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Abstract  

This study uses author co-citation analysis to trace prospectively the development of the cognitive neuroscience of attention between 1980 and 2005 from its precursor disciplines: cognitive psychology, single cell neurophysiology, neuropsychology, and evoked potential research. The author set consists of 28 authors highly active in attentional research in the mid-1980s. PFNETS are used to present the co-citation networks. Authors are clustered via the single-link clustering intrinsic to the PFNET algorithm. By 1990 a distinct cognitive neuroscience specialty cluster emerges, dominated by authors engaged in brain imaging research.

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. The Pathfinder Networks (PFNET) algorithm seeks minimum weight paths between nodes. Two parameters must be set: r defines the Minkowski metrics used to compute the distance of a path, while q limits the scope of the minimum-weight paths that will

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Summary Parallel mappings of the intellectual and cognitive structure of Software Engineering (SE) were conducted using Author Cocitation Analysis (ACA), PFNet Analysis, and card sorting, a Knowledge Elicitation (KE) method. Cocitation counts for 60 prominent SE authors over the period 1990 - 1997 were gathered from SCISEARCH. Forty-six software engineers provided similar data by sorting authors’ names into labeled piles. At the 8 cluster level, ACA and KE identified similar author clusters representing key areas of SE research and application, though the KE labels suggested some differences between the way that the authors’ works were used and how they were perceived by respondents. In both maps, the clusters were arranged along a horizontal axis moving from “micro” to “macro” level R&D activities (correlation of X axis coordinates = 0.73). The vertical axis of the two maps differed (correlation of Y axis coordinates = -0.08). The Y axis of the ACA map pointed to a continuum of high to low formal content in published work, whereas the Y axis of the KE map was anchored at the bottom by “generalist” authors and at the top by authors identified with a single, highly specific and consistent specialty. The PFNet of the raw ACA counts identified Boehm, Basili, and Booch as central figures in subregions of the network with Boehm being connected directly or through a single intervening author with just over 50% of the author set. The ACA and KE combination provides a richer picture of the knowledge domain and provide useful cross-validation.

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pruned network called pathfinder network (PFNET), which keeps only those links that do not violate the triangle inequality, stating that the distance between two nodes passing through any group of intermediate nodes must be less than or equal to the

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normalized dissimilarity matrix as input for pathfinder analysis and get the pathfinder result matrix (namely pathfinder network, PFNET), then convert the PFNET to the “.net” file for Pajek 1 . The result is shown as Fig. 1 . Fig. 1

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McCain ( 1998 ) identified 12 research topics in information science between 1972 and 1995, where the two biggest specialties are experimental retrieval and citation analysis. Later on, White ( 2003 ) proposed Pathfinder networks (PFNETs), and found

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