A. Bhattacharyya, Pavan Kumar Chittimalli, Ravindra Naik
{"title":"Relation Identification in Business Rules for Domain-specific Documents","authors":"A. Bhattacharyya, Pavan Kumar Chittimalli, Ravindra Naik","doi":"10.1145/3172871.3172884","DOIUrl":null,"url":null,"abstract":"This paper focuses on an approach to mine business rules from documents and facilitates a methodology to represent them in a formal notation. Businesses are operated abiding by some rules and complying with respect to regulation and guidelines. The business rules are often written using English in operating procedures, terms and conditions, and various other supporting documents. The manual analysis of these rules for activities like impact analysis, maintenance, business transformation leads to potential discrepancies, ambiguities, and quality issues. In this paper, we discuss our approach of mining relations among the rule intents (atomic facts) defined for business rules. We also present our preliminary studies on a couple of openly available documents.","PeriodicalId":199550,"journal":{"name":"Proceedings of the 11th Innovations in Software Engineering Conference","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 11th Innovations in Software Engineering Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3172871.3172884","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper focuses on an approach to mine business rules from documents and facilitates a methodology to represent them in a formal notation. Businesses are operated abiding by some rules and complying with respect to regulation and guidelines. The business rules are often written using English in operating procedures, terms and conditions, and various other supporting documents. The manual analysis of these rules for activities like impact analysis, maintenance, business transformation leads to potential discrepancies, ambiguities, and quality issues. In this paper, we discuss our approach of mining relations among the rule intents (atomic facts) defined for business rules. We also present our preliminary studies on a couple of openly available documents.