Volume 9 Number 6 (Jun. 2014)
Home > Archive > 2014 > Volume 9 Number 6 (Jun. 2014) >

Guest Editorial: Special Issue on Online Social Network Data Processing

Guest Editors: Hao Lan Zhang, Chaoyi Pang, Ramamohanarao Kotagiri
  Web-based social networks have been growing extremely fast in recent years. It has become one of the most important issues of web-based technologies. Meanwhile, data mining and processing techniques have been applied extensively to various research domains including web technology and social networks.
  Intelligent Data Processing has attracted much attention from various research communities. Researchers in related fields are facing the challenges of data explosion, which demands enormous manpower for data processing. Artificial intelligence and intelligent systems offer efficient mechanisms that can significantly reduce the costs of processing large volume data and improve data processing quality. Practical applications have been developed in different areas including health informatics, financial data analysis, geographic systems, automated manufacturing processes, etc.
  This special issue aims to gather experts and scholars from related fields to present and share their recent research on social networks, data processing and the integration of these two areas. This special issue contains extended versions of the accepted papers from the 14th International Symposium on Knowledge and Systems Sciences, hosted by NIT, Zhejiang University. 10 papers have been invited to the special issue selected from over 44 conference submissions. 4 papers have been accepted after two rounds of review. We are pleased to serve as guest editors for this special issue to bring together researchers, practitioners and users interested in the full spectrum of online social network data processing. This issue reflects the breadth of enterprise services computing topics. There are four papers, each of which is concerned with a specific aspect of the topic and summarised as follows.
  Referring to the first paper “A Novel Approach for Customer Segmentation Based on Bi-clustering”, Hu et al present a novel approach to classify customers for an effective Customer Relationship Management. This approach uses the chisquare statistical analysis to select the set of attributes and uses K-means algorithm to quantize the value of each selected attribute. It then classifies the customers into three groups by using DBSCAN algorithm. The efficiency of this approach has been demonstrated on the real data set from an airline company.


General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
  • Apr 26, 2021 News!

    Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec)     [Click]

  • Jun 22, 2020 News!

    Papers published in JSW Vol 14, No 1- Vol 15 No 4 have been indexed by DBLP     [Click]

  • Sep 13, 2021 News!

    The papers published in Vol 16, No 6 have all received dois from Crossref    [Click]

  • Jan 28, 2021 News!

    [CFP] 2021 the annual meeting of JSW Editorial Board, ICCSM 2021, will be held in Rome, Italy, July 21-23, 2021   [Click]

  • Sep 13, 2021 News!

    Vol 16, No 6 has been published with online version     [Click]