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Santi Phithakkitnukoon
Santi Phithakkitnukoon
Professor of Data Engineering, Chiang Mai University
Bestätigte E-Mail-Adresse bei eng.cmu.ac.th - Startseite
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Zitiert von
Zitiert von
Jahr
Activity-aware map: Identifying human daily activity pattern using mobile phone data
S Phithakkitnukoon, T Horanont, G Di Lorenzo, R Shibasaki, C Ratti
Human Behavior Understanding: First International Workshop, HBU 2010 …, 2010
4162010
Socio-geography of human mobility: A study using longitudinal mobile phone data
S Phithakkitnukoon, Z Smoreda, P Olivier
PLoS ONE, 2011
2812011
Taxi-aware map: Identifying and predicting vacant taxis in the city
S Phithakkitnukoon, M Veloso, C Bento, A Biderman, C Ratti
Ambient Intelligence: First International Joint Conference, AmI 2010, Malaga …, 2010
2142010
Urban mobility study using taxi traces
M Veloso, S Phithakkitnukoon, C Bento
Proceedings of the 2011 international workshop on Trajectory data mining and …, 2011
1562011
Group recommendation system for facebook
EA Baatarjav, S Phithakkitnukoon, R Dantu
On the Move to Meaningful Internet Systems: OTM 2008 Workshops: OTM …, 2008
1302008
Weather effects on the patterns of people's everyday activities: a study using GPS traces of mobile phone users
T Horanont, S Phithakkitnukoon, TW Leong, Y Sekimoto, R Shibasaki
PloS one 8 (12), e81153, 2013
1272013
Inferring passenger travel demand to improve urban mobility in developing countries using cell phone data: a case study of Senegal
MG Demissie, S Phithakkitnukoon, T Sukhvibul, F Antunes, R Gomes, ...
IEEE Transactions on intelligent transportation systems 17 (9), 2466-2478, 2016
1042016
Understanding tourist behavior using large-scale mobile sensing approach: A case study of mobile phone users in Japan
S Phithakkitnukoon, T Horanont, A Witayangkurn, R Siri, Y Sekimoto, ...
Pervasive and Mobile Computing 18, 18-39, 2015
962015
Sensing urban mobility with taxi flow
M Veloso, S Phithakkitnukoon, C Bento
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location …, 2011
642011
Inferring social influence in transport mode choice using mobile phone data
S Phithakkitnukoon, T Sukhvibul, M Demissie, Z Smoreda, J Natwichai, ...
EPJ Data Science 6, 1-29, 2017
612017
Behavior-based adaptive call predictor
S Phithakkitnukoon, R Dantu, R Claxton, N Eagle
ACM Transactions on Autonomous and Adaptive Systems (TAAS) 6 (3), 1-28, 2011
592011
Exploratory study of urban flow using taxi traces
M Veloso, S Phithakkitnukoon, C Bento, N Fonseca, P Olivier
First Workshop on Pervasive Urban Applications (PURBA) in conjunction with …, 2011
562011
Behavior analysis of spam botnets
H Husna, S Phithakkitnukoon, S Palla, R Dantu
2008 3rd International Conference on Communication Systems Software and …, 2008
562008
Visualizing public transit system operation with GTFS data: A case study of Calgary, Canada
P Prommaharaj, S Phithakkitnukoon, MG Demissie, L Kattan, C Ratti
Heliyon 6 (4), 2020
492020
Interpretable machine-learning model with a collaborative game approach to predict yields and higher heating value of torrefied biomass
T Onsree, N Tippayawong, S Phithakkitnukoon, J Lauterbach
Energy 249, 123676, 2022
462022
Trip distribution modeling using mobile phone data: emphasis on intra-zonal trips
MG Demissie, S Phithakkitnukoon, L Kattan
IEEE Transactions on Intelligent Transportation Systems 20 (7), 2605-2617, 2018
452018
Mining temporal patterns of transport behaviour for predicting future transport usage
S Foell, G Kortuem, R Rawassizadeh, S Phithakkitnukoon, M Veloso, ...
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing …, 2013
442013
Weather Effects on Mobile Social Interactions: A Case Study of Mobile Phone Users in Lisbon, Portugal
S Phithakkitnukoon, TW Leong, Z Smoreda, P Olivier
PLoS ONE 7 (10), e45745, 2012
432012
Out of sight out of mind--How our mobile social network changes during migration
S Phithakkitnukoon, F Calabrese, Z Smoreda, C Ratti
2011 IEEE third international conference on privacy, security, risk and …, 2011
432011
Analysis of demand–supply gaps in public transit systems based on census and GTFS data: a case study of Calgary, Canada
K Kaeoruean, S Phithakkitnukoon, MG Demissie, L Kattan, C Ratti
Public Transport 12, 483-516, 2020
382020
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