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Kiyoshi Izumi
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2020 – today
- 2024
- [i5]Takehiro Takayanagi, Masahiro Suzuki, Ryotaro Kobayashi, Hiroki Sakaji, Kiyoshi Izumi:
Is ChatGPT the Future of Causal Text Mining? A Comprehensive Evaluation and Analysis. CoRR abs/2402.14484 (2024) - [i4]Meiyun Wang, Kiyoshi Izumi, Hiroki Sakaji:
LLMFactor: Extracting Profitable Factors through Prompts for Explainable Stock Movement Prediction. CoRR abs/2406.10811 (2024) - 2023
- [j27]Takehiro Takayanagi, Kiyoshi Izumi:
Context-Aware Stock Recommendations with Stocks' Characteristics and Investors' Traits. IEICE Trans. Inf. Syst. 106(10): 1732-1741 (2023) - [j26]Masahiro Suzuki
, Hiroki Sakaji
, Masanori Hirano
, Kiyoshi Izumi:
Constructing and analyzing domain-specific language model for financial text mining. Inf. Process. Manag. 60(2): 103194 (2023) - [j25]Rei Taguchi
, Hiroki Sakaji, Kiyoshi Izumi, Yuri Murayama:
Constructing Sentiment Signal-Based Asset Allocation Method with Causality Information. New Gener. Comput. 41(4): 777-794 (2023) - [j24]Hiroki Sakaji
, Kiyoshi Izumi:
Financial Causality Extraction Based on Universal Dependencies and Clue Expressions. New Gener. Comput. 41(4): 839-857 (2023) - [j23]Masanori Hirano
, Kiyoshi Izumi:
Neural-network-based parameter tuning for multi-agent simulation using deep reinforcement learning. World Wide Web (WWW) 26(5): 3535-3559 (2023) - [c94]Ryotaro Kobayashi, Yuri Murayama, Kiyoshi Izumi:
Impact Analysis of Social Events on Industries through Narrative Causal Search. IEEE Big Data 2023: 2845-2854 - [c93]Takehiro Takayanagi, Kiyoshi Izumi:
Harnessing Behavioral Traits to Enhance Financial Stock Recommender Systems: Tackling the User Cold Start Problem. IEEE Big Data 2023: 5694-5703 - [c92]Masanori Hirano
, Hiroki Sakaji, Kiyoshi Izumi:
Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets. IIAI-AAI 2023: 361-368 - [c91]Takanobu Mizuta, Kiyoshi Izumi:
Frequent Batch Auctions investigated by Agent-Based Model. IIAI-AAI 2023: 446-451 - [c90]Tsubasa Ueda, Takehide Hirose, Kiyoshi Izumi:
Export Nowcasting with AIS and Foot Traffic Data. IIAI-AAI 2023: 486-489 - [c89]Hiroki Sakaji, Ryotaro Kobayashi, Kiyoshi Izumi, Hiroyuki Mitsugi, Wataru Kuramoto:
Summarization of Investment Reports Using Pre-trained Model. IIAI-AAI 2023: 554-559 - [c88]Yoshiyuki Suimon, Hiroto Tanabe, Kiyoshi Izumi:
Using weather-based machine learning approach to estimate retail sales and interpret weather factors. IIAI-AAI 2023: 725-727 - [c87]Shingo Sashida, Kiyoshi Izumi, Hiroki Sakaji:
Extraction SDGs-related sentences from Sustainability Reports using BERT and ChatGPT. IIAI-AAI 2023: 742-745 - [c86]Takehiro Takayanagi
, Chung-Chi Chen
, Kiyoshi Izumi
:
Personalized Dynamic Recommender System for Investors. SIGIR 2023: 2246-2250 - [c85]Takehiro Takayanagi
, Kiyoshi Izumi
, Atsuo Kato
, Naoyuki Tsunedomi
