Calculating association between technical terms based on co‐occurrences in keyword lists of academic papers

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Abstract
In this paper, the authors evaluate a method to calculate association between specialized terms using co‐occurrence information in author keywords from academic papers. When author keywords found in academic paper databases are used, co‐occurrence information in units of separate compound words can easily be obtained. However, because only a few words co‐occur in one paper, the problem of data sparseness arises. Thus, in this paper, the authors take into consideration indirect co‐occurrence relationships when computing relatedness. They create a large‐scale terminology graph which connects sets of keywords for a paper using co‐occurrence relationship links, then define the distance between two sets of terms using the average path length. In addition, the authors evaluate the validity of their proposed method for calculating association by applying the terminology graph created using a real, large‐scale academic paper database to the problem of automatic classification of texts, then compare the results to when direct co‐occurrence and context vectors are used. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(3): 85–95, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.1197

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