Hiroki Sakaji


2023

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Proceedings of the Sixth Workshop on Financial Technology and Natural Language Processing
Chung-Chi Chen | Hen-Hsen Huang | Hiroya Takamura | Hsin-Hsi Chen | Hiroki Sakaji | Kiyoshi Izumi
Proceedings of the Sixth Workshop on Financial Technology and Natural Language Processing

2021

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Economic Causal-Chain Search and Economic Indicator Prediction using Textual Data
Kiyoshi Izumi | Hitomi Sano | Hiroki Sakaji
Proceedings of the 3rd Financial Narrative Processing Workshop

2020

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Learning Company Embeddings from Annual Reports for Fine-grained Industry Characterization
Tomoki Ito | Jose Camacho Collados | Hiroki Sakaji | Steven Schockaert
Proceedings of the Second Workshop on Financial Technology and Natural Language Processing

2019

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Financial Text Data Analytics Framework for Business Confidence Indices and Inter-Industry Relations
Hiroki Sakaji | Ryota Kuramoto | Hiroyasu Matsushima | Kiyoshi Izumi | Takashi Shimada | Keita Sunakawa
Proceedings of the First Workshop on Financial Technology and Natural Language Processing

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Economic Causal-Chain Search using Text Mining Technology
Kiyoshi Izumi | Hiroki Sakaji
Proceedings of the First Workshop on Financial Technology and Natural Language Processing

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mhirano at the FinSBD Task: Pointwise Prediction Based on Multi-layer Perceptron for Sentence Boundary Detection
Masanori Hirano | Hiroki Sakaji | Kiyoshi Izumi | Hiroyasu Matsushima
Proceedings of the First Workshop on Financial Technology and Natural Language Processing

2016

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Creating Japanese Political Corpus from Local Assembly Minutes of 47 prefectures
Yasutomo Kimura | Keiichi Takamaru | Takuma Tanaka | Akio Kobayashi | Hiroki Sakaji | Yuzu Uchida | Hokuto Ototake | Shigeru Masuyama
Proceedings of the 12th Workshop on Asian Language Resources (ALR12)

This paper describes a Japanese political corpus created for interdisciplinary political research. The corpus contains the local assembly minutes of 47 prefectures from April 2011 to March 2015. This four-year period coincides with the term of office for assembly members in most autonomies. We analyze statistical data, such as the number of speakers, characters, and words, to clarify the characteristics of local assembly minutes. In addition, we identify problems associated with the different web services used by the autonomies to make the minutes available to the public.