DocumentCode :
3401436
Title :
Automated analysis of logical connectives in business constraints
Author :
Akbar, Shazia ; Chaudhri, Ahsan Ali ; Bajwa, Imran Sarwar
Author_Institution :
Dept. of Comput. Sci. & IT, Islamia Univ., Bahawalpur, Pakistan
fYear :
2013
fDate :
11-12 Dec. 2013
Firstpage :
209
Lastpage :
213
Abstract :
Business constraints play a key role in business processes. Typically, the business rules are represented in a natural language such as English. Since, the natural languages are naturally ambiguous and one of the reasons of ambiguity is use of logical connectives that can make the NL sentences more ambiguous. Use of logical connectives result in multiple senses of a business rule specifically the XOR role of OR connective makes the things more difficult. To model the Business process specifications and business rules, one need to analyse NL based business rules manually or automatically. During analysis of NL business rules, one had to deal with various occurrences of logical connectives. In this paper, we present a novel approach to identify the type and scope of a logical connective in a target business rule. The presented approach incorporates the Markov Logic approach to handle ambiguity in logical connectives. Initial results of the experiments are also discussed at the end of the paper.
Keywords :
Markov processes; business data processing; Markov logic approach; NL based business rules; NL sentences; XOR role; automated analysis; business constraints; logical connectives; natural language; Analytical models; Artificial neural networks; Business; Computational modeling; Markov processes; Semantics; Business Rules; Logical Connectives; Markov Logic; NL Ambiguity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Current Trends in Information Technology (CTIT), 2013 International Conference on
Conference_Location :
Dubai
Type :
conf
DOI :
10.1109/CTIT.2013.6749505
Filename :
6749505
Link To Document :
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