Knowledge Representation Part I Ontology Jan Pettersen Nytun Knowledge Representation Part I, JPN, UiA

Knowledge Representation Part I, JPN, UiA Outline Knowledge Reasoning / logical Consequence Ontology Ontology in philosophy Ontology in computer science Different types of ontologies Levels of ontological precision Knowledge Representation Part I, JPN, UiA

is is AI require when to use facts/understanding about a particular subject a symbol or thing which represents something else (refers to, stands for) is is Knowledge Representation AI require when to use computer-understandable form when we can not use the “original”, like things in the natural world or concepts Knowledge Representation Part I, JPN, UiA

Knowledge Representation Part I, JPN, UiA From Wikipedia, the free encyclopedia (Knowledge representation and reasoning) Knowledge Representation (KR) is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge. Knowledge Representation Part I, JPN, UiA

Knowledge Representation Part I, JPN, UiA Knowledge Base A database for knowledge management It provides means for information to be: Collected Organized Shared, searched and utilized (new information may be inferred) Knowledge Representation Part I, JPN, UiA

Knowledge Engineering Get knowledge about some subject and represent it in a computable form for some purpose. The knowledge engineer tells the system what is true. Knowledge Representation Part I, JPN, UiA

Knowledge Representation Part I, JPN, UiA Outline Knowledge Reasoning / logical Consequence Ontology Ontology in philosophy Ontology in computer science Different types of ontologies Levels of ontological precision Knowledge Representation Part I, JPN, UiA

Asserted and Inferred Statements The system knows how to infer new facts and solutions – the user may form questions and then the system gives answers. Knowledge Base Asserted Statements Inferred Statements Entailment Asserted Statements Inferred Statements Inferred statements comes as a logical consequence of the asserted statements and logical rules Knowledge Representation Part I, JPN, UiA

Entailment (Logical Consequence) Example: Family Information Identify “something” as being Person: Person(Ola), Person(Kari), Person(Marie), Person(Jan), … Gender of person: Female(Kari), Male(Ola), Female(Marie), Male(Jan), … Who is parent to a person: Parent(Ola, Marie), Parent(Kari, Marie), … Knowledge Base Asserted Statements: Person(Ola), Person(Kari), Person(Marie),Person(Jan), Female(Kari), … Inferred Statements Knowledge Representation Part I, JPN, UiA

Example: Family Information … Continues Given the right logical rules, then family relations can be derived: Parent(x, y) and Female(x)  Mother(x, y) ??  Daughter (x, y) ??  Brother(x, y) Knowledge Base Asserted Statements: Person(Ola), Person(Kari), Person(Marie),Person(Jan), Female(Kari), Male(Ola), Female(Marie), Male(Jan), Parent(Ola, Marie), Parent(Kari, Marie), … Inferred Statements: Mother(Kari, Marie), … Knowledge Representation Part I, JPN, UiA

Knowledge Representation Part I, JPN, UiA Complex relations: Consanguinity - KONSANGUNITI Knowledge Representation Part I, JPN, UiA

Knowledge Representation Part I, JPN, UiA Outline Knowledge Reasoning / logical Consequence Ontology Ontology in philosophy Ontology in computer science Different types of ontologies Levels of ontological precision Knowledge Representation Part I, JPN, UiA

What is an Ontology in Regard to Philosophy? From Wikipedia, the free encyclopedia

What is an Ontology in Regard to Philosophy? Continues… Smith [1] the essence of ontology: “provide a definitive and exhaustive classification of entities in all spheres of being.”

What is an Ontology in Computer Science? Knowledge represented in a formal way: - a hierarchy of concepts within a domain, - a shared vocabulary to denote the types, - properties and interrelationships of those concepts.

