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Lecture Notes
                                                   University of Birzeit
                                                   2nd Semester, 2010



 Advanced Artificial Intelligence     (SCOM7341)




          Ontology
                    Part 3
Knowledge Double-Articulation


        Dr. Mustafa Jarrar
  mjarrar@birzeit.edu           www.jarrar.info
             University of Birzeit

                    Jarrar © 2011                                          1
Reading Material



0) Everything in these slides


1) Jarrar, M.: Towards Methodological Principles for Ontology
    Engineering. PhD thesis, Vrije Universiteit Brussel (2005). See
    http://www.jarrar.info
                           Only chapter 2 & 3



2) Mustafa Jarrar: Towards Effectiveness and Transparency in e-Business
   Transactions, An Ontology for Customer Complaint Management .
  http://www.jarrar.info/publications/mjarrar-CCFORM-chapter.v08.pdf

    This is a case study




                                                  Jarrar © 2011           2
Knowledge Double-Articulation
                      A Methodology to engineer ontologies
                    Ontology
                     Base                               Domain
                                                     Axiomatization

                Ontolog




                                                                     Articulation
                                                                       Double
                y


                                                     Application-kind
                   Commitment
                                                     Axiomatizations
                     Layer




                                                Particular
                                                       Application



The meaning of a vocabulary should be doubly-articulated into domain
  axiomatization and application axiomatization(s).
• Domain axiomatization (or a linguistic resource) is mainly concerned with
  characterizing the “intended meaning/models” of a vocabulary at the
  community/domain level.
• Application axiomatization is more concerned with the utility of these
  vocabularies according to certain application/usability perspectives.
• Ontologies built in this way are easier to build, highly reusable and usable,
  easier to integrate with other ontologies, and smoother to maintain.
                                    Jarrar © 2011                                   3
Knowledge Double-Articulation


Highly reusable (domain/community level)         Highly usable (application level)
 Domain axiomatization                         Application-kind axiomatizations      Particular Applications




                                                                                                Bibliotheek




                                           Jarrar © 2011                                                      4
Knowledge Double-Articulation


    Highly reusable (domain/community level)         Highly usable (application level)
     Domain axiomatization                         Application-kind axiomatizations      Particular Applications




    OntologyBase, holding
linguistic knowledge, such as


    WordNet
                                                                                                    Bibliotheek




                                               Jarrar © 2011                                                      5
Knowledge Double-Articulation


    Highly reusable (domain/community level)         Highly usable (application level)
     Domain axiomatization                         Application-kind axiomatizations      Particular Applications

 accounts for the
  intended meaning of
  domain vocabularies;
    OntologyBase, holding
 rooted at a human as
linguistic knowledge, such
   language/community
    WordNet
   conceptualization.

 interpreted                                                                                       Bibliotheek

  intensionally;

 a shared vocabulary
  space for application
  axiomatizations;
                                               Jarrar © 2011                                                      6
Knowledge Double-Articulation Theory

 A concept is a set of rules in our mind about a certain thing in Back
  reality.
 For concept C, the set I of “all possible” instances that comply with these
 rules are called the intended models of the concept C.
                                                     Domain/Language
                                                                                        Level
            An application A that is interested -according to its usability
      perspectives- in a subset IAi of the set I, is supposed to provide some
                 rules to specialize I, IAi is called legal models.
                                          IAi      I                                Application Level

 I                      I: The set of the intended models for concept C
          IA         e.g. “Book” at the a human language conceptualization level

                   IA1: The set of the legal models (/possible extensions) of application C A
                                       e.g. “Book” for museum applications
     IB
                    IA2: The set of the legal models (/possible extensions) of application C B
                                      e.g. “Book” for public/university libraries
      IC
                   IA3: The set of the legal models(/possible extensions) of application CC
                                                e.g. “Book” for bookstores
                                          Jarrar © 2011                                                 7
Possible way of applying the double-
    articulations theory
Each vocabulary in your ontology should be linked (e.g. though
a namespace) with a concept in a linguistic resource (e.g. a
synset in WordNet).




                         Jarrar © 2011                           8
Example (Customer Complaint Ontology)

              Central complaining portal




    See http://www.jarrar.info/publications/mjarrar-CCFORM-chapter.pdf.htm

                              Jarrar © 2011                                  9
Example (Customer Complaint Ontology)




See http://www.jarrar.info/publications/mjarrar-CCFORM-chapter.pdf.htm



                            Jarrar © 2011                                10
CC Ontology (Example)

                                                        CC Ontology base: 300 lexons
Domain Axiomatization




                          CCcontext




                          CC Glossary: 220 glosses




                                            Recipient       Complaint                  Complianant
                                                                                                     Resolution
                        Contract                                                                                  Address
                        7 axiomatization Modules                            Problem


                            CCApplication1                        CCApplication2                     CCApplicationn
                                                                   Jarrar © 2011                                            11
Gloss

 An auxiliary informal (but controlled) account of the intended meaning
  of a linguistic term, for the commonsense perception of humans.




