Word association norms, mutual information, and lexicography
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Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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This paper introduces a scheme, which we call the baseline method, to define a measure of term representativeness and measures defined by using the scheme. The representativeness of a term is measured by a normalized characteristic value defined for a set of all documents that contain the term. Normalization is done by comparing the original characteristic value with the characteristic value defined for a randomly chosen document set of the same size. The latter value is estimated by a baseline function obtained by random sampling and logarithmic linear approximation. We found that the distance between the word distribution in a document set and the word distribution in a whole corpus is an effective characteristic value to use for the baseline method. Measures defined by the baseline method have several advantages including that they can be used to compare the representativeness of two terms with very different frequencies, and that they have well-defined threshold values of being representative. In addition, the baseline function for a corpus is robust against differences in corpora; that is, it can be used for normalization in a different corpus that has a different size or is in a different domain.