, Yukina Abe
:
Personalized Stock Recommendation with Investors' Attention and Contextual Information. SIGIR 2023: 3339-3343 - [i3]Masanori Hirano, Ryosuke Takata, Kiyoshi Izumi:
PAMS: Platform for Artificial Market Simulations. CoRR abs/2309.10729 (2023) - 2022
- [j22]Rei Taguchi, Hikaru Watanabe, Hiroki Sakaji, Kiyoshi Izumi, Kenji Hiramatsu:
Constructing Equity Investment Strategies Using Analyst Reports and Regime Switching Models. Frontiers Artif. Intell. 5: 865950 (2022) - [j21]Masahiro Suzuki
, Hiroki Sakaji, Kiyoshi Izumi, Yasushi Ishikawa:
Forecasting Stock Price Trends by Analyzing Economic Reports With Analyst Profiles. Frontiers Artif. Intell. 5: 866723 (2022) - [j20]Masanori Hirano
, Kiyoshi Izumi
, Hiroki Sakaji:
STBM+: Advanced Stochastic Trading Behavior Model for Financial Markets using Residual Blocks or Transformers. New Gener. Comput. 40(1): 7-24 (2022) - [c84]Masanori Hirano, Kiyoshi Izumi, Hiroki Sakaji:
Implementation of Actual Data for Artificial Market Simulation. AAMAS 2022: 1624-1626 - [c83]Masanori Hirano
, Kiyoshi Izumi:
Parameter Tuning Method for Multi-agent Simulation using Reinforcement Learning. BESC 2022: 1-7 - [c82]Yoshito Noritake, Takanobu Mizuta
, Ryuta Hemmi, Shota Nagumo, Kiyoshi Izumi:
Investigation on effect of excess buy orders using agent-based model. BESC 2022: 1-5 - [c81]Yuya Takada
, Kiyoshi Izumi:
Implementation of Biased Big Data to the Japanese Official Labor Statistics Using Supervised Learning under Covariate Shift. IEEE Big Data 2022: 2062-2071 - [c80]Naoto Minakawa, Kiyoshi Izumi, Hiroki Sakaji:
Bilateral Trade Flow Prediction by Gravity-informed Graph Auto-encoder. IEEE Big Data 2022: 2327-2332 - [c79]Hiroki Sakaji, Masahiro Suzuki
, Kiyoshi Izumi, Hiroyuki Mitsugi:
Gradual Further Pre-training Architecture for Economics/Finance Domain Adaptation of Language Model. IEEE Big Data 2022: 2352-2355 - [c78]Yoshiyuki Suimon, Hiroto Tanabe, Kiyoshi Izumi:
The relationship between Twitter sentiment and mobility during the COVID-19 pandemic. IEEE Big Data 2022: 2370-2372 - [c77]Rei Taguchi, Hiroki Sakaji, Kiyoshi Izumi:
SSAAM: Sentiment Signal-based Asset Allocation Method with Causality Information. IEEE Big Data 2022: 2373-2376 - [c76]Takehiro Takayanagi, Hiroki Sakaji, Kiyoshi Izumi:
SETN: Stock Embedding Enhanced with Textual and Network Information. IEEE Big Data 2022: 2377-2382 - [c75]Masanori Hirano
, Hiroki Sakaji, Kiyoshi Izumi:
Concept and Practice of Artificial Market Data Mining Platform. CIFEr 2022: 1-10 - [c74]Masanori Hirano
, Kiyoshi Izumi:
Quantitative Tuning of Artificial Market Simulation using Generative Adversarial Network. ICA 2022: 12-17 - [c73]Masanori Hirano
, Kiyoshi Izumi:
Efficient Parameter Tuning for Multi-agent Simulation Using Deep Reinforcement Learning. IIAI-AAI-Winter 2022: 130-137 - [c72]Masanori Hirano
, Ryo Wakasugi, Kiyoshi Izumi:
