22 April 2015

Call for papers: "Data Mining and Service Science for Innovation"

For a special issue of the International Journal of Knowledge Engineering and Soft Data Paradigms.

Recently, in developing countries as well as developed countries, the percentage of service industries accounting for industrial structure has increased rapidly. In business, for example, management, marketing, engineering and other services are important factors for inter-company competition, and service productivity is expected to increase through scientific observation and deeper understanding of the services. Improving existing services or establishing new ones based on knowledge gained from data is particularly a source of important innovation and feedback is being gathered from many researchers or and practitioners.
This special issue aims to investigate how data analysis techniques such as data mining aid in reforming existing services or in forming new ones. The issue aims to propose future directions through the awareness of the research gap in data analysis techniques and service sciences, and to gather further research into service science based on a wide range of data. The issue will provide a communication platform to aid the exchange of new ideas between people involved in service management and data scientists. Furthermore, we hope to propose new topics, models, analysis methods and theories relating to service science, based on the issue’s data.
Suitable topics include, but are not limited to, the following:
  • Techniques
    • Data mining
    • Machine learning
    • Text and semi-structured data mining
    • Pattern recognition
    • Knowledge representation
    • Statistics and probability
    • Service ontologies and modelling
  • Service applications
    • Engineering
    • Management
    • Marketing
    • Operation processes
    • Medical treatment
    • Public administration
Important Dates
Submission of manuscripts: 20 July, 2015
Notification to authors: 21 September, 2015
Final versions due: 20 November, 2015

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