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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Chapleau, R., Gaudette, P., & Spurr, T. (2019). Application of Machine Learning to Two Large-Sample Household Travel Surveys: A Characterization of Travel Modes. Transportation Research Record, 2673(4), 173-183. External link
Spurr, T., Leroux, A., & Chapleau, R. (2018). Comparative Structural Evaluation of Transit Travel Demand using Travel Survey and Smart Card Data for Metropolitan Transit Financing. Transportation Research Record, 2672(8), 807-816. External link
Chapleau, R., Gaudette, P., & Spurr, T. (2018). Strict and deep comparison of revealed transit trip structure between computer-assisted telephone interview household travel survey and smart cards. Transportation Research Record, 2672(42), 13-22. External link
Gaudette, P., Chapleau, R., & Spurr, T. (2016). Bus network microsimulation with general transit feed specification and tap-in-only smart card data. Transportation Research Record, 2544(1), 71-80. External link
Spurr, T., Chu, A., Chapleau, R., & Piché, D. (2014, November). A smart card transaction "travel diary" to assess the accuracy of the Montréal household travel survey [Paper]. 10th International Conference on Transport Survey Methods, Leura, Australia. Published in Transportation Research Procedia, 11. External link
Spurr, T., Chapleau, R., & Piché, D. (2014). Use of subway smart card transactions for the discovery and partial correction of travel survey bias. Transportation Research Record, 2405(1), 57-67. External link
Spurr, T., Chapleau, R., & Piché, D. (2013, July). Animation tools for the microsimulation of a public transport network [Paper]. World Conference on Transport Research, Rio de Janeiro, Brésil. Unavailable
Spurr, T., & Chapleau, R. (2013, July). Direct schedule-based assignment of smart-card trips to a GTFS transit network [Paper]. World Conference on Transport Research, Rio de Janeiro, Brésil. Unavailable
Chapleau, R., & Spurr, T. (2013, July). Microscopie d'un métro : micro-simulation en totalement désagrégé dérivée des transactions de cartes à puces [Paper]. 12ème Séminaire francophone est-ouest de socio-économie des transports, Rio de Janeiro, Brésil. Unavailable
Spurr, T., & Chapleau, R. (2007, January). The contribution of the confusion matrix to the analysis of mode choice in Montréal [Paper]. 86th Annual Meeting of the Transportation Research Board, Washington, D.C.. External link
Spurr, T., & Chapleau, R. (2007, April). L'utilité de la confusion pour mieux prévoir l'usage des modes [Paper]. 42e congrès de l'Association québécoise du transport et des routes, Montréal, Québec. Unavailable
