Aplicatii web semantice

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Aplicatii web semantice

• Modelarea cunostintelor
• Curs 2

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define semantic

• semantics - the meaning of a word, phrase,
  sentence, or text "a petty argument about
  semantics" wordnetweb.princeton.edu/perl/webwn
• Semantics is the study of meaning, usually in
  language. The word "semantics" itself denotes a
  range of ideas, from the popular to the highly
  technical. It is often used in ordinary language
  to denote a problem of understanding that comes
  down to word selection or connotation.
  ...en.wikipedia.org/wiki/Semantic

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• Idea of the semantic web
• Man and machine must interpret data in the same
  way

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• Man and man must interpret data in the same way

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• gt need to have shared understanding inside a
  community

Programmers community
Astronommers community
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• The knowledge model must express relations and
  constraints

Animals with feet
?
Is-a
Is-a
Is-a
Lives in
(part of)
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• Need to be able to represent implicit knowledge

• - Would you find the page that says
• where the mess hall is?
• That's not in the book, sir.
• You mean you've never had a meal?
• Three square meals a day, sir.
• How did you find the mess hall,
• if it's not in this book?
• I guess I just followed the crowd.
• A few good men 1992

Computers do not understand what for us is
implicit knowledge People outside our community
do not understand what for us is implicit
knowledge
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Define ontology

•  ontology ((computer science) a rigorous and
  exhaustive organization of some knowledge domain
  that is usually hierarchical and contains all the
  relevant entities and their relations)
• A formal, explicit specification of a shared
  conceptualisation Gruber 93

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Characteristics of an ontology

• Coverage - extent to which the primitives
  mobilized by the scenarios are covered by the
  ontology
• Specificity - the extend to which ontological
  primitives are precisely identified
• Granularity - the extend to which primitives are
  precisely and formally defined.
• Formality - the extend to which primitives
  aredescribed in a formal language.

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Role of ontologies in the semantic web
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Glossary of terms

• Top level ontology ontology that defines
  general concepts that are the same across all
  domains
• Domain ontology ontology that defines terms
  specific to a domain
• TBOX "terminological component"a vocabulary
  associated with a set of facts ABox classes and
  properties
• ABOX an "assertion component"a fact associated
  with a terminological vocabulary within
  a knowledge base. (usually associated with
  instances)
• Knowledge base TBoxABox

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Glossary of terms

• Closed world assumption every sentence that we
  dont know to be true is false
• Open world assumption if the truth value of a
  sentence is not known we cant assume it to be
  either true or false (used in the semantic web)
• class?concept ?type ?category
• instance ?individual
• property ?slot ?relation ?attribute ?role

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How to build an ontology

• Domain is called ontology engineering
• Multiple methodologies for building ontologies
• Methondology
• TOVE
• Activity First Method
• Agile Methodology - RapidOWL

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Methontology

• Specification purpose of the ontology, level of
  formality (highly informal, semi-formal, formal),
  scope (set of terms to be described)
• Knowledge acquisition discussions with experts,
  text analysis
• Conceptualisation
• Build glossary of terms
• Analyze separately concepts and verbs
• Integration
• Search for similar terms in higher level
  ontologies
• Implementation
• Validation
• Documentation

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Methondology - Conceptualisation

• For concepts specify
• Table of instant attributes which are the
  attributes possible for the instances of the
  concepts
• Table of instances
• Table of constants
• Attribute classification trees which are the
  relations between attributes and constants

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Methontology Conceptualisation (2)

• For verbs specify
• Verbs dictionary meaning of the verbs in a
  declarative way
• Table of conditions need to be satisfied before
  or after action is performed
• Tables of formulas
• Tables of rules

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TOVE methodology

• Define a set of Motivating Scenarios
• Define a set of Informal Competency Questions
  that the ontology must answers in order to
  support the motivating scenarios
• Using First-Order Logic, define the Terminology
  of the ontology
• Formally redefine the Competency Questions using
  the terminology and first-order logic
• Define the semantics and constraints on the
  terminology using first-order logic

