{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T02:09:26Z","timestamp":1767665366873},"reference-count":21,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2007,2,1]],"date-time":"2007-02-01T00:00:00Z","timestamp":1170288000000},"content-version":"vor","delay-in-days":62,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Annals of the New York Academy of Sciences"],"published-print":{"date-parts":[[2006,12]]},"abstract":"<jats:p><jats:bold><jats:sc>Abstract:\u2002<\/jats:sc><\/jats:bold>  <jats:bold>In this article we discuss an assisted cognition information technology system that can learn personal maps customized for each user and infer his daily activities and movements from raw GPS data<\/jats:bold>\n          <jats:bold>. The system uses discriminative and generative models for different parts of this task. A discriminative relational Markov network is used to extract significant places and label them; a generative dynamic Bayesian network is used to learn transportation routines, and infer goals and potential user errors at real time. We focus on the basic structures of the models and briefly discuss the inference and learning techniques. Experiments show that our system is able to accurately extract and label places, predict the goals of a person, and recognize situations in which the user makes mistakes, such as taking a wrong bus.<\/jats:bold> <\/jats:p>","DOI":"10.1196\/annals.1382.017","type":"journal-article","created":{"date-parts":[[2007,2,20]],"date-time":"2007-02-20T20:57:18Z","timestamp":1172005038000},"page":"249-265","source":"Crossref","is-referenced-by-count":57,"title":["Building Personal Maps from GPS Data"],"prefix":"10.1111","volume":"1093","author":[{"given":"LIN","family":"LIAO","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"DONALD J.","family":"PATTERSON","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"DIETER","family":"FOX","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"HENRY","family":"KAUTZ","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2007,2]]},"reference":[{"key":"e_1_2_8_2_1","unstructured":"Ashbrook D. andT.Starner.2003.Using GPS to learn significant locations and predict movement across multiple users. 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L.Liao K.Gajos M.Collier N.Livic K.Olson S.Wang D.Fox andH.Kautz.2004.Opportunity knocks: a system to provide cognitive assistance with transportation services. Pp.433\u2013350inI.Siio N.Davies andE.Mynatt(eds.) Proceedings of UBICOMP 2004: The Sixth International Conference on Ubiquitous Computing. Berlin :Springer. Available online athttp:\/\/www.cs.washington.edu\/homes\/kautz\/papers\/UBICOMP2004Patterson.pdf.","DOI":"10.1007\/978-3-540-30119-6_26"},{"key":"e_1_2_8_17_1","volume-title":"Converging Technologies for Improving Human Performance: Nanotechnology, Biotechnology, Information Technology and Cognitive Science","author":"Roco M.C.","year":"2002"},{"key":"e_1_2_8_18_1","doi-asserted-by":"crossref","unstructured":"Sha F. andF.Pereira.2003.Shallow parsing with conditional random fields. 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