Date post: | 25-Dec-2015 |
Category: |
Documents |
Upload: | charla-strickland |
View: | 216 times |
Download: | 0 times |
LLogics for DData and KKnowledgeRRepresentation
Towards Infrastructure, Methodology and Principles for Ontology Development
Fausto Giunchiglia and Biswanath Dutta
Fall - 2011
Outline Introduction
Knowledge Representation (KR) Ontology
Domain Facet DERA Mapping Methodology Principle Demo : Domain Modeling
2
Knowledge Representation (KR) “…is about building models of the world, of a particular
domain or problem, which allow automatic reasoning and interpretation”
Fundamental Goal is to represent knowledge in a manner that facilitates
inferencing new knowledge (i.e. drawing conclusions) from the knowledge base
3
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
According to (Crawford & Kuipers, 1990): It must have a reasonably compact syntax. It must have a well defined semantics so that one can
say precisely what is being represented. It must have sufficient expressive power to represent
human knowledge. It must have an efficient, powerful, and understandable
reasoning mechanism It must be usable to build large knowledge bases.
Crawford, J. M. & Kuipers, B. (1990). ALL: Formalizing Access Limited Reasoning. Principles of semantic networks: Explorations in the representation of knowledge, Morgan Kaufmann Pub., 299-330.
4
Knowledge Representation Properties
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Knowledge Representation Issues KR issues:
How do people represent knowledge? What is the nature of knowledge? Do we have domain specific schema or generic, domain
independent schema? How much it needs to be expressive?
5
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Ontology “formal, explicit specification of a shared
conceptualisation” – Gruber, 1993
Models a domain consisting of shared vocabulary with the definition of objects and/or concepts and their properties and relations
A structural framework for organizing information, and used as a form of KR in the fields like, AI, SW, Lib. Sc., Inf.
Architecture, etc.
Ontology as a language resource
6
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Ontology Properties Some of the ontological properties are:
Extendable
Reusable
Flexible
Robust …
7
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Domain An area of knowledge or field of study that we are
interested in or that we are communicating about
Example: Computer science, Artificial Intelligence, Soft computing,
Social networks, …Library science, Mathematics, Physics, Chemistry, Agriculture, Geography, …
Music, Movie, Sculpture, Painting, …Food, Wine, Cheese, …Space,…
8
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Domain (contd…) A domain can be decomposed into its several
constituents, and Each of them denotes a different aspect of entities
An example from Space domain: by region, by body of water, by landform, by populated places, by administrative division, by land, by agricultural land, by facility, by altitude, by climate,…
Each of these aspects is called facet
9
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Facet A hierarchy of homogeneous terms describing an
aspect of the domain, where each term in the hierarchy denotes a different concept
E.g., Body of water(e.g., River, Lake, Pond, Canal), Landform
(e.g., mountain, hill, ridge), facility (e.g., house, hut, farmhouse, hotel, resort), etc.
language facet (e.g., English, Hindi, Italian,), property facet, author facet, religion facet (e.g., Christian, Hindu, Muslim), commodity facet, etc.
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
DERA Is a Facet based knowledge organization framework It is is independent from any specific domain Allows building domain specific ontologies Is logically sound Has mapping to Description Logic Decidable
Designed by the UniTn KnowDive group
11
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
DERA Surface Structure In the surface level, it has the following components:
D – Domain E – Entity R – Relation A – Attribute
12
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Domain (D) A DERA domain is a tuple of,
D = <E, R, A>
13
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Entity (E) an elementary component that consist of entity
classes and their instances, having either perceptual correlates or only conceptual existence in a domain in context
E = <{C} + {E'}> Where,
C = Entity class – consists of core classes representing the entities;
E' = Entity (also called object) – consists of real world named entities, that is the instantiation of the entity classes C.
14
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Entity (E) (contd…) Entity class (C) :
Represents the essence of the domain under consideration;
Consists of the core classes representing a domain in context
E.g., Consider the following classes in context of Space domain: Mountain, Hill, Lake, River, Canal, Province, City, Hotel,...
15
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Entity (E) (contd…) Entity (E') :
Are the real world named entities An extension of the real world entities
E.g., The Himalaya, Monte Bondone, Lake Garda, Trento, Povo, Hotel
America,...
16
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Entity (E) (contd….)
