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An interactive fault diagnosis expert system for a helpdesk application
Author(s) -
Zhao Ming,
Leckie Chris,
Rowles Chris
Publication year - 1996
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.1996.tb00120.x
Subject(s) - computer science , inference , inference engine , knowledge representation and reasoning , expert system , event (particle physics) , representation (politics) , sequence (biology) , artificial intelligence , machine learning , data mining , physics , quantum mechanics , politics , biology , political science , law , genetics
This paper presents work on an interactive fault diagnosis expert system for a helpdesk application. A knowledge representation and inference algorithm is proposed to satisfy three design specifications: (1) no parallel event exists in human fault reporting; (2) the diagnostic sequence is unpredictable, and (3) the inference engine is passive in an event‐driven environment. A lattice data structure is designed for knowledge representation, which is generated automatically from a script of decision rules. The inference engine works in a transaction‐like style by prompting and responding to the user according to the knowledge in the lattice. It can explicitly guide the inference sequence, as well as respond to ad hoc input from the user.