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DTSTART;TZID=Israel:20211216T120000
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DESCRIPTION:https://en-engineering.tau.ac.il/Department-of-Industrial-Engin
 eering/event16-12-2021?gid=19\n\nMoran Sorka is an M.Sc student in the Dep
 artment of Industrial Engineering\n\nFor a long time now\, location data h
 as not been the sole preserve of navigation devices\, and nowadays such us
 er data is collected from almost all electronic devices. The wealth of dat
 a and the ever increasing ability of processing such vast quantities\, off
 ers unprecedented information to analyze human mobility\, cultivating an e
 xtensive variety of applications in location-based services such as intell
 igent transportation systems and smart cities. In recent years\, many stud
 ies have been conducted into predicting the next location the user is expe
 cted to reach\, based on a history of previous locations. Existing route-p
 rediction methods have difficulty coping with a large number of trips\, al
 l the more so if they are spread across a wide geographical area.\n\nRoom:
  206\, Bldg: Wolfson\, Tel-Aviv University\, Tel Aviv\, Tel Aviv District\
 , Israel\, Virtual: https://events.vtools.ieee.org/m/303454
LOCATION:Room: 206\, Bldg: Wolfson\, Tel-Aviv University\, Tel Aviv\, Tel A
 viv District\, Israel\, Virtual: https://events.vtools.ieee.org/m/303454
ORGANIZER:bengal@tauex.tau.ac.il
SEQUENCE:0
SUMMARY:Real-Time End-to-End Prediction of Driving Routes
URL;VALUE=URI:https://events.vtools.ieee.org/m/303454
X-ALT-DESC:Description: <br /><p><a href="https://en-engineering.tau.ac.il/
 Department-of-Industrial-Engineering/event16-12-2021?gid=19">https://en-en
 gineering.tau.ac.il/Department-of-Industrial-Engineering/event16-12-2021?g
 id=19</a></p>\n<p>Moran Sorka is an M.Sc student in the Department of Indu
 strial Engineering</p>\n<p>For a long time now\, location data has not bee
 n the sole preserve of navigation devices\, and nowadays such user data is
  collected from almost all electronic devices. The wealth of data and the 
 ever increasing ability of processing such vast quantities\, offers unprec
 edented information to analyze human mobility\, cultivating an extensive v
 ariety of applications in location-based services such as intelligent tran
 sportation systems and smart cities. In recent years\, many studies have b
 een conducted into predicting the next location the user is expected to re
 ach\, based on a history of previous locations. Existing route-prediction 
 methods have difficulty coping with a large number of trips\, all the more
  so if they are spread across a wide geographical area.</p>
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