
• This index can be seen as an ordered list of the
  patents WHAT associations (terms, phrases,
  sentence fragments).
• An entry in the descriptive index contains a
  low-level concept,and the number of its
  occurrences.

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Patent Model RDF/OWL

• For a different application, a different RDF/OWL
  model needs to be devised.
• For describing patents this model could be used
  to capture explicitly stated information
• Patent number and other numbers (? WHICH)
• Inventor, examiner, attorney, (? WHO)
• Date when the patent was filed (? WHEN)
• Explicit references to similar patents (? WHICH)
• etc
• Each W can have multiple sub-categories that are
  application-specific!

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Patent Model Creation
Figure 2 Creation of a patent model Claims
section is processed by the conceptual indexer to
produce an index associated with the
patent. Additional information about the concept
is captured by RDF/OWL statements,into a
predefined, application-specific structure.
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Patent Model Result
Figure 3 Patent model WHAT associations are
contained in a descriptive index. Other Ws are
expressed through RDF/OWL statements.
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Patent model Big Picture

• Descriptive indices are re-processed by the
  Conceptual indexer,to form the system index.
• Each entry in the system index retains links to
  the descriptive indices it originates from,and
  vice-versa.
• This structure allows us to
• Perform quick searches of the existing patents
• Add/remove patents easily

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Figure 4 Top-level scheme
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Patent Model Patent Relations

• Two ways of establishing relations among patents
• Via RDF/OWL statements, using automated reasoners
• ? Problem Referential integrity Consistency
• Via System index (implicit links)
• ? Problem Inexact, based on probability

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Patent Model Implicit Links (1)

• Descriptions of similar concepts (patents)
  usually make a frequent use of similar or even
  same terms.
• By determining overlapping terms we
  createdynamic, implicit links among similar
  concepts.
• The number of such implicit links can be used to
  express similarity among concepts.
• The algorithm for determining the similarity
  needs to be tweaked empirically.

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Patent Model Implicit Links (2)

• For exampleWhen describing two different
  vaccines we would probably make a frequent use
  of terms like vaccine, inactivated antigens,
  immune response, etc.

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Advantages Drawbacks

• Advantages
• Reduced complexity (a great reduction of direct
  links between concepts)
• Fast search and retrieval (as the result of
  using indices)
• Scalability
• Drawbacks
• Use of indices implies loss of precision

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Conclusion

• Our idea is still in the first stage of
  development.
• Its key advantages areits general applicability
  and reduced complexity.
• Further research is needed to explore the
  quality and feasibility of the proposed solution.
• However, we expect that the combination of
  OWL/RDF structures and indices might produce a
  satisfactory performance/exactness ratio.

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References

• W. A. Woods, L. A. Bookman, A. Houston, R. J.
  Kuhns, P. Martin, S. Green, "Linguistic
  Knowledge Can Improve Information
  Retrieval",Proc. of the Applied Natural Language
  Processing Conference (ANLP-2000),Seattle, 2000.
• O. Scekic, P. Bojic, "An Overview of OWL and its
  Role in Semantic Web Architecture",YU-INFO 06,
  Kopaonik, SerbiaMontenegro, 2006.
• Boris V. Dobrov, Natalia V. Loukachevitch,
  Tatyana N. Yudina, "Conceptual Indexing Using
  Thematic Representation of Texts,Scientific
  Research Computer Center of Moscow State
  University, Moscow, 1998.
• S. Omerovic, D. Savic, S. Tomazic,"A Survey of
  Concept Modeling",Faculty of Electrical
  Engineering, University of Ljubljana, Slovenia
  (to appear).
• William A. Woods, Conceptual Indexing A Better
  Way to Organize Knowledge, Technical report,
  Sun Microsystems Laboratories, 1998.
• http//www.uspto.gov U.S. Patent office

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CONCEPT MODELING
A Proposed Hybrid Approach to Patent Modeling
Ðorde Popovic Ognjen
Šcekic Veljko
Milutinovic popajce_at_ptt.yu
ogi_at_cg.yu
vm_at_etf.bg.ac.yu
Thank you !