# Behavioral technology modeling

## Technology

We view "behavior" as media that richly and frankly convey the inner world of humans. Recently, a new research field called "Behavioral Data Science" has attracted much attention. With the widespread use of various devices, human behavior has become digitalized. This research area analyzes human behavior through computational approaches such as machine learning, mathematical optimization, and probability theory.

The NTT Human Informatics Laboratories combine insights into the principles of human behavior in the social sciences and humanities with observable behavioral data to model human and group behaviors. We call this behavioral technology modeling.

We also aim for the "Well-Being of People and Society". By utilizing the behavioral technology modeling, we are also conducting research to transform human behavior in a more positive direction.

## Research

- Behavioral technology modeling and transform human behavior

## Related Technology

- Social group modeling technology

## Publications

### 2024

### Conference Papers

- Yasunori Akagi, Naoki Marumo, and Takeshi Kurashima, "Analytically Tractable Models for Decision Making under Present Bias", Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024), vol.38, no.9, pp.9441-9450, 2024. (oral presentation)
- Shoichiro Takeda, Yasunori Akagi, Naoki Marumo, and Kenta Niwa, "Optimal Transport with Cyclic Symmetry", Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024), vol.38, no.14, pp.15211-15221, 2024.

### 2023

### Journal Papers

- Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda, "MAP inference algorithms without approximation for collective graphical models on path graphs via discrete difference of convex algorithm", Machine Learning, vol.112, no.1, pp.99-129, 2023.
- Yuya Hikima, Yasunori Akagi, Masahiro Kohjima, Takeshi Kurashima, and Hiroyuki Toda, "Price and Time Proposal Optimization for Ride-Hailing Services Based on Individual Utilities", Transactions of the Japanese Society for Artificial Intelligence, vol.38, no.1, pp.CC-M13_1-12, 2023.

### Conference Papers

- Hideaki Kim, "Survival Permanental Processes for Survival Analysis with Time-Varying Covariates", Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 2023.
- Takeshi Kurashima, Tomoharu Iwata, Tomu Tominaga, Shuhei Yamamoto, Hiroyuki Toda, Kazuhisa Takemura, "Personal History Affects Reference Points: A Case Study of Codeforces", In Proceedings of the 17th International AAAI Conference on Web and Social Media (ICWSM 2023), pp.507-518, 2023.
- Yuya Hikima, Yasunori Akagi, Hideaki Kim, and Taichi Asami, "An Improved Approximation Algorithm for Wage Determination and Online Task Allocation in Crowd-sourcing", Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI 2023), vol.37, no.4, pp.3977-3986, 2023.

### Awards

- Outstanding User Modeling Paper Award: Takeshi Kurashima, Tomoharu Iwata, Tomu Tominaga, Shuhei Yamamoto, Hiroyuki Toda, Kazuhisa Takemura, "Personal History Affects Reference Points: A Case Study of Codeforces", In Proceedings of the 17th International AAAI Conference on Web and Social Media (ICWSM 2023), pp.507-518, 2023.

### 2022

### Journal Papers

- Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima, "Context-aware spatio-temporal event prediction via convolutional Hawkes processes", Machine Learning, vol.111, no.8, pp.2929-2950, 2022.

### Conference Papers

- Hideaki Kim, Taichi Asami, Hiroyuki Toda, "Fast Bayesian Estimation of Point Process Intensity as Function of Covariates", Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022.
- Maya Okawa, Tomoharu Iwata, "Predicting Opinion Dynamics via Sociologically-Informed Neural Networks", In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2022), pp.1306-1316, 2022.
- Yuya Hikima, Yasunori Akagi, Marumo Naoki, and Hideaki Kim, "Online Matching with Controllable Rewards and Arrival Probabilities", Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022), pp.1825-1833, 2022.

### 2021

### Journal Papers

- Yusuke Tanaka, Tomoharu Iwata, Takeshi Kurashima, Hiroyuki Toda, Naonori Ueda, Toshiyuki Tanaka, "Time-delayed collective flow diffusion models for inferring latent people flow from aggregated data at limited locations", Artificial Intelligence, vol.292, pp.103430, 2021.

