IEEE International Workshop on Data Mining for Service (DMS2023) will be held in conjunction with
The 2023 IEEE International Conference on Data Mining (ICDM'2023)on December 1-4,
The confenrence/workshop venue will be presented in Shanghai, China.
DMS workshop will be held on December 1st.
25 papers were submitted and 7 papers were accepted by strict review.
Thank you for your contribution!!


In midst of service applications in engineering and the increasing importance of the service sector in the global economy, services are being scientifically and much attention is being focused on service science as a means to improve productivity and underlying business process. Since services are amorphous (they have no sharp) and have the special characteristic of simultaneously causing both production and consumption, it has been difficult to research services in a scientific way. However recently, due to the spread of the internet and technical innovations in the measurements, including sensor networks, huge amounts of data related to all kinds of service activities and processes are being collected, and a new frontier of service research is emerging as an important branch of data science. Given this background, data mining, which can uncover useful knowledge from such masses of data, is expected to take a crucial role in the development of service science and innovation of new services. The focus of this workshop is on empirical findings, methodological papers, and theoretical and conceptual insights related to data mining in the field of various service application areas.


The workshop is aimed at bringing together researchers from the areas of the service sector and data mining.
We expect to encourage an exchange of ideas and perceptions through the workshop, focused on service and data mining. Possible topics of interest include, but are not limited to:

* Information systems for service to understand consumer behavior
* Information systems to integrate various services
* New data mining applications and new insights for service science
* Data-oriented service innovation
* Case studies of data mining applications for service science

Especially, this year, we focus on the topics related to Big Data in the workshop.
This workshop will discuss specific uses of data mining techniques for Big Data to create new service.
Possible topics of interest include below:

* New service and Big Data
* Novel model and Big Data
* Any service application of data mining using Big Data

We are interested in the emergence of new business systems in the real business world, and encouraging new applications of data mining in service science. Therefore, submitted papers will be evaluated from the perspectives of traditional criteria such as technical originality and prediction accuracy, while also going beyond to consider creativity and applicability. Case studies that include successes and failures in service science are also welcome.

Data Mining

Areas of Interest

Examples in Marketing

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Paper submissions should be limited to a maximum of 8 pages, and follow the IEEE ICDM format. More detailed informations are available in the IEEE ICDM 2023 Submission Guidelines.

Please submit your manuscript through the DMS 2023 submission site (No.6).

All accepted papers will be included in the ICDM'23 Workshop Proceedings published by the IEEE Computer Society Press. Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals.

All accepted papers, including workshops, must have at least one “FULL” registration. A full registration is either a “member” or “non-member” registration. Student registrations are not considered full registrations. All authors are required to register by 15th October 2023.
Registration info.


Submissions due: September 3, 2023 September 15, 2023
Notifications of Acceptance: September 24, 2023
Camera-ready deadline and copyright forms: October 1, 2023
Early bird registration finishes: October 1, 2023, 2023
Workshop day: December 4December 1, 2023



Program Committee



Past Workshops


Katsutoshi Yada
Faculty of Business and Commerce, Kansai University, Japan

Shusaku Tsumoto
Department of Medical Informatics, Faculty of Medicine, Shimane University, Japan

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