Mining Human Mobility in Location-Based Social Networks (Record no. 85994)

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fixed length control field 04257nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-3-031-01908-1
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730164926.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2015 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031019081
-- 978-3-031-01908-1
082 04 - CLASSIFICATION NUMBER
Call Number 006.312
100 1# - AUTHOR NAME
Author Gao, Huiji.
245 10 - TITLE STATEMENT
Title Mining Human Mobility in Location-Based Social Networks
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Edition statement 1st ed. 2015.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVI, 99 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Data Mining and Knowledge Discovery,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Acknowledgments -- Figure Credits -- Introduction -- Analyzing LBSN Data -- Returning to Visited Locations -- Finding New Locations to Visit -- Epilogue -- Bibliography -- Authors' Biographies .
520 ## - SUMMARY, ETC.
Summary, etc 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 traditional GPS data, location-based social networks data contains unique properties with abundant heterogeneous information to reveal human mobility, i.e., "when and where a user (who) has been to for what," corresponding to an unprecedented opportunity to better understand human mobility from spatial, temporal, social, and content aspects. The mining and understanding of human mobility can further lead to effective approaches to improve current location-based services from mobile marketing to recommender systems, providing users more convenient life experience than before. This book takes a data mining perspective to offer an overview of studying human mobility in location-based social networks and illuminate a wide range of related computational tasks. It introduces basic concepts, elaborates associated challenges, reviews state-of-the-art algorithms with illustrative examples and real-world LBSN datasets, and discusses effective evaluation methods in mining human mobility. In particular, we illustrate unique characteristics and research opportunities of LBSN data, present representative tasks of mining human mobility on location-based social networks, including capturing user mobility patterns to understand when and where a user commonly goes (location prediction), and exploiting user preferences and location profiles to investigate where and when a user wants to explore (location recommendation), along with studying a user's check-in activity in terms of why a user goes to a certain location.
700 1# - AUTHOR 2
Author 2 Liu, Huan.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-01908-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
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-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2015.
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-- computer
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-- rdamedia
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-- online resource
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-- text file
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data mining.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Statistics .
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Mining and Knowledge Discovery.
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-- Statistics.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2151-0075
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