Authors:
Ryosuke Saga
1
;
Naoaki Ohkusa
2
;
Takafumi Yamashita
3
and
Nahomi Maki
4
Affiliations:
1
Graduate School of Engineering, Osaka Prefecture University, College of Sustainable System Sciences and Osaka Prefecture University, Japan
;
2
College of Sustainable System Sciences and Osaka Prefecture University, Japan
;
3
Graduate School of Engineering and Osaka Prefecture University, Japan
;
4
Kanagawa Institute of Tehcnology, Japan
Keyword(s):
Information Visualization, Service Science, Customer Expectations, Co-occurrence Graph, Clustering, Auto-labeling.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
Data Management and Knowledge Representation
;
General Data Visualization
;
Graph Visualization
;
Information and Scientific Visualization
;
Visual Analytical Reasoning
;
Visual Representation and Interaction
Abstract:
This study describes the visualization of customer expectations using the service science domain. Customer expectations influence service quality and are considered important factors for user evaluation of services. Customer expectations are constructed from word of mouth, rumors, and user experience. Investigation using a questionnaire is useful in comprehending customer expectations, but this method is costly and time consuming. In this research, we extract customer expectations from Web text consisting of massive word-of-mouth data and visualize them using a co-occurrence graph. In addition, we apply clustering and auto-labeling methods to easily understand the results of the co-occurrence graph. In the case study of a coffee service, we are able extract topics related to customer expectations, but labeling methods are still subject to improvement.