A gloss is supposed to render factual knowledge that is critical to
understand a concept, but that e.g. is implausible, unreasonable, or very
difficult to formalize and/or articulate explicitly

(NOT) to catalogue general information and comments, as e.g.
  conventional dictionaries and encyclopedias usually do, or as
  <rdfs:comment>.                                                           12
                                Jarrar © 2011
The ontological notion of Gloss

What should and what should not be provided in a
gloss:
 1. Start with the principal/super type of the concept being defined.
    E.g. „Search engine‟: “A computer program that …”, „Invoice‟: “A business document
         that…”, „University‟: “An institution of …”.

 2. Written in a form of propositions, offering the reader inferential
   knowledge that help him to construct the image of the concept.
    E.g. Compare „Search engine‟:
    “A computer program for searching the internet, it can be defined as one of the most
         useful aspects of the World Wide Web. Some of the major ones are Google, ….”;
    A computer program that enables users to search and retrieves documents or data from a
         database or from a computer network…”.


 3. Focus on distinguishing characteristics and intrinsic prosperities that
    differentiate the concept out of other concepts.
    E.g. Compare, „Laptop computer‟:
    “A computer that is designed to do pretty much anything a desktop computer can do, it
         runs for a short time (usually two to five hours) on batteries”.
    “A portable computer small enough to use in your lap…”.
                                      Jarrar © 2011                                         13
The ontological notion of Gloss


4. Use supportive examples :

  -    To clarify cases that are commonly known to be false but they are true, or that are
       known to be true but they are false;

  -    To strengthen and illustrate distinguishing characteristics (e.g. define by examples,
       counter-examples).

  Examples can be types and/or instances of the concept being defined.




5. Be consistent with formal definitions/axioms.



6. Be sufficient, clear, and easy to understand.


                                     Jarrar © 2011                                             14
Context
     • A scope of Interpretation
     • An abstract identifier that refers to implicit (or maybe tacit)
        assumptions, in which the interpretation of a term is bounded to
        a concept




In In practice, we define context by referring to a source (e.g. a set of
documents, laws and regulations, informal description of “best
practice”, etc.), which, by human understanding, is assumed to
“contain” those assumptions. Concepts, relations and rules are
assumed (by human understanding) to be “true within their context‟s
                                 Jarrar © 2011                           15
Context (Example)

        Customer complaining Cotext




                 Jarrar © 2011        16

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Jarrar.lecture notes.aai.2011s.ontology part3_double-articulation

