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When and Where: Predicting Human Movements Based on Social Spatial-Temporal Events [article]

Ning Yang, Xiangnan Kong, Fengjiao Wang, Philip S. Yu
2014 arXiv   pre-print
We first define a new concept, Social Spatial-Temporal Event (SSTE), to represent social interactions among people.  ...  For the location prediction, we propose a ranking model where the periodicity and the sociality of human movements are simultaneously taken into consideration for improving the prediction accuracy.  ...  [13] propose a spatial-temporal event model to discover social associations among individuals based on spatial-temporal co-occurrences.  ... 
arXiv:1407.1450v1 fatcat:ms7eblstmvcjfmltaqurxrd3mu

When and Where: Predicting Human Movements Based on Social Spatial-Temporal Events [chapter]

Ning Yang, Xiangnan Kong, Fengjiao Wang, Philip S. Yu
2014 Proceedings of the 2014 SIAM International Conference on Data Mining  
We first define a new concept, Social Spatial-Temporal Event (SSTE), to represent social interactions among people.  ...  For the location prediction, we propose a ranking model where the periodicity and the sociality of human movements are simultaneously taken into consideration for improving the prediction accuracy.  ...  [13] propose a spatial-temporal event model to discover social associations among individuals based on spatial-temporal co-occurrences.  ... 
doi:10.1137/1.9781611973440.59 dblp:conf/sdm/YangKWY14 fatcat:rt434hcfrzawljjjrai7pfygii

When and where next

Győző Gidófalvi, Fang Dong
2012 Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems - MobiGIS '12  
terms of temporal and spatial prediction accuracy.  ...  The ability to predict when an individual mobile user will leave his current location and where we will move next enables a myriad of qualitatively different Location-Based Services (LBSes) and applications  ...  regularities in movements of an object to predict when and where the object will move next.  ... 
doi:10.1145/2442810.2442821 dblp:conf/gis/GidofalviD12 fatcat:rulkqz7d2rdtzdhrqhsx3yneme

Prediction in Joint Action: What, When, and Where

Natalie Sebanz, Guenther Knoblich
2009 Topics in Cognitive Science  
We explore how a common coding of perceived and performed actions may allow actors to predict the what, when, and where of others' actions.  ...  The "when" aspect is critical for all joint actions requiring close temporal coordination.  ...  However, it may also be possible that movement trajectories can be directly predicted based on simulating observed actions, rather than coming just as a by-product.  ... 
doi:10.1111/j.1756-8765.2009.01024.x pmid:25164938 fatcat:ux63ksftynfs7bjk5vd27dwqim

When and where do infants follow gaze?

Gedeon O. Deak
2015 2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)  
Those results are consistent with models in which incremental learning processes gradually learn to predict interesting events in allocentric space, and spatial attention networks learn to integrate predictive  ...  Infants' processing of adult social cues develops late in the first year. Sensitivity before 6 months is limited to nonspecific motion-cuing by lateral eye movements.  ...  Deák and J. Triesch (HSD SES-0527756), and to the Temporal Dynamics of Learning Center (SBE-0542013). Thanks to J. Triesch, H. Jasso, and M.  ... 
doi:10.1109/devlrn.2015.7346138 dblp:conf/icdl-epirob/Deak15 fatcat:gmuula2dqjexjm4gwcl3f56ecy

Time Perception Machine: Temporal Point Processes for the When, Where and What of Activity Prediction [article]

Yatao Zhong, Bicheng Xu, Guang-Tong Zhou, Luke Bornn, Greg Mori
2018 arXiv   pre-print
Furthermore, we also extend our model to a joint estimation framework for predicting the timing, spatial location, and category of the activity simultaneously, to answer the when, where, and what of activity  ...  We propose an integrated framework of neural networks and temporal point processes for predicting when the next activity will happen.  ...  Our goal is to predict the timing, spatial location, and category of the next activity given past information. We aim to answer the when, where, and what questions of activity prediction.  ... 
arXiv:1808.04063v2 fatcat:dfq5q36dfzf2rdkwgpvo7ojcfq

'Where are we when we think?' Space, time and emancipatory education in galleries

Janna Graham
2018 International Journal of Lifelong Education  
dislocated set of events on trendy and consumable political themes, and a site for 'allyship' and other kinds of radical and socially transformative work.  ...  Resurrecting Hannah Arendt's question,'where are we when we think?'  ...  Notes on contributor Janna Graham is an organiser, artist and curator who works at the intersection of critical peda-gogy, curation and gallery education.  ... 
doi:10.1080/02601370.2017.1406548 fatcat:cvokcpctdzgnrawlbcmoi3ugza

The where, what and when of gaze allocation in the lab and the natural environment

Tom Foulsham, Esther Walker, Alan Kingstone
2011 Vision Research  
Our results focused on where people directed their eyes and their head, what objects were gazed at and when attention-grabbing items were selected.  ...  For example, pedestrians close to the walker were fixated more often when viewed on video than in the real world.  ...  human tendency for social attention (Emery, 2000; Kingstone, 2009) .  ... 
doi:10.1016/j.visres.2011.07.002 pmid:21784095 fatcat:heib7xq55vhvrmbahr5i35bxxu