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TOVE
Informal competency questions requirements in
form of questions that the ontology must be able
to answer Axioms specify the definitions of
concepts and constraints Completeness theorems
the conditions under which the solutions to the
questions are complete
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AFM Activity First Method

• method of building task and domain ontologies
  from technical documents
• Extraction of task-units
• Divide the text in the technical documents into
  small blocks to extract vocabulary easier.
• Extract task-units which contain only one
  process(action) from these blocks.
• Make a flow chart called a concrete task-flow by
  combining task-units.
• Organization of task-activities
• Conceptualize task-activities from verbs in the
  task-units.
• Organize the task-activities in an is-a
  hierarchy.
• Define role-concepts, called task-activity roles,
  which appear in the input/output of these
  task-activities.

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AFM Activity First Method

• Analysis of task-structure
• Generalize the concrete task-flows to obtain
  general task-flows.
• Describe the object-flows, which clearly express
  relations between inputs and outputs of the
  task-activities, in the general task-flows
  obtained above.
• Define the task-context roles on the basis of
  these object-flows. By task-context roles, we
  mean the role-concepts dependent on the whole
  process of a task.
• Extract the domain terms which play a
  task-context role.
• Organization of domain concepts
• Discriminate between the roles dependent on the
  domain concepts and the basic concepts.
• Organize the domain concepts in an is-a hierarchy

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RapidOWL Agile methodology

• domain experts initially express all facts they
  assume as true by means of statements
• More experienced domain experts assist in
  restructuring, interlinking and consolidating the
  gathered data
• Knowledge engineers can support such a community
  of domain experts with advice for reasonable
  representation methods and by providing ontology
  evolution and data migration strategies.
• Knowledge engineers can further enrich the
  knowledge base with logical ontology axioms

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Practical development guide Ontology 101

• Determine the domain and scope of the ontology
• Competency questions for determining scope
• Consider reusing existing ontologies
• Enumerate important terms in the ontology
• Define the classes and the class hierarchy
• Top-down approach from the most general
  concepts to the most specific
• Bottom-up approach
• Combination (middle-out)
• Define the properties of classes - slots

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Practical development guide Ontology 101

• Define the facets of slots
• Slot cardinality
• Slot-value type (Number, String, Instance,)
• Domain and range
• Create instances

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Methodology conclusions

• Most methodologies depend on what you need to do.
  Establish this first!
• Work in teams to gather concepts in the ontology
• Group terms according to properties and create
  the is-a hierarchy
• Establish the relations between concepts and the
  relation properties
• Validate the ontology create a documentation

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Conclusions and practical observations

• How the development process should look like
• How the actual process takes place

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Middle layer guidelines

• (Generic constraints and guidelines which specify
  major steps )
• Concepts rather than terms
• Mixed and flexible strategies of Top-down,
  Bottom-up and Middle-out is strongly suggested
• Top-level category should be identified in the
  early phase of the development process to govern
  the rest of the steps.
• Note that you cannot define any concept
  completely in theory. Therefore, do not stick to
  the definition of each term too much.

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Middle layer guidelines

• When you deal with a concept, identify its main
  components that is, part-of relation as well
  as its main attributes.
• Arrange and resolve the terminological issues(how
  to name a concept) at the last step.
• Put a higher priority on is-a hierarchy
  construction than term definition. Carefully
  designed is-a hierarchy gives you a correct
  context to define a term.

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Bottom layer guidelines

• Determine an essential property for each concept
  and instance. Having an essential property of
  each concept help you a lot.
• Each subclass of a super class is distinguished
  by the values of exactly one attribute of the
  super class.
• Proper use of is-a relation should inherit the
  Essential property of its super classes.
• Clear and consistent differentiation between
  basic concepts (man, rice, oil, etc.) and role
  concepts (teacher, food, fuel, etc.)

