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Huan Liu

Mining Human Mobility in Location-Based Social Networks

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In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook Places, which have attracted an increasing number of users and greatly enriched their urban experience. Typical location-based social networking sites allow a user to check in at a real-world POI (point of interest, e.g., a hotel, restaurant, theater, etc.), leave tips toward the POI, and share the check-in with their online friends. The check-in action bridges the gap between real world and online social networks, resulting in a new type of social networks, namely location-based social networks (LBSNs). Compared to tra… Mehr

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Produktdetails


Weitere Autoren: Gao, Huiji
  • ISBN: 978-3-031-00780-4
  • EAN: 9783031007804
  • Produktnummer: 39048718
  • Verlag: Springer International Publishing
  • Sprache: Englisch
  • Erscheinungsjahr: 2015
  • Seitenangabe: 116 S.
  • Masse: H23.5 cm x B19.1 cm x D0.6 cm 233 g
  • Abbildungen: Paperback
  • Gewicht: 233

Über den Autor


Huiji Gao is an applied researcher at LinkedIn. He received his Ph.D. of Computer Science and Engineering at Arizona State University in 2014, and B.S./M.S. from Beijing University of Posts and Telecommunications in 2007 and 2010, respectively. His research interests include social computing, crowdsourcing for disaster management system, recommender systems, and mobile data mining on location-based social networks. He was awarded the 2014 ASU Graduate Education Dissertation Fellowship, the 2014 ASU President's Award for Innovation, the 3rd Place Dedicated Task 2 Next Location Prediction of Nokia Mobile Data Challenge 2012, and Student Travel Awards and Scholarships in various conferences.Huan Liu is a professor of Computer Science and Engineering at Arizona State University. He obtained his Ph.D. in Computer Science at University of Southern California and B.Eng. in Computer Science and Electrical Engineering at Shanghai JiaoTong University. Before he joined ASU, he worked at Telecom Australia Research Labs and was on the faculty at National University of Singapore. He was recognized for excellence in teaching and research in Computer Science and Engineering at Arizona State University. His research interests are in data mining, machine learning, social computing, feature selection, and artificial intelligence, investigating problems that arise in many real-world, data-intensive applications with high-dimensional data of disparate forms such as social media. His well-cited publications include books, book chapters, encyclopedia entries as well as conference and journal papers. He is Editor in Chief of ACM Transaction on Intelligent Systems and Technology (TIST), serves on journal editorial boards and numerous conference program committees, and is a founding organizer of the International Conference Series on Social Computing, Behavioral-Cultural Modeling, and Prediction. He is an IEEE Fellow.

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