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The Annotation of Global Positioning System (GPS) Data with Activity Purposes Using Multiple Machine Learning Algorithms
16 references·0 citing·35 second hop
The Annotation of Global Positioning System (GPS) Data with Activity Purposes Using Multiple Machine Learning Algorithms (2014)The Annotation of Global Positioning Syst…Daily activity pattern recognition by using support vector machines with multiple classes (2013)Daily activity pattern recogn…Annotating mobile phone location data with activity purposes using machine learning algorithms (2013)Annotating mobile phone locat…Understanding transportation modes based on GPS data for web applications (2010)Understanding transportation …Semiautomatic Imputation of Activity Travel Diaries (2010)Semiautomatic Imputation of A…Deriving Rules for Trip Purpose Identification from GPS Travel Survey Data and Land Use Data: A Machine Learning Approach (2010)Deriving Rules for Trip Purpo…Eigenbehaviors: identifying structure in routine (2009)Eigenbehaviors: identifying s…Eigenbehaviors: identifying structure in routine (2009)Eigenbehaviors: identifying s…Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands (2009)Deriving and validating trip …An automated GPS-based prompted recall survey with learning algorithms (2009)An automated GPS-based prompt…Travel Mode Choice Modeling with Support Vector Machines (2008)Travel Mode Choice Modeling w…Deducing mode and purpose from GPS data (2008)Deducing mode and purpose fro…Learning and inferring transportation routines (2007)Learning and inferring transp…Eighty Weeks of Global Positioning System Traces: Approaches to Enriching Trip Information (2004)Eighty Weeks of Global Positi…A learning-based transportation oriented simulation system (2003)A learning-based transportati…Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data (2001)Elimination of the Travel Dia…Using GPS data loggers to replace travel diaries in the collection of travel data (2000)Using GPS data loggers to rep…Can Land-use Policy Really Affect Travel Behaviour? A Study of the Link between Non-work Travel and Land-use Characteristics (1998)GPS tracking in neighborhood and health studies: A step forward for environmental exposure assessment, a step backward for causal inference? (2013)Review of GPS Travel Survey and GPS Data-Processing Methods (2014)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Using GPS to learn significant locations and predict movement across multiple users (2003)Understanding mobility based on GPS data (2008)Transportation mode inference from anonymized and aggregated mobile phone call detail records (2010)What We Know and Don't Know about Online Word-of-Mouth: A Review and Synthesis of the Literature (2014)Analysis of human mobility patterns from GPS trajectories and contextual information (2015)Discrete choice analysis: Theory and application to travel demand (1988)Work Travel Mode Choice Modeling with Data Mining: Decision Trees and Neural Networks (2003)A Self Instructing Course in Mode Choice Modeling: Multinomial and Nested Logit Models (2006)Choice modelling in the age of machine learning - Discussion paper (2021)Exploring interactive and nonlinear effects of key factors on intercity travel mode choice using XGBoost (2024)Architecture of Cognition (1983)A multiple discrete–continuous extreme value model: formulation and application to discretionary time-use decisions (2004)How fixed is fixed? Gendered rigidity of space–time constraints and geographies of everyday activities (2008)Activity-based models of travel demand: promises, progress and prospects (2013)Reality mining: sensing complex social systems (2005)Bridging the gap between physical location and online social networks (2010)Predictability of population displacement after the 2010 Haiti earthquake (2012)A survey of results on mobile phone datasets analysis (2015)The Massachusetts Institute of Technology (1999)Mining large-scale smartphone data for personality studies (2011)Measuring Large-Scale Social Networks with High Resolution (2014)Tracking tourists in the digital age (2007)Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones (2010)Applying mobile phone data to travel behaviour research: A literature review (2017)PEIR, the personal environmental impact report, as a platform for participatory sensing systems research (2009)Route choice modeling with network-free data (2007)The Minimum Circuity Frontier and the Journey to Work (2009)Latent variables and route choice behavior (2011)Applications of New Technologies in Travel Surveys (2006)Trip purpose inference using automated fare collection data (2013)The Netherlands Mobility Panel: An Innovative Design Approach for Web-based Longitudinal Travel Data Collection (2015)
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References

  • 2007Learning and inferring transportation routines798 cited
  • 2003A learning-based transportation oriented simulation system583 cited
  • 2009Eigenbehaviors: identifying structure in routine504 cited
  • 2009Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands501 cited
  • 2010Understanding transportation modes based on GPS data for web applications485 cited
  • 2009Eigenbehaviors: identifying structure in routine439 cited
  • 2001Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data394 cited
  • 2004Eighty Weeks of Global Positioning System Traces: Approaches to Enriching Trip Information141 cited
  • 2000Using GPS data loggers to replace travel diaries in the collection of travel data131 cited
  • 2008Travel Mode Choice Modeling with Support Vector Machines127 cited
  • 2009An automated GPS-based prompted recall survey with learning algorithms119 cited
  • 2013Daily activity pattern recognition by using support vector machines with multiple classes95 cited
  • 2013Annotating mobile phone location data with activity purposes using machine learning algorithms85 cited
  • 2008Deducing mode and purpose from GPS data75 cited

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  • 2010Semiautomatic Imputation of Activity Travel Diaries57 cited
  • 2010Deriving Rules for Trip Purpose Identification from GPS Travel Survey Data and Land Use Data: A Machine Learning Approach57 cited
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