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<Paper uid="I05-2043">
  <Title>Trend Survey on Japanese Natural Language Processing Studies over the Last Decade</Title>
  <Section position="5" start_page="254" end_page="254" type="concl">
    <SectionTitle>
7 Conclusion
</SectionTitle>
    <Paragraph position="0"> In this paper, we described a trend survey carried out on Japanese natural language processing studies done over the last ten years. We were able to investigate trend surveys on research areas very easily by treating divided words in titles by a morphological analyzer as the indications of research areas. We displayed the changes in the number of papers put out by each research organization and written on specific research topics. We also displayed the relationship between research organizations and research areas using the dual scaling method. The simple methods we used that are described here made it possible to show many useful results.</Paragraph>
    <Paragraph position="1"> This paper has the following two significant effects: null This paper explained a trend survey on Japanese natural language processing. By reading it, we can understand the trends in research on Japanese natural language processing. For example, we can find out which research areas were studied more often and we can see which research organizations were involved in studying natural language processing. We can also see which research organization studied a particular research area most often over the ten-year period. null We used natural language processing to carry out the trend survey described here.</Paragraph>
    <Paragraph position="2"> For example, we automatically detected the indication of a research area from words used in titles by using a morphological analyzer. In addition, we displayed words that were extracted by the morphological analyzer in several ways to display the results of the trend survey effectively. The methods used in this paper would be useful in other trend surveys.</Paragraph>
    <Paragraph position="3"> In short, this paper is useful for recognizing trends in Japanese NLP and for constructing methods of supporting trend surveys using NLP.</Paragraph>
    <Paragraph position="4"> In the future, we would like to perform an international trend survey on natural language processing using international conference and journal papers such as IJCNLP, ACL, and the Journal of Computational Linguistics. We would also like to do trend surveys on other topics such as AI, biology, politics, and sociology.</Paragraph>
    <Paragraph position="5"> The kinds of investigations we did can easily be altered to do many other kinds of investigations as well. For example, we can use the dual scaling method by investigating the relationship between the reference years and the research organizations/areas. We can also use the representation in contour for the relationship between research organizations and research areas. Although we showed the data in ascending order of the average value of the published years, we could show the data in different order, for example, the order of the total number of papers or the order of the location, i.e., showing similar research organizations/areas that are located near each other by clustering research organizations/areas using their cooccurrent words. We would like to continue to study these kinds of support methods for trend surveys in the future.</Paragraph>
  </Section>
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