Analysis of Demand Response Scenarios by Industrial Consumers Using Artificial Electric Power Market Simulations. IIAI-AAI 2022: 547-554 - [c71]Rei Taguchi, Hikaru Watanabe, Hiroki Sakaji, Kiyoshi Izumi, Kenji Hiramatsu:
Proposal for Turning Point Detection Method Using Financial Text and Transformer. JSAI-isAI Workshops 2022: 171-181 - [c70]Naoto Minakawa, Kiyoshi Izumi, Hiroki Sakaji, Hitomi Sano:
Transaction Prediction by Using Graph Neural Network and Textual Industry Information. JSAI-isAI Workshops 2022: 251-266 - [c69]Masanori Hirano
, Ryo Wakasugi, Kiyoshi Izumi
:
Analysis of Carbon Neutrality Scenarios of Industrial Consumers Using Electric Power Market Simulations. PRIMA 2022: 90-105 - [c68]Masanori Hirano
, Kiyoshi Izumi
:
Does Order Simultaneity Affect the Data Mining Task in Financial Markets? - Effect Analysis of Order Simultaneity Using Artificial Market. PRIMA 2022: 297-313 - [c67]Naoto Minakawa, Kiyoshi Izumi, Hiroki Sakaji, Hitomi Sano:
Graph Representation Learning of Banking Transaction Network with Edge Weight-Enhanced Attention and Textual Information. WWW (Companion Volume) 2022: 630-637 - [i2]Masanori Hirano
, Hiroki Sakaji, Kiyoshi Izumi:
Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets. CoRR abs/2204.13338 (2022) - 2021
- [c66]Hiroki Sakaji, Teruaki Hayashi, Yoshiaki Fukami, Takumi Shimizu, Hiroyasu Matsushima
, Kiyoshi Izumi
:
Retrieving of Data Similarity using Metadata on a Data Analysis Competition Platform. IEEE BigData 2021: 3480-3485 - [c65]Rei Taguchi, Hikaru Watanabe, Masanori Hirano
, Masahiro Suzuki
, Hiroki Sakaji, Kiyoshi Izumi
, Kenji Hiramatsu:
Market Trend Analysis Using Polarity Index Generated from Analyst Reports. IEEE BigData 2021: 3486-3494 - 2020
- [j19]Tomoki Ito
, Kota Tsubouchi
, Hiroki Sakaji, Tatsuo Yamashita, Kiyoshi Izumi
:
Contextual Sentiment Neural Network for Document Sentiment Analysis. Data Sci. Eng. 5(2): 180-192 (2020) - [j18]Tomoki Ito
, Hiroki Sakaji, Kiyoshi Izumi
, Kota Tsubouchi
, Tatsuo Yamashita:
GINN: gradient interpretable neural networks for visualizing financial texts. Int. J. Data Sci. Anal. 9(4): 431-445 (2020) - [j17]Masahiro Suzuki
, Hiroki Sakaji
, Kiyoshi Izumi
, Hiroyasu Matsushima
, Yasushi Ishikawa:
Forecasting Net Income Estimate and Stock Price Using Text Mining from Economic Reports. Inf. 11(6): 292 (2020) - [j16]Masanori Hirano
, Kiyoshi Izumi
, Hiroyasu Matsushima
, Hiroki Sakaji:
Comparing Actual and Simulated HFT Traders' Behavior for Agent Design. J. Artif. Soc. Soc. Simul. 23(3) (2020) - [c64]Tomoki Ito, Kota Tsubouchi, Hiroki Sakaji, Tatsuo Yamashita, Kiyoshi Izumi:
Word-Level Contextual Sentiment Analysis with Interpretability. AAAI 2020: 4231-4238 - [c63]Hiroki Sakaji, Teruaki Hayashi, Kiyoshi Izumi
, Yukio Ohsawa:
Verification of Data Similarity using Metadata on a Data Exchange Platform. IEEE BigData 2020: 4467-4474 - [c62]Yoshiyuki Suimon, Kiyoshi Izumi
, Hiroki Sakaji, Takashi Shimada, Hiroyasu Matsushima:
