Page 190 - DCAP310_INTRODUCTION_TO_ARTIFICIAL_INTELLIGENCE_AND_EXPERT_SYSTEMS

Introduction to Artificial Intelligence & Expert Systems Anil Sharma, Lovely Professional University

Notes Unit 10: Matching Techniques

CONTENTS
Objectives
Introduction

10.1 Structures Used in Matching
10.2 Measure for Matching
10.3 Matching Like Patterns

10.4 Prediction by Partial Matching (PPM)
10.5 Fuzzy Matching Algorithms
10.6 The Rete Matching Algorithm
10.7 Summary
10.8 Keywords

10.9 Review Questions
10.10 Further Readings

Objectives

After studying this unit, you will be able to:
Discuss the Structures used in Matching

Explain how to measure for Matching
Describe Matching Like Patterns
Define Prediction by Partial Matching

Identify Fuzzy Matching Algorithms
Discuss the Rete Matching Algorithm
Introduction

Artificial Intelligence (AI) could be defined as the ability of computer software and hardware to
do those things that we, as humans, recognize as intelligent behavior. Traditionally, those
things include such activities as:
Searching: Finding “good” material after having been provided only limited direction, especially
from a large quantity of available data.
Surmounting Constraints: Finding ways that something will fit into a confined space, taking
apart or building a complex object, or moving through a difficult maze.

Recognizing Patterns: Finding items with similar characteristics, or identifying an entity when
not all its characteristics are stated or available.
Making Logical Inferences: Drawing conclusions based upon understood reasoning methods
such as deduction and induction.

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