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    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

    Data extraction from form imagesDatabase and Expert Systems Applications

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    In this paper, we describe a system capable of extracting textual information from images of structured documents. In particular the model and the algorithms we described are used to process forms in which the information fields can not be located only by their position on the page, but can also be identified after locating the corresponding instruction fields. The proposed model is based on attributed relational graphs and performs form registration and location of information fields using algorithms based on the hypothesize-and-verify paradigm. The location of instruction fields is carried out in an holistic way, by using connectionist models. © Springer-Verlag Berlin Heidelberg 1995
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