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    Learning-Oriented Reliability Improvement of Computing Systems From Transistor to Application Level

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    This research was supported in part by 1) Advantest as part of the Graduate School "Intelligent Methods for Test and Reliability" (GS-IMTR) at the University of Stuttgart; 2) funding from National Science Foundation Grants No. CPS 1646235, CCF 1723476 - the NSF/Intel joint research center for Computer Assisted Programming for Heterogeneous Architectures (CAPA) at Arizona State University; 3) National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2022-00165225) at Yonsei University; 4) German Research Foundation (DFG) within the Cluster of Excellence Center for Advancing Electronics Dresden (CFAED) at the Technische Universitat Dresden

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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