Comparing a clustering density criteria of temporal patterns of terms obtained by different feature sets

Authors:
Hidenao Abe;Shusaku Tsumoto
Affiliations:
Department of Medical Informatics, Shimane University, School of Medicine, Izumo, Shimane, Japan;Department of Medical Informatics, Shimane University, School of Medicine, Izumo, Shimane, Japan
Venue:
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Year:
2011

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Abstract

In this paper, we present a comparison of similarity measures of temporal patterns of term usages in sets of documents. In order to find out remarkable trends in sets of documents, temporal text mining methods have been developed by combining text mining and temporal pattern extraction. However, most conventional methods are not treated temporal behaviors of the values of importance indices explicitly. By separating the calculation process of the importance indices and the temporal pattern extraction, we have developed a method for finding temporal patterns of term usages based on the importance indices. Then, we obtained two sets of temporal patterns from a set of bibliographical documents by using two sets of features; one is based on the values of each index, the other is the features of the linear trends based on linear regression. After obtaining the two sets of the temporal patterns, we compare a similarity measure between the terms included in each set of temporal patterns.