Estimating Manufacturing Activity via Machine Learning Analysis of High-frequency Electricity Demand Patterns. IIAI-AAI 2020: 562-565 - [c61]Masanori Hirano
, Hiroyasu Matsushima
, Kiyoshi Izumi, Hiroki Sakaji:
STBM: Stochastic Trading Behavior Model for Financial Markets. JSAI 2020: 157-165 - [c60]Yasutaka Nishimura, Taichi Shimura, Kiyoshi Izumi
, Kiyohito Yoshihara:
Design and Evaluations of Multi-agent Simulation Model for Electric Power Sharing Among Households. MABS 2020: 41-53 - [c59]Masanori Hirano
, Hiroyasu Matsushima
, Kiyoshi Izumi
, Hiroki Sakaji:
Implementation of Real Data for Financial Market Simulation Using Clustering, Deep Learning, and Artificial Financial Market. PRIMA 2020: 3-18 - [c58]Masanori Hirano
, Hiroyasu Matsushima
, Kiyoshi Izumi
, Taisei Mukai
:
Simulation of Unintentional Collusion Caused by Auto Pricing in Supply Chain Markets. PRIMA 2020: 352-359 - [c57]Tomoki Ito, Kota Tsubouchi
, Hiroki Sakaji, Tatsuo Yamashita, Kiyoshi Izumi
:
SSNN: Sentiment Shift Neural Network. SDM 2020: 262-270
2010 – 2019
- 2019
- [j15]Masanori Hirano
, Hiroki Sakaji, Shoko Kimura, Kiyoshi Izumi
, Hiroyasu Matsushima
, Shintaro Nagao, Atsuo Kato:
Related Stocks Selection with Data Collaboration Using Text Mining. Inf. 10(3): 102 (2019) - [j14]Ryo Hamawaki, Kiyoshi Izumi, Hiroki Sakaji, Takashi Shimada, Hiroyasu Matsushima
:
Chain bankruptcy size in inter-bank networks: the effects of asset price volatility and the network structure. J. Comput. Soc. Sci. 2(1): 53-66 (2019) - [c56]Hiroki Sakaji, Akio Kobayashi, Masaki Kohana, Yasunao Takano, Kiyoshi Izumi
:
Estimation of Tags Using Various Data for Online Videos. AINA 2019: 301-312 - [c55]Hirofumi Yamamoto, Hiroki Sakaji, Hiroyasu Matsushima
, Yuki Yamashita, Kyohei Osawa, Kiyoshi Izumi
, Takashi Shimada:
Forecasting Crypto-Asset Price Using Influencer Tweets. AINA 2019: 940-951 - [c54]Tomoki Ito, Kota Tsubouchi
, Hiroki Sakaji, Tatsuo Yamashita, Kiyoshi Izumi
:
Word-level Sentiment Visualizer for Financial Documents. CIFEr 2019: 1-7 - [c53]Atsuki Nakayama, Kiyoshi Izumi
, Hiroki Sakaji, Hiroyasu Matsushima
, Takashi Shimada, Kenta Yamada:
Short-term Stock Price Prediction by Analysis of Order Pattern Images. CIFEr 2019: 1-5 - [c52]Yoshiyuki Suimon, Hiroki Sakaji, Takashi Shimada, Kiyoshi Izumi
, Hiroyasu Matsushima
:
Japanese long-term interest rate forecast considering the connection between the Japanese and US yield curve. CIFEr 2019: 1-7 - [c51]Kyoto Yono, Kiyoshi Izumi
, Hiroki Sakaji, Hiroyasu Matsushima
, Takashi Shimada:
Extraction of Focused Topic and Sentiment of Financial Market by using Supervised Topic Model for Price Movement Prediction. CIFEr 2019: 1-7 - [c50]Yuta Niki, Hiroki Sakaji, Kiyoshi Izumi
, Hiroyasu Matsushima
:
Causality Existence Classification from Multilingual Texts Using End-to-End LSTM Models. ICDM Workshops 2019: 17-23 - [c49]Hiroki Sakaji, Yasutomo Kimura, Kiyoshi Izumi
, Hiroyasu Matsushima
:
