Extraction of tourist destinations and comparative analysis of preferences between foreign tourists and domestic tourists on the basis of geotagged social media data TN Maeda, M Yoshida, F Toriumi, H Ohashi ISPRS International Journal of Geo-Information 7 (3), 99, 2018 | 47 | 2018 |
RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders TN Maeda, S Shimizu International Conference on Artificial Intelligence and Statistics, 735-745, 2020 | 30 | 2020 |
Decision tree analysis of tourists' preferences regarding tourist attractions using geotag data from social media TN Maeda, M Yoshida, F Toriumi, H Ohashi Proceedings of the Second International Conference on IoT in Urban Space, 61-64, 2016 | 21 | 2016 |
Detecting and understanding urban changes through decomposing the numbers of visitors¡¯ arrivals using human mobility data TN Maeda, N Shiode, C Zhong, J Mori, T Sakimoto Journal of Big Data 6, 1-25, 2019 | 19 | 2019 |
Comparative examination of network clustering methods for extracting community structures of a city from public transportation smart card data TN Maeda, J Mori, I Hayashi, T Sakimoto, I Sakata IEEE Access 7, 53377-53391, 2019 | 14 | 2019 |
Causal additive models with unobserved variables TN Maeda, S Shimizu Uncertainty in Artificial Intelligence, 97-106, 2021 | 13 | 2021 |
Python package for causal discovery based on LiNGAM T Ikeuchi, M Ide, Y Zeng, TN Maeda, S Shimizu Journal of Machine Learning Research 24 (14), 1-8, 2023 | 11 | 2023 |
Next place prediction in unfamiliar places considering contextual factors TN Maeda, K Tsubouch, F Toriumi The 25th ACM SIGSPATIAL International Conference on Advances in Geographic ¡, 2017 | 10 | 2017 |
Ç°Ìï¸ßÖ¾¥Ë¥³¥é¥¹, ÈýÄÚ顕義, ÇåË®²ýƽ, ÐÇÒ°ÀûÑå: EBPM ¤È統計µÄÒò¹û̽Ë÷¡¤ÊýÀí¥â¥Ç¥ë¤ÎÀû»îÓà ¸ßɽÕýÐУ¬ С²ñ Ñо¿¡¤¥¤¥Î¥Ùþí¥·¥ç¥óѧ»á µÚ 36 »ØÄê´Îѧ術´ó»á (Óè¸å¼¯)., ¹«ÑÝ·¬ºÅ 2G02, 2021 | 5 | 2021 |
The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images M Suzuki, J Mori, TN Maeda, J Ikeda Journal of Asian Architecture and Building Engineering 22 (3), 1110-1125, 2023 | 4 | 2023 |
Repetitive causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders TN Maeda, S Shimizu International Journal of Data Science and Analytics, 1-13, 2022 | 4 | 2022 |
Ç°Ìï¸ßÖ¾¥Ë¥³¥é¥¹, ÈýÄÚ顕義, ÇåË®²ýƽ, ÐÇÒ°ÀûÑå: ²©Ê¿課³Ì進ѧÂʤË関¤¹¤ëÒò¹û¥â¥Ç¥ë¤Î構築: 統計µÄÒò¹û̽Ë÷¥¢¥ë¥´¥ê¥º¥à ¡°LiNGAM¡± ¤Ë¤è¤ë試ÐеķÖÎö ¸ßɽÕýÐУ¬ С²ñ Jxiv preprint, 2022 | 3 | 2022 |
Causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders TN Maeda, S Shimizu arXiv preprint arXiv:2001.04197, 2020 | 3 | 2020 |
Measurement of Opportunity Cost of Travel Time for Predicting Future Residential Mobility Based on the Smart Card Data of Public Transportation TN Maeda, J Mori, M Ochi, T Sakimoto, I Sakata ISPRS international journal of geo-information 7 (11), 416, 2018 | 3 | 2018 |
Analysis of smart card data for understanding spatial changes in consumption-oriented human flows TN Maeda, J Mori, F Toriumi, H Ohashi Proceedings of the 2nd ACM SIGSPATIAL Workshop on Smart Cities and Urban ¡, 2016 | 3 | 2016 |
統計µÄÒò¹û̽Ë÷¥¢¥ë¥´¥ê¥º¥à ¡°LiNGAM¡± ¤òÓ䤤¿ÈôÊÖÑо¿ÕßÖ§Ô®Õþ²ß¤Ë関¤¹¤ëÑо¿ ¸ßɽÕýÐУ¬ С²ñ£¬ Ç°Ìï¸ßÖ¾£¬ ÈýÄÚ顕義£¬ ÇåË®²ýƽ£¬ ÐÇÒ°ÀûÑå Ñо¿¡¤¥¤¥Î¥Ùþí¥·¥ç¥óѧ»á, 2021 | 2 | 2021 |
Discovery of causal additive models in the presence of unobserved variables TN Maeda, S Shimizu arXiv preprint arXiv:2106.02234, 2021 | 2 | 2021 |
I-RCD: an improved algorithm of repetitive causal discovery from data with latent confounders TN Maeda Behaviormetrika 49 (2), 329-341, 2022 | 1 | 2022 |
EBPM ¤È統計µÄÒò¹û̽Ë÷¡¤ÊýÀí¥â¥Ç¥ë¤ÎÀû»îÓà ¸ßɽÕýÐУ¬ С²ñ£¬ Ç°Ìï¸ßÖ¾£¬ ÈýÄÚ顕義£¬ ÇåË®²ýƽ£¬ ÐÇÒ°ÀûÑå Ñо¿¡¤¥¤¥Î¥Ùþí¥·¥ç¥óѧ»á, 2021 | 1 | 2021 |
Use of Prior Knowledge to Discover Causal Additive Models with Unobserved Variables and its Application to Time Series Data TN Maeda, S Shohei arXiv preprint arXiv:2401.07231, 2024 | | 2024 |