Search Results for author: Teruaki Hayashi

Found 6 papers, 0 papers with code

Extraction of Constituent Factors of Digestion Efficiency in Information Transfer by Media Composed of Texts and Images

no code implementations17 Feb 2023 Koike Hiroaki, Teruaki Hayashi

The development and spread of information and communication technologies have increased and diversified information.

Feature Concepts for Data Federative Innovations

no code implementations5 Nov 2021 Yukio Ohsawa, Sae Kondo, Teruaki Hayashi

In this short paper, such a creative communication is reviewed, showing a couple of appli-cations, for example, change explanation in markets and earthquakes, and highlight the feature concepts elicited in these cases.

Clustering

Hierarchical entropy and domain interaction to understand the structure in an image

no code implementations20 Apr 2021 Nao Uehara, Teruaki Hayashi, Yukio Ohsawa

It aims to help people interpret and explain what the structure in an image looks like from two indicators that change with the size of the region and the component.

Data Combination for Problem-solving: A Case of an Open Data Exchange Platform

no code implementations21 Dec 2020 Teruaki Hayashi, Hiroki Sakaji, Hiroyasu Matsushima, Yoshiaki Fukami, Takumi Shimizu, Yukio Ohsawa

The results indicate that even datasets that have a few variables are frequently used to propose solutions for problem solving.

Computers and Society

Detecting and explaining changes in various assets' relationships in financial markets

no code implementations21 May 2020 Makoto Naraoka, Teruaki Hayashi, Takaaki Yoshino, Toshiaki Sugie, Kota Takano, Yukio Ohsawa

We study the method for detecting relationship changes in financial markets and providing human-interpretable network visualization to support the decision-making of fund managers dealing with multi-assets.

Decision Making Time Series +1

Extracting and Validating Explanatory Word Archipelagoes using Dual Entropy

no code implementations22 Feb 2020 Yukio Ohsawa, Teruaki Hayashi

An island here means the local sequence of sentences where the word is emphasized, and an archipelago of a length comparable to the target text is extracted using the co-variation of entropy A (the window-based entropy) on the distribution of the word's occurrences with the width of each time window.

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