淡江大學機構典藏:Item 987654321/115099
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62805/95882 (66%)
Visitors : 3994935      Online Users : 527
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/115099


    Title: Social Network Based Big Data Analysis and Applications
    Authors: Mehmet Kaya, Jalal Kawash, Suheil Khoury, Min-Yuh Day
    Keywords: social network analysis and mining, influence analysis, pattern recognition, big data streams, community detection, sentiment analysis, recommendation and prediction, ASONAM proceedings
    Date: 2018-06-08
    Issue Date: 2018-10-04 12:12:06 (UTC+8)
    Publisher: Springer International Publishing
    Abstract: This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services.
    Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2016), which was held in August 2016.

    The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.
    Relation: Lecture Notes in Social Networks
    Appears in Collections:[Graduate Institute & Department of Information Management] Monograph

    Files in This Item:

    There are no files associated with this item.

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback