Paper Info
Title
Enhancing Usability Inspection Through Data-Mining Techniques: An Automated Approach For Detecting Usability Problem Patterns Of Academic Websites
Abstract
Usability is one of important attribute of software quality. It is associated with the "ease of use" of any system. Usability evaluation is becoming significant component of software development. Usability evaluation is performed through qualitative assessments. Qualitative assessments can be attained through Qualitative usability inspection (QUI). QUI methods emphasize on evaluating the interface of a specific system. These methods turn out to be complicated when huge number of systems related to similar context of use, are considered jointly to impart a general diagnosis. The principal cause for this is due to substantial quantity of information that should be conceptualized simultaneously. To handle substantial quantity of information, this paper proposes a novel approach that integrates QUI with automated woorank tool and data-mining techniques (association rules and decision tree). To validate this proposed approach, 50-academic websites are evaluated and usability problems patterns related to academic websites are identified by processing 2475 records.
Year
DOI
Venue
2016
10.1007/978-3-319-52503-7_19
INTELLIGENT HUMAN COMPUTER INTERACTION, IHCI 2016
Keywords
Field
DocType
Usability, Usability engineering, Qualitative usability inspection, Heuristic evaluation, Context of use, Usability problem patterns, Data-mining knowledge discovering in databases, Association rules, Decision trees
Data science,Pluralistic walkthrough,Web usability,Computer science,Usability engineering,Heuristic evaluation,Usability,Usability lab,Cognitive walkthrough,Artificial intelligence,Usability inspection,Machine learning
Conference
Volume
ISSN
Citations 
10127
0302-9743
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Kalpna Sagar121.04
Anju Saha2222.77