Bibliometrics such as the number of papers and times cited are often used to compare researchers based on specific criteria. The criteria, however, are different in each research domain, and are set by empirical laws. Moreover, there are arguments such that the simple sum of metric values works to the advantage of elders. Therefore, this paper attempts to constitute features from time series data of bibliometrics, and then classify the researchers according to the features. In detail, time series patterns, which correspond to knowledge of bibliometrics, are extracted from the large amount of bibliographic datasets, and then a model to classify whether the researchers are "distinguished" or not is created by machine learning techniques. The experiments achieved an F-measure of 81.0% in the classification of 42 researchers in a research domain based on the datasets of Japan Science and Technology Agency and Elsevier's Scopus. In the future, we will conduct verification on a number of researchers in several domains, and then make use of discovering "distinguished" researchers, who are not widely known so far.

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　We propose a system model to develop a subject management system based on FRSAD model and Linked Data. This system can handle multiple subject schemes by using Tbema and Nomen entities defined in FRSAD model. We describe "NIER Textbook Classification" and Nippon Decimal Classification 9th Edition in FRSAD model, and show that those subject information can be connected to bibliographic information based on FRBR model using Linked Data technology.

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　In this research, we attempt to classify and arraign citations in academic articles. They were variable classification type by each previous research, and were not organized has been a problem. First stage, we reorganized their by perspective, (1) significance type ,(2)evaluative type, (3)functional type, (4)morphologic type, (5)location type, (6)sociological type. Second stage, we discussed scaling level, recommended classification scheme, and point to be noted, for perspectives obtained in the first stage. A division that has been built from the complex perspective to separate, by integrating the division, which has been positioned as a different perspective, we create a basic scheme for the citation classification.

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