Authors:
Robin G. Qiu
1
;
Helio Ha
1
;
Ramya Ravi
1
;
Lawrence Qiu
1
and
Youakim Badr
2
Affiliations:
1
Penn State University, United States
;
2
LIRIS-CNRS, France
Keyword(s):
Big Data, Smart Evaluation System, Higher Education Services, Rankings, Ranking System, Sentiment Analysis, Public Opinions.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Problem Solving
;
Software Engineering
;
Tools, Techniques and Methodologies for System Development
Abstract:
Assessing service quality proves very subjective, varying with objectives, methods, tools, and areas of assessment in the service sector. Customers’ perception of services usually plays an essential role in assessing the quality of services. Mining customers’ opinions in real time becomes a promising approach to the process of capturing and deciphering customers’ perception of their service experiences. Using the US higher education services as an example, this paper discusses a big data-mediated approach and system that facilitates capturing, understanding, and evaluation of their customers’ perception of provided services in real time. We review such a big data based framework (Qiu et al., 2015) in support of data retrieving, aggregations, transformations, and visualizations by focusing on public ratings and comments from different data sources. An implementation with smart evaluation services is mainly presented.