17
E.g., An example from a domain Space
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Relation (R) An elementary component consists of classes
defining the relations between entities
R = <{r}>
A relation is a link between two entities (E') Builds a semantic relation between the entities
E.g., Some relations (spatial) from Space domain: near,
adjacent, inside, before, center, sideways, etc.
18
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Attribute (A) An elementary component consists of classes
expressing the characteristics of entities
A = <{A'}, {C}>
An attribute is any property, qualitative, quantitative or descriptive measure of an entity
19
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Attribute (A) (contd…) Datatype Attribute (A'):
A datatype attribute includes the attribute classes that accounts the quality or quantity of an entity within a domain
E.g., latitude, longitude (of a place):
450 N, 180 S altitude (of a mountain):
8000ft, 2400m. high, low
depth (of a lake): deep, shallow 100ft., 20m.
20
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Attribute (A) (contd…) Descriptive Attribute (C):
It includes the attribute classes that describe the entities under a domain in consideration
The value of a descriptive attribute could consists of a single string or a set of strings
E.g., natural resource (of a place):
coal, natural gas, oil, … architectural style (of a castle):
{Classical architecture, Greek architecture, Roman architecture, Bauhaus, etc.}
history (of a place) ……….
climbing route (to a mountain) ……………….
21
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Mapping From DERA to DL
Entity classes (C) -> Concepts Relation (R) -> Roles Datatype attribute (A') -> Roles Descriptive attribute (C) -> Roles Entity (E') -> Individuals
22
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Methodology Step 1: Identification of the atomic concepts Step 2: Analysis (per genus et differentiam) Step 3: Synthesis Step 4: Standardization Step 5: Ordering
Following the above steps leads to the creation of a set of facets. They constitute a faceted representation scheme for a domain
23
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Ontological Principle Relevance (e.g.,breed is more realistic to classify the universe of cows
instead of by grade) Ascertainability (e.g., flowing body of water) Permanence (e.g., Spring- a natural flow of ground water) Exhaustiveness (e.g., to classify the universe of people, we need both
male and female) Exclusiveness (e.g., age and date of birth, both produce the same
divisions) Context (e.g., bank, a bank of a river, OR, a building of a financial
institution) Important: helps in reducing the homographs
Currency (e.g., metro station vs. subway station) Reticence (e.g., minority author, black man) Ordering
Important: ordering carries semantics as it provides implicit relations between the coordinate terms
24
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Step 1: identification of the atomic concepts
Sources of the concepts WordNet GeoNames (357/663 classes) TGN Literature
25
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Step 1: identification of the atomic concepts (2)
Some of the relevant sub-trees in WordNet are: location artifact, artefact body of water, water geological formation, formation land, ground, soil land, dry land, earth, ground, solid ground, terra firma
Note: not necessarily all the nodes in these sub-trees need to be part of the space domain. For example, the descendants of artifact, like, article, anachronism, block, etc. are not.
26
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Hill Stream River
• the well defined elevated land
• formed by the geological formation (where geological formation is a natural phenomenon)
• altitude in general >500m
• the well defined elevated land
• formed by the geological formation, where geological formation is a natural phenomenon
• altitude in general <500m
• a body of water
• a flowing body of water
• no fixed boundary
• confined within a bed and stream banks
• a body of water
• a flowing body of water
• no fixed boundary
• confined within a bed and stream banks
• larger than a brook
Mountain
Analysis
27
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Body of water
Flowing body of waterStream
BrookRiver
Stagnant body of waterPond
Landform
Natural depressionOceanic depression
Oceanic valleyOceanic trough
Continental depressionTroughValley
Natural elevationOceanic elevation
SeamountSubmarine hill
Continental elevationHillMountain
* each term in the above has gloss and is linked to synonym(ous) terms in the knowledge base
Synthesis
28
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Space [Domain] by geographical feature [Entity class]
by water formation by land formation by land by administrative division …
by relations [Relation] spatial relation
direction, internal, external, longitudinal, sideways, etc. functional relation (e.g., primary inflow, primary outflow) …
by attribute [Datatype attribute]
latitude Longitude dimension …
[Descriptive attribute] Natural resource Architectural style Time zone ph History …
Facets and sub-facets
29
INTRODUCTION :: DOMAN :: FACET :: DERA :: MAPPING :: METHODOLOGY :: PRINCIPLE :: DEMO
Log-in: http://uk.disi.unitn.it/resources/html/UKDomain.html