Semantics OverviewSharon L. Bolding, PhD

Jan 26, 2008

Historic context

• Cross-disciplinary field: philosophy, linguistics, computer sciences, cognitive sciences

• Goal is to represent meaning of knowledge unambiguously so that it can be understood, shared and used by computational agents

• Computational focus emerged in the 1980s, AI community work in expert systems and formal semantics, such as Situational Theory

Historic context cont.

• Philosophy: Socrates questioning, Plato’s study of epistemology, the nature of being

• Aristotle shifted the debate to terminology, development of logic as a precise method for reasoning about knowledge

• Middle Ages: Anselm of Canterbury and the existence of God, theories of reference and mental language, Scholastic logic

• Semantic Network: First used by Porphyry in the 3rd century to represent Aristotle’s hierarchy of species

Semantics—Classic Taxonomy Tree, Porphyry

Substance

Body

Living

Animal

Human

Material

Animate

Sensitive

Rational

Socrates

Plato Aristotle Etc.

Immaterial

Inanimate

Insensitive

Irrational

Spirit

Mineral

Plant

Beast

Supreme genus

Differentiae

Subordinate genera

Species

Individuals

Differentiae

Subordinate generaDifferentiae

Subordinate generaDifferentiae

A more modern view

Berners-Lee

McGuinness

Definitions

• An ontology is a specification of a conceptualization— Tom Gruber

• Knowledge engineering is the application of logic and ontology to the task of building computational models of some domain for some purpose — John Sowa

• Knowledge representation means that knowledge is formalized in a symbolic form, that is, to find a symbolic expression that can be interpreted —Klein and Methlie

• The task of classifying all the words of language, or what’s the same thing, all the ideas that seek expression, is the most stupendous of logical tasks. Anybody but the most accomplished logician must break down in it utterly; and even for the strongest man, it is the severest possible tax on the logical equipment and faculty — Charles Sanders Peirce

• A data model describes data, or database schemas - an ontology describes the world — Adam Farquhar, Stanford

Semantics—Ontologies

OLP Schema for Sentences using this Ontology Linking Predicate

instance (instance ITEM CLASS)

subclass (subclass SUBCLASS CLASS)

subrelation (subrelation SPECIAL-RELATION GENERAL-RELATION)

subAttribute (subAttribute SPECIAL-ATTRIBUTE GENERAL-ATTRIBUTE)

Ontologies have relationships…

Heart Human

part

part

part

Hair Colorattribute

Brown

Blond

Black

attribute

attribute

… and attributes.

Ontology based technologies

• Search• Artificial Intelligence• Natural Language Processing (NLP)• Semantic Web• Speech generation• Automatic translation systems • Profiling & finding people

Example: Semantics and Search

• Keyword Search ≠ Semantic Search– Keywords = Words, not context– Semantic Search = Concepts +

Context• Semantics in Technology

– Taxonomy - A structure of known human knowledge for a specific domain, organized into categories and subcategories

– Ontology - Defines meanings and relationships for each category

How search technology uses ontologies

• Servers: Semantic Analysis of Sources– Multiple ontologies used to

semantically analyze and rank content into an index

• Users: Categories as Search Criteria– Build queries using categories

from multiple ontologies

Ontologies cont.

• Add 1 Category to a query

• 1 Category + 8 definitions

• = 9 keyword searches at once!

• Cross-fertilization

• Ask about concepts, get relevant answers

Search using ontologies

When the entire body of documents is mapped, it forms the index graph

Index

Search using ontologies

CompareThe document to index graph

Search using ontologies

RetrieveDocuments by signature

Ontology in XML

Kinds of ontologies

• An upper ontology defines base concepts supporting ontology development (SUMO)

• A domain or classic ontology defines the terminology and concepts relevant to a particular topic or area of interest

• A process ontology defines the inputs, outputs, constraints, relations, terms and sequencing information relevant to business processes (ISO PSL Process Specification Language)

• A service ontology defines a core set of constructs for describing vocabularies and capabilities of services (OWL-S)

Example: Semantic Web

• The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation—Time Berners-Lee

Benefits

• Creates an “open world” scenario, where communications are enabled at a computational level

• Because they are XML-based, ontologies can assist businesses in leveraging existing investments in markup, content and metadata

• Creates policy-based applications for compliance

• Supports less certainty creating informed answers, predictive analytics, etc... rather than binary absolutes

• Reuse of existing knowledge, write once, revise

Example: Call Center Support Application

• Text mining is the key idea powering the application

• Background: Call center supports hardware business, service customers need tech support, product managers provide information into a KB system, phone support staff add real time information to the KB via phone records

Call Center cont.

• Documentation comes from multiple sources, customers may have needs that have never been documented

• Challenges: No feedback loop for product improvements, increased employee & service costs, increased customer dissatisfaction, employees demoralized

• Solutions: Identify conflicting documents, show product relationships, impact of one issue on multiple components & features, traceability for compliance

How to create an ontology

• Prerequisite: Learn XML.• Define domain terms and relationships

– Concepts (classes, nouns)– Identify subclass and superclass relationships

(verbs)– Identify attributes and properties (adj, adv)

including exclusions– Identify any general properties, relations, functions – Restrict slot values (how terms may be entered)– Define individuals– Define interrelationships between individuals (fill in

the slots)– Iterate to improve over time

Classes

• A concept in the domain• A collection of elements with similar

properties• Contains necessary conditions for

membership• A node is a particular instance of a class • Has inheritance: True subclass

relationships are the basis of formal “is-a” hierarchies, where the instance of the subclass is an instance of the superclass

Class hierarchy levels

• Different modes of development:– Top down: general to specific– Bottom up: specifics organized in to general

buckets– Combo: breadth at the top level, then depth at a

few branches to test the design

• Class inheritance is transitive:– A is a subclass of B– B is a subclass of C– Therefore A is a subclass of C

• (See McGuinness and Noy paper in syllabus)

Example: Mercury

• Is it a planet, a car, an element, or a god?

• If car, then exclude god, planet, element• If car, then has physical and spatial

attributes• If car, then has value and utility• Question: does car have psychological

attributes (the kind of car I drive says what?) Do I care?

Ontologies

• Questions?