BibSonomy publications for /user/cschie/rules

Visual Rules Modeling

cschie — 2009-05-05T14:54:23+02:00

Gerd Wagner Sergey Lukichev REWERSE, (2006)

Methodological approaches based on business rules

cschie — 2009-03-25T15:11:22+01:00

Uta Andreescu Informatica Economica 3(47):23-27 (2008)

Logical View of Architecture of Business Rules Repository

cschie — 2009-03-25T15:10:18+01:00

An approach to information system development based on business rules emphasizes the importance of rules and encourages explicit rule modelling. Rule repository supports storage, sharing and maintenance of rules captured in the process of modelling and development. Repository architecture that supports three abstraction levels: business system, information system and software system of rules and core functional requirements defined in the our earlier papers and in Haggerty et al. and including traceability, meta-data support, versioning integration, etc. is investigated. A logical view on architecture of rule repository with the main focus on a conceptual data model is suggested in the paper.

Modeling of Business Processes and Business Rules: An Integrated Methodology

cschie — 2009-03-24T16:23:28+01:00

Michael zur Muehlen, Marta Indulska, and Kai Kittel 19th Australasian Conference on Information Systems ACIS 2008, Christchurch, New Zealand, Australasian Computer Society, (2008)

Modeling languages for business processes and business rules: A representational analysis

cschie — 2009-03-24T16:15:52+01:00

Process modeling and rule modeling languages are both used to document organizational policies and procedures. To date, their synergies and overlap are under-researched. Understanding the relationship between the two modeling types would allow organizations to maximize synergies, avoid content duplication, and thus reduce their overall modeling effort. In this paper we use the Bunge-Wand-Weber (BWW) representation theory to compare the representation capabilities of process and rule modeling languages. We perform a representational analysis of four rule modeling specifications: The Simple Rule Markup Language (SRML), the Semantic Web Rules Language (SWRL), the Production Rule Representation (PRR) and the Semantics of Business Vocabulary and Business Rules (SBVR) specification. We compare their BWW representation capabilities with those of four popular conceptual process modeling languages. In our analysis we focus on the aspects of maximum ontological completeness and minimum ontological overlap. The outcome of this study shows that no single language is internally complete with respect to the BWW representation model. We also show that a combination of two languages, in particular SRML and BPMN, appears to be better suited for combined process and rule modeling than any of these modeling languages used independently.

On the Nature of Business Rules

cschie — 2009-03-18T15:22:49+01:00

Business rules are in the center of attention, both in the ‘business world’ and in the ‘ICT applications world’. Recently, the OMG has completed a major study in defining the notion of business rule and its associated notions. On closer look, however, the definitions provided appear to be not as rigid and precise as one would hope and as deemed necessary. Based on the consistent and coherent theoretical framework of Enterprise Ontology, several clarifications of the core notions regarding business rules are presented. They are illustrated by means of a small example case.

Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation

cschie — 2009-03-13T11:08:56+01:00

Credit-risk evaluation is a very challenging and important management science problem in the domain of financial analysis. Many classification methods have been suggested in the literature to tackle this problem. Neural networks, especially, have received a lot of attention because of their universal approximation property. However, a major drawback associated with the use of neural networks for decision making is their lack of explanation capability. While they can achieve a high predictive accuracy rate, the reasoning behind how they reach their decisions is not readily available. In this paper, we present the results from analysing three real-life credit-risk data sets using neural network rule extraction techniques. Clarifying the neural network decisions by explanatory rules that capture the learned knowledge embedded in the networks can help the credit-risk manager in explaining why a particular applicant is classified as either bad or good. Furthermore, we also discuss how these rules can be visualized as a decision table in a compact and intuitive graphical format that facilitates easy consultation. It is concluded that neural network rule extraction and decision tables are powerful management tools that allow us to build advanced and user-friendly decision-support systems for credit-risk evaluation.

Enterprise Modeling and Decision-Support for Automating the Business Rules Lifecycle

cschie — 2009-03-13T11:06:19+01:00

Business rules represent policies, procedures and constraints regarding how an enterprise conducts its business. To get the full benefits of modeling business rules requires an approach to managing them through their full lifecycle, from acquisition through deployment and evolution. The research reported in this paper is aimed at determining what infrastructure capabilities are needed to provide this lifecycle support. The solution embodies a modeling framework that captures the structure of the enterprise, in terms of which the business rules can be expressed, and decision-support capabilities for reasoning about and deriving business rules. The paper demonstrates the possibility of automatic support of the business rules lifecycle by automatically generating business rules from the captured information, along with data representing domain assumptions in a case study (the London Ambulance System). A system was implemented to illustrate the methodology and to demonstrate the feasibility of the approach. The methodology also gives guidance on how to deal with pragmatically important situations such as rules that involve both automated and human tasks, nondeterministic rules, and goal-oriented versus operational rules.

