Paper Info
Title
Ontology Based Data Access Methods to Teach Students to Transform Traditional Information Systems and Simplify Decision Making Process.
Abstract
We describe a service-based approach that provides a natural language interface to legacy information systems, built on top of relational database management systems. The long term goal is to make data management and analysis accessible to a wider range of users for a diverse range of purposes and to simplify the decision making process. We present an ontology-driven web-service, named Reply, that transforms traditional information systems into intelligent systems, endowed with a natural language interface, so that they can be queried by any novice user much like modern day search engines. The principal mechanism of our approach is turning a natural language query into a SQL-query for structured data sources by using Ontology-Based Data Access methods. We also outline how the proposed approach allows semantic searching of large structured, unstructured, or semi-structured data within the database or outside sources, thus helping bridge the talent gap in the case of Big Data Analytics used by researchers and postgraduate students.
Year
DOI
Venue
2016
10.1016/j.procs.2016.05.458
ICCS
Keywords
Field
DocType
Bridging the Talent Gap in Data Analytics, Legacy Information System, Intelligent Information System, Natural Language Interface, Ontology-Driven System, Ontology-Based Data Access, Semantic Web, Open Data
Information system,Data modeling,Data mining,Intelligent decision support system,Computer science,Natural language user interface,Artificial intelligence,World Wide Web,Data model,Data management,Big data,Data access,Machine learning
Conference
Volume
Issue
ISSN
80
C
1877-0509
Citations 
PageRank 
References 
3
0.41
5
Authors
3
Name
Order
Citations
PageRank
Svetlana Chuprina1274.75
Igor Postanogov231.09
Olfa Nasraoui31515164.53