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All Journal Infolitika Journal of Data Science
Takeuchi, Keita
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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Similarity-Based Network in the Industrial Community of Joyo City Takeuchi, Keita; Iwasaki, Masashi; Shinjo, Masato
Infolitika Journal of Data Science Vol. 3 No. 1 (2025): May 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v3i1.267

Abstract

Data utilization is becoming increasingly widespread in a variety of fields around the world, and has become especially important in the industrial world. Data utilization techniques and approaches can contribute to the development of not only individual companies but also certain groups of companies. In this paper, we consider the industrial structure of Joyo City, Japan, by analyzing data collected through interviews with company presidents and managers. The main purpose of this paper is to grasp it in terms of similarity across industrial categories. We first express the features of each company as a vector with entries determined from the interview data. We then compute vector similarities in order to draw a graphical network, in which nodes corresponding to similar companies are linked by an edge. From the resulting network, we derive the most similar companies in the same and different industrial categories for each company. Moreover, we then classify Joyo City's companies into new groups across the standard categories.
Co-Authors Iwasaki, Masashi Shinjo, Masato