This study describes an analysis of the actual situation in which the distance between representations is measured using natural language processing methods. The distance between representations and neighbor words of each representation were measured by calculating the word embeddings based on the co-occurrence frequencies of the examples in the corpus. As a result of the analysis, we clarified that there were words such as “naku (〈泣く〉, 〈鳴く〉, etc.)”, for which the distance between the representations was far apart and their neighbor words feature each representation, and also, there were words such as "wakaru (〈分かる〉,〈判る〉, etc.)", for which the distance between the representations was close and their neighbor words were difficult to explain the differences. In addition, we also measured the distance between the representations in the Heisei period and the early Showa period, demonstrating that the usage of these representations has changed over time.

The purpose of this study is to construct an LOD model that connects and structures DA-based learning materials and related information. To this end, we develop a LOD dataset for the S×UKILAM learning materials archive by structuring the metadata using machine-readable RDF. The metadata are hierarchized by characteristics centering on the materials, and each resource is assigned a URI to enhance the searchability of the materials and related information. Following this, we develop a SPARQL endpoint to confirm the connection and structuring of the materials and related information. In addition, for users who are not familiar with the SPARQL language, we also develop an application that enables users to intuitively retrieve materials and related information by using metadata items. The result shows that the LOD model can connect DA-based learning materials and related information, and can be retrieved based on the structured metadata. We consider that the results of this study have contributed to the informatization of education and the promotion of the use of digital cultural heritage.

The previous researches approached to the relationship between stories and emotions from various viewpoints. However, the details about the relationships between plot patterns and emotions of readers, protagonists and characters have not been yet clarified. This paper focused on picture books which would have comparatively simple story structures, and developed a dataset for emotions of readers and protagonists and other characters with story structure based on scene units. From the analysis for constructed dataset, those are cleared that “Anger”, “Sadness” and “Anticipation” co-occur for readers and protagonists, “Surprise” co-occurs for readers and all characters, but “Joy”, “Fear”, and “Disgust” don’t co-occur. Moreover, stories were clustered based on chronological shift of emotions, and three types of clusters “tragedy”, “reader satisfaction” and “happy end” were extracted.

In a story, even if the content is the same, the effect on the reader can vary greatly depending on one expression. Therefore, it is assumed that it is useful to analyze the effects of expressions on the reader. In this study, we focused on the concept of "descriptive distance" among the impressions readers receive, and analyzed and clarified stylistic features that affect descriptive distance. The analysis included basic statistical analysis, χ-square test, and co-occurrence analysis for scenes that fulfill the conditions in novels of genres in which the descriptive distance is considered to be near, medium, or far. The analysis suggests that the addition of information and euphemisms, such as the point of view and the narrator of the ground text, increases complexity, and as a result, the descriptive distance becomes closer. Then, based on the analysis results, we created a formula for calculating the descriptive distance, actually calculated the descriptive distance, and conducted an evaluation experiment. We inferred that the closer the descriptive distance is, the easier it is to judge the descriptive distance, and that in scenes with a mixture of descriptive distance features, it is more difficult to judge the descriptive distance

This manuscript presents a comprehensive overview of text data encoded in Unicode, delineating the contents of two dictionaries from Japan's Heian period: Honzō Wamyō and Wamyō Ruijushō. Additionally, it includes an index of Japanese names transcribed into Katakana. The utilization of Unicode facilitates the preservation and dissemination of these historical linguistic resources, contributing significantly to scholarly endeavors in Japanese language studies. The encoded text data not only preserves the linguistic heritage encapsulated within these dictionaries but also opens avenues for further research in Japanese historical linguistics.