An automatic selection method of key search algorithms based on expert knowledge bases

Abstract

This paper proposes an automatic selection method for key search algorithms. The methodology has been implemented in a system called KEALASE (KEy-search Algorithm SElection). Key search algorithms are selected according to the user's requirements through interaction with KEALSE which bases its inferences on an evaluation table. The evaluation table contains values rating the performance of each key search algorithm for the different searching properties. The proposed selection algorithm is based on a step by step reduction of key search algorithms and searching properties. The paper also proposes assistance facilities that consist of both a support function and a program synthesis function. Experimental results show that the appropriate key search algorithms are effectively selected, and that the necessary number of questions asked, to select the appropriate algorithm, is reduced to less than half of the total number of possible questions. The support function is useful for the user during the selection process, and the program synthesis function fully translates a selected key search algorithm into high level language in an average of less than 1 hour.