The series ‘‘Studies in Big Data’’ (SBD) publishes new developments andadvances in the various areas of Big Data- quickly and with a high quality. Theintent is to cover the theory, research, development, and applications of Big Data,as embedded in the fields of engineering, computer science, physics, economicsand life sciences. The books of the series refer to the analysis and understanding oflarge, complex, and/or distributed data sets generated from recent digital sourcescoming from sensors or other physical instruments as well as simulations, crowdsourcing, social networks or other internet transactions, such as emails or videoclick streams and other. The series contains monographs, lecture notes and editedvolumes in Big Data spanning the areas of computational intelligence incl. neuralnetworks, evolutionary computation, soft computing, fuzzy systems, as well asartificial intelligence, data mining, modern statistics and Operations research, aswell as self-organizing systems. Of particular value to both the contributors andthe readership are the short publication timeframe and the world-wide distribution,which enable both wide and rapid dissemination of research output.
In the globalized economy, the service sector is expanding rapidly and becomingmore and more important. Many researchers have conducted research on servicesfrom various points of view and offered insights to business owners. Recognized asone of the most important challenges in research on services among practitionersand researchers is how to improve service productivity and efficiently ensurecustomer satisfaction with limited natural and human resources. Due to theirnature, services used to be difficult to research using a scientific approach, but theinnovation of digital devices has led to the accumulation of a variety of data,which is gradually enabling researchers to analyze services scientifically.Data mining is one of the most important steps to scientific analysis of serviceprocesses. It is a series of processes which include collecting and accumulatingdata, modeling phenomena, and discovering new information. Numerous technicalpapers and studies on data mining have been published in computer science. Usingcalculation speed and prediction accuracy as the evaluation criteria, many of thesestudies have contributed to the efficient processing of a large amount of data.However, when it comes to applying data mining to analyzing services, calculationspeed and prediction accuracy do not suffice; instead, algorithms and techniquesthat are appropriate for a particular service must be adopted or developed.Therefore, expertise in the service domain is crucial in applying data mining inservices. This book reveals how data mining can be applied to the service sectorwithin a variety of service-related examples. Understanding the compatible relationbetween the expertise in services and data mining techniques will provideinsights on the extended use of data mining in other service domains.I would like to thank everyone who has supported me in the publishing of thisbook. I would like to address my special thanks to the authors of all the chapters,who offered new ideas and valuable perspectives; staff members at Springer fortheir continued guidance in the editing process, and the secretaries at KansaiUniversity Data Mining Laboratory. This work was supported by the program forthe Strategic Research Foundation at Private Universities from Ministry ofvEducation, Culture, Sports, Science and Technology (MEXT), 2009–2013. Finally,I hope this book will stimulate interest in the relation between data mining technologyand its application to other fields and provide important insights for manyresearchers and practitioners involved in the service sector.Osaka, October 2013 Katsutoshi Yada


  Editor: Katsutoshi Yada