Extraction of Volitional Utterances from Japanese Local Political Corpus. ICDM Workshops 2019: 24-29 - [c48]Masahiro Suzuki
, Toshiya Katagi, Hiroki Sakaji, Kiyoshi Izumi
, Yasushi Ishikawa:
Stock Price Analysis Using Combination of Analyst Reports and Several Documents. ICDM Workshops 2019: 30-36 - [c47]Tomoki Ito, Kota Tsubouchi
, Hiroki Sakaji, Kiyoshi Izumi
, Tatsuo Yamashita:
CSNN: Contextual Sentiment Neural Network. ICDM 2019: 1126-1131 - [c46]Yoshiyuki Suimon, Hiroki Sakaji, Takashi Shimada, Kiyoshi Izumi
, Hiroyasu Matsushima
:
Extraction of Relationship between Japanese and US Interest Rates using Machine Learning Methods. IIAI-AAI 2019: 649-654 - [c45]Kei Nakagawa
, Shingo Sashida, Hiroki Sakaji, Kiyoshi Izumi
:
Economic Causal Chain and Predictable Stock Returns. IIAI-AAI 2019: 655-660 - [c44]Kyoto Yono, Kiyoshi Izumi
, Hiroki Sakaji, Hiroyasu Matsushima
, Takashi Shimada:
Analysis of the Macroeconomic Uncertainty Based on the News-based Textual Data with Financial Market. IIAI-AAI 2019: 661-666 - [c43]Iwao Maeda, Hiroyasu Matsushima
, Hiroki Sakaji, Kiyoshi Izumi
, David deGraw, Atsuo Kato, Michiharu Kitano:
Effectiveness of Uncertainty Consideration in Neural-Network-Based Financial Forecasting. IIAI-AAI 2019: 673-678 - [c42]Yoshinori Tanaka, Syunya Kodera, Fumihito Sato, Hiroki Sakaji, Kiyoshi Izumi
:
The Extraction of the Future-Oriented Sentences from Annual Reports. IIAI-AAI 2019: 679-684 - [c41]Kiyoshi Izumi
, Hiroki Sakaji:
Economic Causal-Chain Search Using Text Mining Technology. IJCAI 2019: 23-35 - [c40]Tomoki Ito, Hiroki Sakaji, Kiyoshi Izumi
:
Segment Information Extraction from Financial Annual Reports Using Neural Network. JSAI 2019: 215-226 - [c39]Hiroki Sakaji, Akio Kobayashi, Masaki Kohana, Yasunao Takano, Kiyoshi Izumi
:
Card Price Prediction of Trading Cards Using Machine Learning Methods. NBiS 2019: 705-714 - [c38]Ryo Hamawaki, Jun'ichi Ozaki, Kiyoshi Izumi
, Takashi Shimada, Hiroki Sakaji, Hiroyasu Matsushima
:
Chain Bankruptcy Simulation Considering Investment from Banks to Companies. SMC 2019: 3784-3790 - [i1]Kei Nakagawa, Tomoki Ito, Masaya Abe, Kiyoshi Izumi:
Deep Recurrent Factor Model: Interpretable Non-Linear and Time-Varying Multi-Factor Model. CoRR abs/1901.11493 (2019) - 2018
- [j13]Itsuki Noda, Nobuyasu Ito, Kiyoshi Izumi, Hideki Mizuta, Tomio Kamada
, Hiromitsu Hattori:
Roadmap and research issues of multiagent social simulation using high-performance computing. J. Comput. Soc. Sci. 1(1): 155-166 (2018) - [c37]Masanori Hirano
, Hiroki Sakaji, Shoko Kimura, Kiyoshi Izumi
, Hiroyasu Matsushima
, Shintaro Nagao, Atsuo Kato:
Selection of Related Stocks using Financial Text Mining. ICDM Workshops 2018: 191-198 - [c36]Tomoki Ito, Hiroki Sakaji, Kota Tsubouchi
, Kiyoshi Izumi
, Tatsuo Yamashita:
Text-Visualizing Neural Network Model: Understanding Online Financial Textual Data. PAKDD (3) 2018: 247-259 - 2017
- [j12]Takuma Torii, Tomio Kamada