What is an Ontology in Computer Science? … Continues An ontology is a specification of a conceptualization that is designed for reuse across multiple applications and implementations. …a specification of a conceptualization is a written, formal description of a set of concepts and relationships in a domain of interest. Peter Karp (2000) Bioinformatics 16:269

Ontology vs Knowledge Base" “The Artificial-Intelligence literature contains many definitions of an ontology; many of these contradict one another. … An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins.” [http://protege.stanford.edu/publications/ontology_development/ontology101-noy-mcguinness.html] Knowledge Representation Part I, JPN, UiA

Not All Would Agree On The Following: “An ontology is, very roughly, a formal representation of a domain of knowledge. It is an abstract entity: it defines the vocabulary for a domain and the relations between concepts, but an ontology says nothing about how that knowledge is stored (as physical file, in a database, or in some other form), or indeed how the knowledge can be accessed. A knowledge base is a physical artifact: it is a database, a repository of information that can be accessed and manipulated in some predefined fashion. The knowledge in a knowledge base can be said to be modeled according to an ontology.” [http://answers.semanticweb.com/questions/21500/what-is-the-difference-between-knowledge-base-and-ontology] Knowledge Representation Part I, JPN, UiA

Types of Ontologies [Ref. Medical Informatics: Knowledge Management and Data Mining in Biomedicine]: From Wikipedia, the free encyclopedia: In computer science and information science, an ontology is… a practical application of philosophical ontology.

Types of Ontologies… Continues An upper ontology - also called top-level ontology or foundation ontology - describes the most general concepts that are the same across all knowledge domains (e.g., Entity). Knowledge Representation Part I, JPN, UiA

Types of Ontologies… Continues [Ref. Medical Informatics: Knowledge Management and Data Mining in Biomedicine]: General ontologies represent knowledge at an intermediate level of detail independently of a specific task… theories of time and space, for example... Knowledge Representation Part I, JPN, UiA

Types of Ontologies… Continues [Ref. Medical Informatics: Knowledge Management and Data Mining in Biomedicine]: Domain ontologies represent knowledge about a particular part of the world, such as medicine, and should reflect the underlying reality through a theory of the domain represented. Knowledge Representation Part I, JPN, UiA

Types of Ontologies… Continues [Ref. Medical Informatics: Knowledge Management and Data Mining in Biomedicine]: …ontologies designed for specific tasks are called application ontologies. Conversely, reference ontologies are developed independently of any particular purpose… Knowledge Representation Part I, JPN, UiA

Descriptive Ontology for Linguistic and Cognitive Engineering Knowledge Representation Part I, JPN, UiA

Knowledge Representation Part I, JPN, UiA Outline Knowledge Reasoning / logical Consequence Ontology Ontology in philosophy Ontology in computer science Different types of ontologies Levels of ontological precision Knowledge Representation Part I, JPN, UiA

Knowledge Representation Part I, JPN, UiA Catalog: A list of things. Knowledge Representation Part I, JPN, UiA

From Wikipidia: A Glossary, also known as a vocabulary,… is an alphabetical list of terms in a particular domain of knowledge with the definitions for those terms.

A Taxonomy – also called a class hierarchy - organizes its data into categories and subcategories.

From Wikipidia: In general usage, a thesaurus is a reference work that lists words grouped together according to similarity of meaning (containing synonyms and sometimes antonyms).

From Wikipidia: A database schema …is a structure described in a formal language… and refers to the organization of data as a blueprint of how a database is constructed (e.g., database tables for Relational Databases).

From Wikipidia: In mathematics, an axiomatic system is any set of axioms from which some or all axioms can be used in conjunction to logically derive theorems. A mathematical theory consists of an axiomatic system and all its derived theorems.

Ontology Engineering as a Discipline Example of Process Decide Scope Reuse? Enumerate Terms Studies the methods and methodologies for building ontologies. Define Classes Define Properties Define Constraints Create Instances Knowledge Representation Part I, JPN, UiA

Knowledge Representation Part I, JPN, UiA References [1] Book: David Poole and Alan Mackworth, Artificial Intelligence: Foundations of Computational Agents, Cambridge University Press, 2010, http://artint.info/ Sowa, John F. (2000) Knowledge Representation: Logical, Philosophical, and Computational Foundations, Brooks/Cole Publishing Co., Pacific Grove, CA. Artificial Intelligence: Structures and Strategies for Complex Problem Solving (Addison-Wesley), George F. Luger Smith Barry. Accessed 24th of March, 2013, Ontology: Philosophical and Computational. http: //ontology.buffalo.edu/smith/articles/ontologies.htm Quine WVO. On What There Is. Review of Metaphysics 1948;p. 21–38. Knowledge Representation Part I, JPN, UiA