Capuchins, space, time and memory: an experimental test of what-where-when memory in wild monkeys

Charles H. Janson
2016 Proceedings of the Royal Society of London. Biological Sciences  
, Julia Monk and Flor Espinosa.  ...  I am grateful to the ongoing support and permission to conduct studies at the field site from the Argentine Administració n de Parques Nacionales and their Delegació n Técnica Regional Noreste.  ...  Introduction A critical underpinning of human intelligence is the ability to recall specific events in the past with a wealth of context-specific details (what happened, when it happened, where it happened  ... 
doi:10.1098/rspb.2016.1432 pmid:27708145 pmcid:PMC5069509 fatcat:5ipnbxwdmvhwzlcaqvskk64mk4

The who, where, what, how and when of market entry

Gideon D. Markman, Peter Gianiodis, G. Tyge Payne, Christopher Tucci, Igor Filatotchev, Reddi Kotha, Eric Gedajlovic
2019 Journal of Management Studies  
as incumbents, entrants, suppliers, etc.), when (the timing and sequence of entry), how (the strategy, resources, capabilities, etc.), where (the space of entry) and what (product, service, business model  ...  , etc.)to include two additional categories: complements (networks, platforms, ecosystems) and non-market elements (government, political, social and cultural arrangements).  ...  Human capital and social capital increase with TMTs' accumulated prior experience in a product market and should bolster the effectiveness of entry.  ... 
doi:10.1111/joms.12448 fatcat:7tatpnq2prhjhjin232ttgnlpm

MS-LaTTE: A Dataset of Where and When To-do Tasks are Completed [article]

Sujay Kumar Jauhar, Nirupama Chandrasekaran, Michael Gamon, Ryen W. White
2021 arXiv   pre-print
Finally, we test the dataset on the two problems of predicting spatial and temporal task co-occurrence, concluding that predictors for co-location and co-time are both learnable, with a BERT fine-tuned  ...  By logging signals such as text, timestamp information, and social connectivity graphs, an increasingly rich and detailed picture of how tasks are created and organized, what makes them important, and  ...  Other applications include generating online recommendations for advertising and news, based on temporal patterns (Zeng et al., 2016) , and recommending entities based on historic user behavior and spatio-temporal  ... 
arXiv:2111.06902v1 fatcat:cnpqsuq4sfbc7bun4fv37flav4

Who, Where, Why and When? Using Smart Card and Social Media Data to Understand Urban Mobility

Yuanxuan Yang, Alison Heppenstall, Andy Turner, Alexis Comber
2019 ISPRS International Journal of Geo-Information  
In so doing, they support a more nuanced and detailed view of who, where, when and why people use city spaces.  ...  Different groups were identified based on their travel times and trip costs.  ...  card dataset and community boundary data.  ... 
doi:10.3390/ijgi8060271 fatcat:d56akoqzrvgszc4xufepv7l5fy

Where are the passengers?

Meng-Fen Chiang, Tuan-Anh Hoang, Ee-Peng Lim
2015 Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS '15  
These include the prediction of number of bookings at certain location and time of the day, and the detection of anomalous booking events.  ...  Taxi demand modeling, spatial-temporal dynamics, unified grid-based Gaussian mixure model 1 We cannot provide precise statistics and app name in order to comply with the non-disclosure agreement.  ...  Acknowledgment This research is supported by the Singapore National Research Foundation under its International Research Centre @ Singapore Funding Initiative and administered by the IDM Programme O ce  ... 
doi:10.1145/2820783.2820807 dblp:conf/gis/ChiangHL15 fatcat:5t5ayojy7jdfnjytahr2t6m7jq

From where do tweets originate?

Qunying Huang, Guofeng Cao, Caixia Wang
2014 Proceedings of the 7th ACM SIGSPATIAL International Workshop on Location-Based Social Networks - LBSN '14  
(timestamps when a message was posted) information recorded on user digital footprints.  ...  on the number of digit footprints collected for social media users.  ...  Examples include disease outbreak detection [1] , emergency management and relief [2] [3] , analysis and mapping of people's opinions or sentiments towards to political and social events [4] , and human  ... 
doi:10.1145/2755492.2755494 dblp:conf/gis/HuangCW14 fatcat:psu4nnwu4vehha5hzt66vpy2wm

Where and Why Users "Check In"

Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan
2014 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
The emergence of location based social network (LBSN) services makes it possible to study individuals' mobility patterns at a fine-grained level and to see how they are impacted by social factors.  ...  In this study we analyze the check-in patterns in LBSN and observe significant temporal clustering of check-in activities.  ...  While most prior work has focused on user-based modeling of spatial-temporal LBSN data (Cho, Myers, and Leskovec 2011; Gao, Tang, and Liu 2012a) , here we argue that a venue-centric approach is sometimes  ... 
doi:10.1609/aaai.v28i1.8746 fatcat:lxfztcgonbcpjpppurrhzho45y
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