https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=R._et_al_2020aR. et al 2020a - Revision history2026-04-11T07:20:46ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=R._et_al_2020a&diff=197103&oldid=prevScipediacontent: Scipediacontent moved page Draft Content 791851420 to R. et al 2020a2021-02-01T19:20:31Z<p>Scipediacontent moved page <a href="/public/Draft_Content_791851420" class="mw-redirect" title="Draft Content 791851420">Draft Content 791851420</a> to <a href="/public/R._et_al_2020a" title="R. et al 2020a">R. et al 2020a</a></p>
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</td></tr></table>Scipediacontenthttps://www.scipedia.com/wd/index.php?title=R._et_al_2020a&diff=197102&oldid=prevScipediacontent: Created page with " == Abstract == The large availability of mobility data allows studying human behavior and human activities. However, this massive and raw amount of data generally lacks any..."2021-02-01T19:20:27Z<p>Created page with " == Abstract == The large availability of mobility data allows studying human behavior and human activities. However, this massive and raw amount of data generally lacks any..."</p>
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== Abstract ==<br />
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The large availability of mobility data allows studying human behavior and human activities. However, this massive and raw amount of data generally lacks any detailed semantics or useful categorization. Annotations of the locations where the users stop may be helpful in a number of contexts, including user modeling and profiling, urban planning, activity recommendations, and can even lead to a deeper understanding of the mobility evolution of an urban area. In this paper, we foster the expressive power of individual mobility networks, a data model describing users' behavior, by defining a data-driven procedure for locations annotation. The procedure considers individual, collective, and contextual features for turning locations into annotated ones. The annotated locations own a high expressiveness that allows generalizing individual mobility networks, and that makes them comparable across different users. The results of our study on a dataset of trucks moving in Greece show that the annotated individual mobility networks can enable detailed analysis of urban areas and the planning of advanced mobility applications.<br />
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== Original document ==<br />
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The different versions of the original document can be found in:<br />
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* [https://publications.cnr.it/doc/424846 https://publications.cnr.it/doc/424846]</div>Scipediacontent