, Kiyoshi Izumi
, Kenta Yamada:
Platform design for large-scale artificial market simulation and preliminary evaluation on the K computer. Artif. Life Robotics 22(3): 301-307 (2017) - [c35]Tomoki Ito, Hiroki Sakaji, Kiyoshi Izumi
, Kota Tsubouchi
, Tatsuo Yamashita:
Development of an Interpretable Neural Network Model for Creation of Polarity Concept Dictionaries. ICDM Workshops 2017: 1122-1131 - [c34]Hiroki Sakaji, Atsuya Miyazaki, Hiroyuki Sakai, Kiyoshi Izumi
:
Extracting Laboratory Front Pages from University Websites. NBiS 2017: 1117-1125 - [c33]Tomoki Ito, Hiroki Sakaji, Kiyoshi Izumi
, Kota Tsubouchi
, Tatsuo Yamashita:
Development of sentiment indicators using both unlabeled and labeled posts. SSCI 2017: 1-8 - [c32]Hiroki Sakaji, Risa Murono, Hiroyuki Sakai, Jason Bennett, Kiyoshi Izumi
:
Discovery of rare causal knowledge from financial statement summaries. SSCI 2017: 1-7 - 2016
- [j11]Takanobu Mizuta
, Shintaro Kosugi, Takuya Kusumoto, Wataru Matsumoto, Kiyoshi Izumi
, Isao Yagi
, Shinobu Yoshimura:
Effects of Price Regulations and Dark Pools on Financial Market Stability: An Investigation by Multiagent Simulations. Intell. Syst. Account. Finance Manag. 23(1-2): 97-120 (2016) - [c31]Tomoki Ito, Kiyoshi Izumi
, Kota Tsubouchi
, Tatsuo Yamashita:
Polarity propagation of financial terms for market trend analyses using news articles. CEC 2016: 3477-3482 - [c30]Takanobu Mizuta
, Yoshito Noritake, Satoshi Hayakawa, Kiyoshi Izumi
:
Affecting market efficiency by increasing speed of order matching systems on financial exchanges - investigation using agent based model. SSCI 2016: 1-8 - 2015
- [c29]Itsuki Noda, Nobuyasu Ito, Kiyoshi Izumi
, Tomohisa Yamashita, Hideki Mizuta, Tomio Kamada
, Yohsuke Murase, Sachiko Yoshihama, Hiromitsu Hattori:
Roadmap for Multiagent Social Simulation on HPC. WI-IAT (3) 2015: 22-25 - 2014
- [j10]Saki Kawakubo, Kiyoshi Izumi, Shinobu Yoshimura:
Analysis of an Option Market Dynamics Based on a Heterogeneous Agent Model. Intell. Syst. Account. Finance Manag. 21(2): 105-128 (2014) - [j9]Bungo Miyazaki, Kiyoshi Izumi, Fujio Toriumi
, Ryo Takahashi:
Change Detection of Orders in Stock Markets using a Gaussian Mixture Model. Intell. Syst. Account. Finance Manag. 21(3): 169-191 (2014) - [j8]Saki Kawakubo, Kiyoshi Izumi
, Shinobu Yoshimura:
How Does High Frequency Risk Hedge Activity Have an Affect on Underlying Market?: Analysis by Artificial Market Model. J. Adv. Comput. Intell. Intell. Informatics 18(4): 558-566 (2014) - [c28]Takanobu Mizuta
, Wataru Matsumoto, Shintaro Kosugi, Kiyoshi Izumi
, Takuya Kusumoto, Shinobu Yoshimura:
Do dark pools stabilize markets and reduce market impacts? Investigations using multi-agent simulations. CIFEr 2014: 71-76 - [c27]Takanobu Mizuta
, Kiyoshi Izumi
, Isao Yagi
, Shinobu Yoshimura:
Regulations' effectiveness for market turbulence by large erroneous orders using multi agent simulation. CIFEr 2014: 138-143 - 2013
