Identifying Tiers of Influence in Artificial Intelligence Research: I

Abstract

As a step in the direction of helping researchers, students, and developers to stay abreast of ongoing research work in the field of artificial intelligence (AI) in general, and expert systems (ES) in particular, we have conducted a large-scale citation analysis to identify the most influential journals for AI/ES research. We use a multifaceted methodology for assessing journal influence (i.e. quality and relevance). The methodology assesses each cited journals from two sets of base journals on several dimensions: breadth of recognition, consistency of recognition, trend of recognition, and intensity of recognition. Here, in Part I, we describe how these assessments are established objectively via data collected from base journals with a general AI focus. Part II will extend the set of base journals to include those that are devoted to expert systems (ES) research. The main results are tiers and a ranking that identify the most influential, important journals publishing AI/ES research. © 1996 Wiley Periodicals, Inc.