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Data mining for service
Yada K., Springer Publishing Company, Incorporated, Berlin, Germany, 2014. 250 pp. Type: Book (978-3-642452-51-2)
Date Reviewed: Jun 10 2014

The increase in consumerism across the globe has led to the exponential growth of the service sector. The service sector is characterized by the intangibility of inputs and results. The chief factor that separates the winners from the losers in the service sector is the ability to add value to the services while improving quality, productivity, efficiency, and customer satisfaction. The intangible nature of this sector makes the collection of data for data mining extremely difficult.

Service science is a productivity improving approach for the service sector. It works by defining processes that create new services or add value to existing ones. Data mining is an integral part of service science as it generates and accumulates data and transforms it into knowledge that can be used for improving the efficiency and productivity of the services.

Two developments have helped in improving service science, namely innovations in data collection and storage and developments in computer science (CS). The innovations in the field of data collection and storage, like new information collection devices (Internet clickstreams, video monitoring, text analysis, sensor technologies, and so on), make it easy to electronically record the service process events that were difficult to record previously. These new devices help in the collection and accumulation of large volumes of service data. The development of various new technologies for analyzing large-scale diverse data in the field of CS is another factor. These innovations have changed the field of data mining by improving the generation and accumulation of data, the discovery of new knowledge, and gaining an in-depth understanding of the various phenomena in the service sector.

With the information accumulation and analysis of data from the service sector made easier, data mining for service emerged as an important field of research. But data mining of the service sector has many challenges. To overcome these challenges and use data mining efficiently, knowledge of both the service field and applied technologies is a must. The existing algorithms have to be improved and new technologies have to be developed to suit the characteristics of each service. This has to be done by people who have extensive domain knowledge and a deep understanding of the unique problems of each field.

This book contains 14 chapters, each written by leading data mining experts in the service sector. The chapters are divided into four parts. Each chapter deals with a fundamental data mining technology and explains how data mining can be successfully applied to different service fields.

The introduction of technology and algorithms used, and examples from diverse fields in the service sector, will help readers acquire an excellent understanding of the unique nature of data mining. The importance of combining domain knowledge with the data mining technology is also illustrated.

The latest research on data mining algorithms and techniques that support mining in the service sector are explored in Part 1. The various fundamental technologies that are specific to the services, such as clustering, feature selection, and dimensionality reduction, are covered comprehensively. Part 2 deals with the research on knowledge discovery from huge text data like Internet comments, call center conversation logs, academic and research databases, and so on. The challenges of text mining and the new technologies used to make text mining effective and efficient are explained in detail.

Part 3 examines the mining of data collected by social networking services on the Internet, such as Twitter, YouTube, and BlogSpot, and how to discover new knowledge that will enable a better user experience of those services. Part 4 describes where data mining is applied to diverse data collection using new information devices in the various service fields. This part also deals with the problems and challenges in dealing with real-time data collected using these devices and strategies.

This book is a must-read for data mining practitioners in the service sector, as it gives state-of-the-art information about new technologies, strategies, and devices that will help improve the efficiency and usefulness of data mining in this field. It will also be of interest to researchers, as data mining in the service sector is realizing its full potential and is an interesting field to be in since many cutting-edge technologies are at play here.

Reviewer:  Alexis Leon Review #: CR142381 (1409-0726)
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