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Bottom layer guidelines

• Do not worry about the vagueness of the boundary
  between similar concepts. Most boundaries between
  concepts are vague.
• Class partition is not a part-of relation. Ex.
  Male is not part-of human.
• When you notice you do not have an appropriate
  term to represent a concept you identify, do not
  hesitate to coin a new term. The new term could
  be temporary which will be fixed at the last
  stage.
• Consult a reliable upper ontology when you find
  the necessity of a general and high level
  distinction of categories.

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Usual problems

• Class or individual?
• A set of individuals is countable
• Every individual has a clear identity
• If 2 concepts have equivalent descriptions then
  they represent the same concept
• Descriptions of individuals can change
• Changes of individuals do not alter the class
  hierarchy
• Choosing class vs. individual depends on
  granularity

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Usual problems

• Concept or property
• Person concept
• Mother is not a concept. It only exists as a
  concept if we consider the relation between 2
  persons.
• There are usually conventions for choosing
  property names hasMother, hasGenre
• Properties that change over time extrinsic
• Properties that dont change over time -
  intrinsic

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Usual problems

• Difficult to reason about individuals
• Reasoning is usually performed at the
  concept/class level

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Practical example - PC ontology

• Objectives
• Well define the notion of computer and of
  computer part as well as the relations between
  computer parts and compatibility constraints that
  appear when putting a computer together
• Competency questions
• Which of the processors in stock is compatible
  with the following motherboard?
• Having a configuration we need to establish if it
  is correct
• Build a configuration with given constraints and
  using components with lowest prices

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Practical example - PC ontology

• Extracting the concept ontologies
• No similar ontologies
• Using taxonomies from e-commerce web sites
• Ex concept of motherboard

Shop 1 Shop 2 Shop 3
Manufacturer Manufacturer Manufacturer
Model Name Cod producer, Platform
Socket CPU Socket
Chipset Chipset Chipset
I/O FSB/ HTT BUS
Sound Audio Sound
Slots PCIe, AGP/PCI
IDE/SATA Connectors PATA, Connectors SATA IDE/SATA
Memory Memory Memory
LAN Retea LAN
Price Price Price
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Concept list

• Speakers, WebCam, Carcasa, Card Reader,
  HeadPhones, Microphone, Cooler, Fax-Modem, Floppy
  Disk, Hard Disk, Printer, Memory, Monitor, Mouse,
  Motherboard, Soundcard.

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properties

• Model, number of speakers, Resolution, FPS,
  Sensor type, Interface, Format, card type, RPM,
  airFlow, sound level, Chipset, Dimension,
  Capacity, Cache, printing speed, Printer type,
  Mhz, reading speed(MB/s), writing speed(MB/s),
  Frequency (min, max), Color, Dot pitch, Socket,
  I/O, Sound, Memory, Slot, LAN, IDE/SATA,
  Connectors, CacheL2, CacheL1, FSB, Tehnology,
  Color depth, has Remote, Format TV, Format
  Capture,

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Defining classes

• Top-down
• Component
• Motherboard
• Motherboard with socket 939
• Motherboard with socket 754
• Processor

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Defining properties constraints

• Component Producer
• Processor socket, frecquency
• Constraints
• Cardinalitaty 1 component has 1 producer
• Domain-range hasProducer has domain Component
  and has range Company

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References

• Methontology - http//speech.inesc.pt/joana/prc/a
  rtigos/06c20METHONTOLOGY20from20Ontological20A
  rt20towards20Ontological20Engineering20-20Fer
  nandez,20Perez,20Juristo20-20AAAI20-201997.p
  df
• TOVE - https//eprints.kfupm.edu.sa/50622/1/50622.
  pdf
• Guidelines - http//www.ei.sanken.osaka-u.ac.jp/pu
  b/miz/Part2V3.pdf
• RapidOWL - http//citeseerx.ist.psu.edu/viewdoc/do
  wnload?doi10.1.1.60.1894reprep1typepdf
• Ontology Development 101 - http//protege.stanford
  .edu/publications/ontology_development/ontology101
  -noy-mcguinness.html