Relation Identification in Business Rules for Domain-specific Documents

被引:2
|
作者
Bhattacharyya, Abhidip [1 ]
Chittimalli, Pavan Kumar [2 ]
Naik, Ravindra [2 ]
机构
[1] Univ Colorado, Boulder, CO 80309 USA
[2] TRDDC, TCS Innovat Labs, Pune, Maharashtra, India
关键词
Business Rule Extraction; Document Mining; Natural Language Processing; Maximum Entropy; EXTRACTION;
D O I
10.1145/3172871.3172884
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页数:5
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