- [c26]Takanobu Mizuta
, Kiyoshi Izumi
, Shinobu Yoshimura:
Price variation limits and financial market bubbles: Artificial market simulations with agents' learning process. CIFEr 2013: 1-7 - 2012
- [c25]Isao Yagi
, Takanobu Mizuta
, Kiyoshi Izumi
:
A study on the reversal mechanism for large stock price declines using artificial markets. CIFEr 2012: 1-7 - 2011
- [j7]Kiyoshi Izumi
, Keiki Takadama, Hiromitsu Hattori, Nariaki Nishino
, Itsuki Noda:
Social and Group Simulation Based on Real Data Analysis. J. Adv. Comput. Intell. Intell. Informatics 15(2): 166-172 (2011) - [j6]Kiyoshi Izumi
, Yoshifumi Nishida, Yoichi Motomura:
Risk Evaluation by Human Trajectory Simulation Based on Real Data. J. Adv. Comput. Intell. Intell. Informatics 15(2): 220-225 (2011) - [c24]Tohgoroh Matsui
, Takashi Goto, Kiyoshi Izumi
, Yu Chen:
Compound Reinforcement Learning: Theory and an Application to Finance. EWRL 2011: 321-332 - 2010
- [c23]Isao Yagi
, Takanobu Mizuta
, Kiyoshi Izumi
:
A Study on the Effectiveness of Short-Selling Regulation in View of Regulation Period Using Artificial Markets. ACIS-ICIS 2010: 169-174 - [c22]Kiyoshi Izumi
, Takashi Goto, Tohgoroh Matsui
:
Trading Tests of Long-Term Market Forecast by Text Mining. ICDM Workshops 2010: 935-942 - [c21]Atsushi Nara
, Kiyoshi Izumi
, Hiroshi Iseki, Takashi Suzuki, Kyojiro Nambu, Yasuo Sakurai:
Surgical Workflow Monitoring Based on Trajectory Data Mining. JSAI-isAI Workshops 2010: 283-291
2000 – 2009
- 2009
- [j5]Kiyoshi Izumi
, Fujio Toriumi
, Hiroki Matsui:
Evaluation of automated-trading strategies using an artificial market. Neurocomputing 72(16-18): 3469-3476 (2009) - [j4]Tohgoroh Matsui, Takashi Goto, Kiyoshi Izumi:
Acquiring a Government Bond Trading Strategy Using Reinforcement Learning. J. Adv. Comput. Intell. Intell. Informatics 13(6): 691-696 (2009) - [c20]Fujio Toriumi
, Kiyoshi Izumi
, Hiroki Matsui:
Market Participant Estimation by Using Artificial Market. PRIMA Workshops 2009: 201-215 - [c19]Isao Yagi
, Takanobu Mizuta
, Kiyoshi Izumi
:
A Study on the Market Impact of Short-Selling Regulation Using Artificial Markets. PRIMA Workshops 2009: 217-231 - 2007
- [j3]Kiyoshi Izumi
, Hiroki Matsui, Yutaka Matsuo:
Integration of artificial market simulation and text mining for market analysis. Soft Comput. 11(12): 1199-1205 (2007) - [c18]Kiyoshi Izumi
, Hiroki Matsui, Yutaka Matsuo:
Socially embedded multi agent based simulation of financial market. AAMAS 2007: 175 - [c17]Kiyoshi Izumi
, Hiroki Matsui, Yutaka Matsuo:
A Self-Impact Analysis by Artificial Market Simulation. CIDM 2007: 726-733 - [c16]Yutaka Matsuo, Naoaki Okazaki, Kiyoshi Izumi, Yoshiyuki Nakamura, Takuichi Nishimura, Kôiti Hasida, Hideyuki Nakashima:
Inferring Long-term User Properties Based on Users' Location History. IJCAI 2007: 2159-2165 - 2006
- [c15]Kiyoshi Izumi
, Hiroki Matsui, Yutaka Matsuo:
