Automated identification of business rules in requirements documents

Business Rules (BR) are usually written by different stakeholders, which makes them vulnerable to contain different designations for a same concept. Such problem can be the source of a not well orchestrated behaviors. Whereas identification of synonyms is manual or totally neglected in most approaches dealing with natural language Business Rules. In this paper, we present an automated approach to identify semantic similarity between terms in textual BR using Natural Language Processing and knowledge-based algorithm refined using heuristics. Our method is unique in that it also identifies abbreviations/expansions (as a special case of synonym) which is not possible using a dictionary. Then, results are saved in a standard format (SBVR) for reusability purposes. Our approach was applied on more than 160 BR statements divided on three cases with an accuracy between 69% and 87% which suggests it to be an indispensable enhancement for other methods dealing with textual BR.

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Analyzing Language in Suicide Notes and Legacy Tokens

Crisis ◽

10.1027/0227-5910/a000363 ◽

2016 ◽

Vol 37 (2) ◽

pp. 140-147 ◽

Cited By ~ 6

Author(s):

Michael J. Egnoto ◽

Darrin J. Griffin

Keyword(s):

Text Analysis ◽

Low Cost ◽

Computer Software ◽

Student Writing ◽

Computer Assisted ◽

Automated Identification ◽

Completed Suicide ◽

Suicide Notes ◽

Self Harm ◽

Harm To Others

Abstract. Background: Identifying precursors that will aid in the discovery of individuals who may harm themselves or others has long been a focus of scholarly research. Aim: This work set out to determine if it is possible to use the legacy tokens of active shooters and notes left from individuals who completed suicide to uncover signals that foreshadow their behavior. Method: A total of 25 suicide notes and 21 legacy tokens were compared with a sample of over 20,000 student writings for a preliminary computer-assisted text analysis to determine what differences can be coded with existing computer software to better identify students who may commit self-harm or harm to others. Results: The results support that text analysis techniques with the Linguistic Inquiry and Word Count (LIWC) tool are effective for identifying suicidal or homicidal writings as distinct from each other and from a variety of student writings in an automated fashion. Conclusion: Findings indicate support for automated identification of writings that were associated with harm to self, harm to others, and various other student writing products. This work begins to uncover the viability or larger scale, low cost methods of automatic detection for individuals suffering from harmful ideation.

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Towards Planning in Mainstream Applications – Important Considerations

10.34048/2018.2.f2 ◽

2018 ◽

Author(s):

Biplav Srivastava ◽

Anton V ◽

Anton V. Riabov ◽

Adi Botea

Keyword(s):

Industrial Applications ◽

New Wave ◽

Business Rules ◽

Learning Constraints

Planning has been used in many industrial applications but they are still few and far between compared to other AI sub-fields like learning, constraints and (business) rules. In this paper, we highlight key considerations important in practice and articulate the issues therein which if addressed, we anticipate, will trigger a new wave of planning-based applications.

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Bridging the Gap between Business Rules and Ontologies in a Skills Man-Agement Application

SSRN Electronic Journal ◽

10.2139/ssrn.2910850 ◽

2016 ◽

Author(s):

Sabina Cristiana Necula

Keyword(s):

Business Rules

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Cross-border Distribution of Collective Investment Products in the EU

10.1093/oso/9780198813392.003.0019 ◽

2018 ◽

Cited By ~ 1

Author(s):

Matteo Gargantini ◽

Carmine Di Noia ◽

Georgios Dimitropoulos

Keyword(s):

Home Country ◽

Legal Framework ◽

Business Rules ◽

Investment Funds ◽

Legal Rules ◽

Section 8 ◽

Cross Border ◽

Product Regulation ◽

Supervisory Practices ◽

The Eu

This chapter analyzes the current regulatory framework for cross-border distribution of investment funds and submits some proposals to improve it. The chapter is organized as follows. Section 2 provides a schematic description of the legal taxonomy for collective investment schemes. Section 3 addresses the EU disclosure regimes that apply to the distribution of various types of investment funds. Sections 4 and 5 consider conduct-of-business rules and, respectively, the legal framework for the allocation of supervisory powers on product regulation when fund units are distributed in more than one country. Section 6 provides some data that help assess the performance of the current framework for cross-border distribution. It then analyzes some of the residual legal rules and supervisory practices that still make cross-border distributions of funds more burdensome than purely national distributions, whether these restrictions are set forth in the country where investors are domiciled (Section 7) or in the fund's home country (Section 8).

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