### Conference Papers

- Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda, "Non-approximate inference for collective graphical models on path graphs via discrete difference of convex algorithm", Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 2021.
- Hideaki Kim, "Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation", Advances in Neural Information Processing Systems 34 (NeurIPS 2021), spotlight, 2021.
- Yuya Hikima, Masahiro Kohjima, Yasunori Akagi, Takeshi Kurashima, and Hiroyuki Toda, "Price and Time Optimization for Utility-Aware Taxi Dispatching", In Proceedings of the 18th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2021), pp.370-381, 2021.
- Tomu Tominaga, Shuhei Yamamoto, Takeshi Kurashima, Hiroyuki Toda, "Effects of personal characteristics on temporal response patterns in ecological momentary assessments", In Proceedings of the 18th IFIP TC 13 International Conference on Human-Computer Interaction (INTERACT 2021), pp.3-22, 2021.
- Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima, "Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes", In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2021), pp.1276-1286, 2021.
- Yuya Hikima, Yasunori Akagi, Hideaki Kim, Masahiro Kohjima, Takeshi Kurashima, and Hiroyuki Toda, "Integrated Optimization of Bipartite Matching and Its Stochastic Behavior: New Formulation and Approximation Algorithm via Min-cost Flow Optimization", In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), pp.3796-3805, 2021.

### 2020

### Conference Papers

- Masahiro Kohjima, Takeshi Kurashima, Hiroyuki Toda, "Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data", In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), pp.2412-2419, 2020.
- Shuhei Yamamoto, Takeshi Kurashima, and Hiroyuki Toda, "Identifying Near-Miss Traffic Incidents in Event Recorder Data", The 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020), pp.717-728, 2020.
- Yasunori Akagi, Takuya Nishimura, Yusuke Tanaka, Takeshi Kurashima, Hiroyuki Toda, "Exact and efficient inference for collective flow diffusion model via minimum convex cost flow algorithm", In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), pp.3163-3170, 2020.

### 2019

### Journal Papers

- Jun Suzuki, Yoshihiko Suhara, Hiroyuki Toda, Kyosuke Nishida, "Personalized visited-poi assignment to individual raw GPS trajectories", ACM Transactions on Spatial Algorithms and Systems, vol.5, no.3, pp.1-28, 2019.
- Maya Okawa, Yusuke Tanaka, Takeshi Kurashima, Hiroyuki Toda, Tomohiro Yamada, "Marked Temporal Point Processes for Trip Demand Prediction in Bike Sharing Systems", IEICE TRANSACTIONS on Information and Systems, vol.102, no.9, pp.1635-1643, 2019.

### Conference Papers

- Yusuke Tanaka, Toshiyuki Tanaka, Tomoharu Iwata, Takeshi Kurashima, Maya Okawa, Yasunori Akagi, Hiroyuki Toda, "Spatially aggregated Gaussian processes with multivariate areal outputs", Advances in Neural Information Processing Systems 32 (NeurIPS 2019), 2019.
- Hidetaka Ito, Kyota Tsutsumida, Tatsushi Matsubayashi, Takeshi Kurashima, Hiroyuki Toda, "Coordinated traffic signal control via bayesian optimization for hierarchical conditional spaces", 2019 Winter Simulation Conference (WSC 2019), pp.3645-3656, 2019.
- Masahiro Kohjima, Tatsushi Matsubayashi, Hiroyuki Toda, "Exemplar Based Mixture Models with Censored Data", In Proceedings of The Eleventh Asian Conference on Machine Learning (ACML 2019), pp.535-550, 2019.
- Yoshiaki Takimoto, Yusuke Tanaka, Takeshi Kurashima, Shuhei Yamamoto, Maya Okawa, Hiroyuki Toda, "Predicting traffic accidents with event recorder data", In Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility (PredictGIS 2019), pp.11-14, 2019.
- Masami Takahashi, Masahiro Kohjima, Takeshi Kurashima, Tatsushi Matsubayashi, Hiroyuki Toda, "Identifying self-changeable actions toward regulating rhythm of daily life", Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers (UbiComp/ISWC 2019), pp.218-221, 2019.
- Maya Okawa, Tomoharu Iwata, Takeshi Kurashima, Yusuke Tanaka, Hiroyuki Toda, Naonori Ueda, "Deep mixture point processes: Spatio-temporal event prediction with rich contextual information", In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2019), pp.373-383, 2019.
- Masahiro Kohjima, Tatsushi Matsubayashi, Hiroyuki Toda, "Generalized interval valued nonnegative matrix factorization", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2019), pp.3412-3416, 2019.
- Daisuke Sato, Tatsushi Matsubayashi, Shoichi Nagano, Hiroyuki Toda, "People flow prediction by multi-agent simulator", 2019 IEEE International Conference on Big Data and Smart Computing (BigComp 2019), pp.1-4, 2019.
- Yusuke Tanaka, Tomoharu Iwata, Toshiyuki Tanaka, Takeshi Kurashima, Maya Okawa, Hiroyuki Toda, "Refining coarse-grained spatial data using auxiliary spatial data sets with various granularities", In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2019), pp.5091-5099, 2019.