Integration of Artificial Market Simulation and Text Mining for Market Analysis. ICHIT 2006: 404-413 - 2005
- [j2]Kiyoshi Izumi
, Shigeo Nakamura, Kazuhiro Ueda
:
Development of an artificial market model based on a field study. Inf. Sci. 170(1): 35-63 (2005) - [c14]Tomohisa Yamashita, Kiyoshi Izumi, Koichi Kurumatani, Hideyuki Nakashima:
Smooth traffic flow with a cooperative car navigation system. AAMAS 2005: 478-485 - [c13]Satoshi Kurihara, Kiyoshi Izumi
:
Agent Network Dynamics and Intelligence (ANDI 2005). JSAI Workshops 2005: 237-238 - [c12]Tomohisa Yamashita, Kiyoshi Izumi
, Koichi Kurumatani:
Information Sharing for Smooth Traffic in Road Networks. JSAI Workshops 2005: 330-339 - [p1]Tomohisa Yamashita, Kiyoshi Izumi, Koichi Kurumatani:
Analysis of the Effect of Route Information Sharing on Reduction of Traffic Congestion. Applications of Agent Technology in Traffic and Transportation 2005: 99-111 - 2004
- [c11]Kiyoshi Izumi, Tomohisa Yamashita, Koichi Kurumatani:
Analysis of Efficiency and Accuracy of Learning in Minoriy Games. AAMAS 2004: 1410-1411 - [c10]Tomohisa Yamashita, Kiyoshi Izumi, Koichi Kurumatani:
Investigation of Reduction of Traffic Congestion with Route Information Sharing. AAMAS 2004: 1446-1447 - [c9]Kiyoshi Izumi
:
Analysis of Efficiency and Accuracy of Learning in Minority Games. JSAI Workshops 2004: 103-113 - [c8]Kiyoshi Izumi
, Tomohisa Yamashita, Koichi Kurumatani:
Analysis of Learning Types in an Artificial Market. MABS 2004: 145-158 - [c7]Tomohisa Yamashita, Kiyoshi Izumi
, Koichi Kurumatani:
An Investigation into the Use of Group Dynamics for Solving Social Dilemmas. MABS 2004: 185-194 - 2003
- [c6]Tomohisa Yamashita, Kiyoshi Izumi
, Koichi Kurumatani:
Effect of Using Route Information Sharing to Reduce Traffic Congestion. MAMUS 2003: 86-104 - 2002
- [c5]Kiyoshi Izumi, Shigeo Nakamura, Kazuhiro Ueda:
Identification of Agents' Strategy Making Process by an Experimental Market. JCIS 2002: 1081-1084 - 2001
- [j1]Kiyoshi Izumi
, Kazuhiro Ueda
:
Phase transition in a foreign exchange market-analysis based on an artificial market approach. IEEE Trans. Evol. Comput. 5(5): 456-470 (2001) - [c4]Kiyoshi Izumi
:
Complexity of Agents and Complexity of Markets. JSAI Workshops 2001: 110-120 - 2000
- [c3]Kiyoshi Izumi
, Kazuhiro Ueda:
Learning of Virtual Dealers in an Artificial Market: Comparison with Interview Data. IDEAL 2000: 511-516
1990 – 1999
- 1999
- [c2]Kiyoshi Izumi, Kazuhiro Ueda:
Analysis of Exchange Rate Scenarios Using an Artificial Market Approach. IC-AI 1999: 360-366 - 1996
- [c1]Kiyoshi Izumi, Takashi Okatsu:
An Artificial Market Analysis of Exchange Rate Dynamics. Evolutionary Programming 1996: 27-36
Coauthor Index
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Unpaywalled article links
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Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-07-19 19:16 CEST by the dblp team
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