A methodology and tool support for managing business rules in organisations

cschie — 2009-03-13T10:58:13+01:00

Business rules are evidently important for organisations as they describe how they are doing business. Their value has also been recognised within the information system (IS) domain, mostly because of their ability to make applications flexible and amenable to change. In this paper, we propose a methodology that helps business people and developers to keep business rules at the business level inline with the rules that are implemented at the system level. In contrast to several existing approaches that primarily focus on business rules in the scope of an application, our methodology addresses the entire IS of an organisation. The paper also describes requirements for a tool support that would be appropriate to support the methodology.

The Handbook of Applied Expert Systems

cschie — 2009-03-09T17:52:08+01:00

The Handbook of Applied Expert Systems is a landmark work dedicatedsolely to this rapidly advancing area of study. Edited by Jay Liebowitz, a professor, author, and consultant known around the world for his work in the field, this authoritative source covers the latest expert system technologies, applications, methodologies, and practices. The book features contributions from more than 40 of the world's foremost expert systems authorities in industry, government, and academia. The Handbook is organized into two major sections. The first section explains expert systems technologies while the second section focuses on applied examples in a wide variety of industries. Key topics covered include fuzzy systems, genetic algorithm development, machine learning, knowledge representation, and much more.

On the Expressiveness of Rule-based Systems for Reasoning with Uncertainty.

cschie — 2009-03-09T15:53:23+01:00

David Heckerman, and Eric Horvitz AAAI, page 121-126. (1987)

Merging Model Driven Architecture and Semantic Web for Business Rules Generation

cschie — 2009-03-09T15:12:32+01:00

Mouhamed Diouf, Sofian Maabout, and Kaninda Musumbu Web Reasoning and Rule Systems (2007)

Knowledge representation concepts for automated SLA management

cschie — 2009-03-09T15:12:15+01:00

Outsourcing of complex IT infrastructure to IT service providers has increased substantially during the past years. IT service providers must be able to fulfil their service-quality commitments based upon predefined Service Level Agreements (SLAs) with the service customer. They need to manage, execute and maintain thousands of SLAs for different customers and different types of services, which needs new levels of flexibility and automation not available with the current technology. The complexity of contractual logic in SLAs requires new forms of knowledge representation to automatically draw inferences and execute contractual agreemen ts. A logic-based approach provides several advantages including automated rule chaining allowing for compact knowledge representation as well as flexibility to adapt to rapidly changing business requirements. We suggest logical formalisms for the representation and enforcement of SLA rules and describe a proof-of-concept implementation. The article describes selected formalisms of the ContractLog KR and their adequacy for automated SLA management and presents results of experiments and examples from common industry use cases to demonstrate the expressiveness of the language and the scalability of the approach.

Event-driven rules for sensing and responding to business situations

cschie — 2009-03-09T15:11:25+01:00

Event-based systems have been developed and used to implement networked and adaptive business environments based on loosely coupled systems in order to respond faster to critical business events. In this paper, we introduce a rule management system which is able to sense and evaluate events in order to respond to changes in a business environment or customer needs. It enables users to graphically compose comprehensive event-triggered rules, which can be used to control the processing of services. For the definition of a rule set, users can independently define event conditions, event patterns and correlation-related information which can be combined for modeling complex business situations. We have fully implemented the proposed system with a service-oriented approach and illustrate our approach with an order management business case.

Business Process and Business Rule Modeling: A Representational Analysis

cschie — 2009-03-03T13:29:52+01:00

Michael zur Muehlen, Marta Indulska, and Gerrit Kamp EDOCW '07: Proceedings of the 2007 Eleventh International IEEE EDOC Conference Workshop, page 189--196. Washington, DC, USA, IEEE Computer Society, (2007)

A Lifecycle Approach towards Business Rules Management

cschie — 2009-02-18T14:41:04+01:00

M.L. Nelson, R.L. Rariden, and R. Sen Hawaii International Conference on System Sciences, Proceedings of the 41st Annual (January 2008)

Patterns of Business Rules to Enable Agile Business Processes

cschie — 2009-02-17T18:50:00+01:00

T. Graml, R. Bracht, and M. Spies Enterprise Distributed Object Computing Conference, 2007. EDOC 2007. 11th IEEE International (October 2007)

Business Rule-oriented Conceptual Modeling

cschie — 2009-02-17T18:28:02+01:00

Holger Herbst (1997)

Regelbasierte Entwicklung betrieblicher Informationssysteme. Gestaltung flexibler Informationssysteme durch explizite Modellierung der Geschäftslogik

cschie — 2009-02-17T18:10:55+01:00

Rainer Endl Bern, (2004)

Swiss Workflow Management in Distributed Environments Modeling Processes and Workflows by Business Rules

cschie — 2009-02-17T18:04:51+01:00

Rainer Endl, Gerhard Knolmayer, and Marcel Pfahrer (1998)