  • 1. Lecture Notes University of Birzeit 2nd Semester, 2010 Advanced Artificial Intelligence (SCOM7341) Ontology Part 3 Knowledge Double-Articulation Dr. Mustafa Jarrar mjarrar@birzeit.edu www.jarrar.info University of Birzeit Jarrar © 2011 1
  • 2. Reading Material 0) Everything in these slides 1) Jarrar, M.: Towards Methodological Principles for Ontology Engineering. PhD thesis, Vrije Universiteit Brussel (2005). See http://www.jarrar.info Only chapter 2 & 3 2) Mustafa Jarrar: Towards Effectiveness and Transparency in e-Business Transactions, An Ontology for Customer Complaint Management . http://www.jarrar.info/publications/mjarrar-CCFORM-chapter.v08.pdf This is a case study Jarrar © 2011 2
  • 3. Knowledge Double-Articulation A Methodology to engineer ontologies Ontology Base Domain Axiomatization Ontolog Articulation Double y Application-kind Commitment Axiomatizations Layer     Particular Application The meaning of a vocabulary should be doubly-articulated into domain axiomatization and application axiomatization(s). • Domain axiomatization (or a linguistic resource) is mainly concerned with characterizing the “intended meaning/models” of a vocabulary at the community/domain level. • Application axiomatization is more concerned with the utility of these vocabularies according to certain application/usability perspectives. • Ontologies built in this way are easier to build, highly reusable and usable, easier to integrate with other ontologies, and smoother to maintain. Jarrar © 2011 3
  • 4. Knowledge Double-Articulation Highly reusable (domain/community level) Highly usable (application level) Domain axiomatization Application-kind axiomatizations Particular Applications Bibliotheek Jarrar © 2011 4
  • 5. Knowledge Double-Articulation Highly reusable (domain/community level) Highly usable (application level) Domain axiomatization Application-kind axiomatizations Particular Applications OntologyBase, holding linguistic knowledge, such as WordNet Bibliotheek Jarrar © 2011 5
  • 6. Knowledge Double-Articulation Highly reusable (domain/community level) Highly usable (application level) Domain axiomatization Application-kind axiomatizations Particular Applications  accounts for the intended meaning of domain vocabularies; OntologyBase, holding  rooted at a human as linguistic knowledge, such language/community WordNet conceptualization.  interpreted Bibliotheek intensionally;  a shared vocabulary space for application axiomatizations; Jarrar © 2011 6
  • 7. Knowledge Double-Articulation Theory  A concept is a set of rules in our mind about a certain thing in Back reality.  For concept C, the set I of “all possible” instances that comply with these rules are called the intended models of the concept C. Domain/Language Level  An application A that is interested -according to its usability perspectives- in a subset IAi of the set I, is supposed to provide some rules to specialize I, IAi is called legal models. IAi I Application Level I I: The set of the intended models for concept C IA e.g. “Book” at the a human language conceptualization level IA1: The set of the legal models (/possible extensions) of application C A e.g. “Book” for museum applications IB IA2: The set of the legal models (/possible extensions) of application C B e.g. “Book” for public/university libraries IC IA3: The set of the legal models(/possible extensions) of application CC e.g. “Book” for bookstores Jarrar © 2011 7
  • 8. Possible way of applying the double- articulations theory Each vocabulary in your ontology should be linked (e.g. though a namespace) with a concept in a linguistic resource (e.g. a synset in WordNet). Jarrar © 2011 8
  • 9. Example (Customer Complaint Ontology) Central complaining portal See http://www.jarrar.info/publications/mjarrar-CCFORM-chapter.pdf.htm Jarrar © 2011 9
  • 10. Example (Customer Complaint Ontology) See http://www.jarrar.info/publications/mjarrar-CCFORM-chapter.pdf.htm Jarrar © 2011 10
  • 11. CC Ontology (Example) CC Ontology base: 300 lexons Domain Axiomatization CCcontext CC Glossary: 220 glosses Recipient Complaint Complianant Resolution Contract Address 7 axiomatization Modules Problem CCApplication1 CCApplication2 CCApplicationn Jarrar © 2011 11
  • 12. Gloss An auxiliary informal (but controlled) account of the intended meaning of a linguistic term, for the commonsense perception of humans. A gloss is supposed to render factual knowledge that is critical to understand a concept, but that e.g. is implausible, unreasonable, or very difficult to formalize and/or articulate explicitly (NOT) to catalogue general information and comments, as e.g. conventional dictionaries and encyclopedias usually do, or as <rdfs:comment>. 12 Jarrar © 2011
  • 13. The ontological notion of Gloss What should and what should not be provided in a gloss: 1. Start with the principal/super type of the concept being defined. E.g. „Search engine‟: “A computer program that …”, „Invoice‟: “A business document that…”, „University‟: “An institution of …”. 2. Written in a form of propositions, offering the reader inferential knowledge that help him to construct the image of the concept. E.g. Compare „Search engine‟: “A computer program for searching the internet, it can be defined as one of the most useful aspects of the World Wide Web. Some of the major ones are Google, ….”; A computer program that enables users to search and retrieves documents or data from a database or from a computer network…”. 3. Focus on distinguishing characteristics and intrinsic prosperities that differentiate the concept out of other concepts. E.g. Compare, „Laptop computer‟: “A computer that is designed to do pretty much anything a desktop computer can do, it runs for a short time (usually two to five hours) on batteries”. “A portable computer small enough to use in your lap…”. Jarrar © 2011 13
  • 14. The ontological notion of Gloss 4. Use supportive examples : - To clarify cases that are commonly known to be false but they are true, or that are known to be true but they are false; - To strengthen and illustrate distinguishing characteristics (e.g. define by examples, counter-examples). Examples can be types and/or instances of the concept being defined. 5. Be consistent with formal definitions/axioms. 6. Be sufficient, clear, and easy to understand. Jarrar © 2011 14
  • 15. Context • A scope of Interpretation • An abstract identifier that refers to implicit (or maybe tacit) assumptions, in which the interpretation of a term is bounded to a concept In In practice, we define context by referring to a source (e.g. a set of documents, laws and regulations, informal description of “best practice”, etc.), which, by human understanding, is assumed to “contain” those assumptions. Concepts, relations and rules are assumed (by human understanding) to be “true within their context‟s Jarrar © 2011 15
  • 16. Context (Example) Customer complaining Cotext Jarrar © 2011 16