Improving understandability of semantic search explanations Online publication date: Sat, 07-Mar-2015
by Thomas Roth-Berghofer, Bjorn Forcher
International Journal of Knowledge Engineering and Data Mining (IJKEDM), Vol. 1, No. 3, 2011
Abstract: Explanation-aware software design aims at making software systems smarter in interactions with their users. The long-term goal is to provide methods and tools for systematically engineering understandability into the respective (knowledge-based) software system. In this paper, we describe how we improved a semantic search engine, i.e., RadSem, regarding understandability. The research project MEDICO aims at developing an intelligent, robust and scalable semantic search engine for medical documents. RadSem is based on formal ontologies and designated for different kinds of users. Since semantic search results are often hard to understand, an explanation facility for justifying and exploring search results was integrated into RadSem employing the same ontologies used for searching also for explanation generation. We evaluated the understandability of selected concept labels in an experiment with different user groups using semantic networks as form of depicting explanations and using a class frequency approach for selecting appropriate labels.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Knowledge Engineering and Data Mining (IJKEDM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook