Abstract
We aim to present an approach that can be used for the automated identification and extraction of the
business rules with the help of using semantic technology. In typical BRMS, keyword based search is used
to extract required business rules from rule base. However, we aim to incorporate semantic based search
for retrieving business rules according to the contextual meaning and identify context of search, location,
variation of words, and synonyms. In business rules, it is defined that the constraints and rules control the
behavior of the business for achieving the goal of any organization. One can apply business rules in the form
of constraints, definition and operations. All the strategies and directions tell the business rules that what
organization should do and how to focus on a particular business activity. In Business Management controlled
all the work like saving, defining, updating, retrieving, and deleting the rules. No support available still that
give us accuracy of matching of word, location, intent, variation of words, synonyms, concept matching to
provide relevant search result. Limitations of simple search have some issues when result is published after
a query. Most popular techniques are called stemming but it has some draw backs because it focuses on
the root word not the meaning. In semantic based search, a search is improved by improving accuracy by
searching according to the contextual meaning.
Muhammad Ifrahim Yasir, Taimoor Hassan, Imran Sarwar Bajwa. (2016) Automated Business Rules Harvesting using Semantic Technology, Journal of Applied and Emerging Sciences, Volume 6, Issue 1.
-
Views
1219 -
Downloads
90
Article Details
Volume
Issue
Type
Language
