International Workshop: AI-Biz2021
November 15, 2021:Online (because of COVID-19 pandemic):
Aims and Scope
The objective of this workshop is to foster the concepts and techniques of“Business Intelligence (BI).” in Artificial Intelligence. BI should include such cutting-edge techniques as data science, agent-based modelling, complex adaptive systems, and IoT. The application areas include but not limited to business management, finance engineering, service sciences, manufacturing engineering, and so on.The basic idea of BI would enhance the capabilities of conventional techniques in business domain, however, so far, we have not discussed BI concepts deeply in artificial intelligence literature. We would like to focus on BI topics to the issues of firms and organizations for getting more benefits on interactions with human- and computer- mixed systems.
The main purpose of this workshop is to provide a forum to discuss important research questions and practical challenges in Business Intelligence, Business Informatics, Data Analysis and Agent-based Modelling to exchange latest results, to join efforts in solving the common challenges. It is also to establish an effective communication between researchers and developers involved in the both areas. The workshop will provide opportunities for the participants to exchange new ideas and experiences to establish research or business network and to find global partners for future collaboration.
Program
November 15, 20219:00 - 9:10
Opening session
Prof. Takao Terano
9:10 - 10:10
1st Session: Chair Hiroaki Jotaki
What is the investment strategy to overcome the severe business environment? :Perspectives on decision makers' competencies and institutional designs
Kazuya Morimatsu and Hiroshi Takahashi
A Study of News and Stock Markets Using FinBERT Models: Evidence from Japan and Korea
Sungjae Yoon and Hiroshi Takahashi
Classifying Mergers and Acquisitions Through Clustering Method with Innovation Output
Nozomi Tamagawa and Hiroshi Takahashi
10:20 - 11:20
2nd Session: Chair Setsuya Kurahashi
Identifying Legality of Japanese Online Advertisements using Complex-valued Support Vector Machine with DFT-based Document Features
Satoshi Kawamoto, Toshio Akimitsu and Kikuo Asai
A Knowledge Extraction from Gaming Logs
Akinobu Sakata, Takamasa Kikuchi, Ryuichi Okumura, Masaaki Kunigami, Atsushi Yoshikawa, Masayuki Yamamura and Takao Terano
Estimation of Imbalance Price Considering Power Generation Utility’s Thermal Power Generation Output Control and Structural Change
Hiroo Horii, Takahiro Obata, Junsuke Senoguchi and Setsuya Kurahashi
11:40 - 12:30
Invited Talk 1
Building an Agent-based Network Model for Simulating Epidemic Outbreaks and Epidemic-induced Medical Demand
Prof. Tzai-Hung Wen
13:30 - 14:30
3rd Session: Chair Eiji Murakami
Modeling of Bicycle Sharing Operating System with Collaborative Multi-agent by Deep Reinforcement Learning
Kohei Yashima and Setsuya Kurahashi
Visualization of discussion process with convergence and divergence by applying the faultline perspective
Fumiko Kumada and Setsuya Kurahashi
Assessment of the Impact of COVID-19 Infections Considering Risk of Infected People Inflow to the Region
Setsuya Kurahashi
14:40 - 15:40
4th Session: Chair Junsuke Senoguchi
Analysis of helpfulness of online hotel reviews: classification based approach
Sakun Rathnayaka and Shantha Jayalal
A hybrid feature-based approach for classification of Fake News in Sinhala on social media
Suranga Wijayarathna and Shantha Jayalal
Wide and Deep Learning for Enhancing Context-Aware Recommender Systems in the Telecommunication Industry
H.W.C. Madhushanka, Chathura Rajapakse and P.P.G.D. Asanka
16:00 - 16:50
Invited talk 2
Empirical inference for agent-based models, where are we going next?
Dr. Ernesto Carrella
17:00 - 17:10
Closing session
Prof. Takao Terano
AI-Biz2021 Invited Talk
Prof. Tzai-Hung Wen
Building an Agent-based Network Model for Simulating Epidemic Outbreaks and Epidemic-induced Medical Demand
Due to the complex interactions between human behaviors and the environment, it is essential to quantify the association between epidemic progression and human spatial behaviors. We proposed a methodological framework for generating geospatial agent-based networks and established a spatially explicit model for simulating epidemic outbreaks and epidemic-induced medical demand. The model combined dynamic epidemic process and resource accessibility to assess the availability of medical resources. We used the model to characterize the spatiotemporally dynamic patterns of the COVID-19 transmission under different ration levels of medical resources. It demonstrates that the medical resource demand and ration level in each area varies over space and time. The methodological framework captures the spatial-temporal dynamics of epidemic-induced demand and establishes the integrated accessibility modeling to deal with time-varying demand. It clarifies the effects of medical resource accessibility on disease transmission dynamics.
Prof. Tzai-Hung Wen
Professor
Department of Geography
National Taiwan University
Dr. Ernesto Carrella
Empirical inference for agent-based models, where are we going next?
We want our agent-based models to answer empirical questions and provide actionable insights. This can only be done if our agent-based models can be informed by the large amount of data the world collects. Because of their nature, it has often been difficult to "fit" agent-based models and their parameters to data. Fortunately, in the past ten years a large number of methods and techniques have been developed to parameterise simulation models; these have often proved successful but their limitations have also become apparent. In this talk, we will review recent developments, test their limits in agent-based models and look at possible future avenues for research.
Dr. Ernesto Carrella
Oxford University Centre for the Environment
Important Dates
Submission Deadline: September 16, 2021 (extended!)Notification: September, 2021
Camera-ready due: October, 2021
Deadline for Early registration : October, 2021
Workshop: One day in November 13-15, 2021
Submissions
Papers must be prepared according to the Springer LNCS/LNAI format. The page limit is 14 pages, including figures and bibliography. This conference uses a double-blind review.Selected papers will be published as post-proceedings via Springer Verlag LNAI after the second round of a double-blind review after the workshop.
Please ensure that your paper fully complies with the LNAI format.
Guidelines for the LNAI format
http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0
LNCS/LNAI style files
ftp://ftp.springer.de/pub/tex/latex/llncs/latex2e/llncs2e.zip
Submission and review of papers for AI-Biz2021 is managed via EasyChair:
www.easychair.org/conferences/?conf=aibiz2021
Registration
Please register the workshop at registration page of JSAI International Symposia on AI 2021.https://www.ai-gakkai.or.jp/isai/registration-2021