An Abstracted ‘Not So Expert’ System

G.M. McGrath (Australia)


Expert systems; data abstraction; betting.


ED ‘NOT SO EXPERT’ SYSTEM G. Michael McGrath Centre for Tourism and Services Research Victoria University Melbourne, Australia ABSTRACT After falling out of favour during the 1990s, advisory expert systems and their underlying artificial intelligence (AI) technologies are now being used increasingly in organizational decision making activities – particularly, data mining. In this paper, an expert system designed for greyhound race tipping specifically (and investment advice more generally) is described. Our system is distinguished from others in two ways: i) the use of an abstracted schema allows ready extension to other investment domains; and ii) emphasis is placed on reducing complexity where possible – hence, the ‘not so expert’ system. Early indications are that the forecasts produced by our system compare favourably with those of both human experts and previous, relevant decision support systems (DSS).

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