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Semantic Web pp 153-172 | Cite as

Reliable Semantic Systems for Decision Making: Defining a Business Rules Ontology for a Survey Decision System

  • Pavani AkundiEmail author
Chapter

Abstract

Concepts like “decision analysis” and “data mining” refer to knowledge engineering techniques used by researchers to gather statistics and influence decisions about requirements. These concepts are also relevant when defining meaningful business rules as evaluation criteria for decision making. In this chapter, a decision domain is modeled for community health outreach survey. The basic semantic framework is stated in terms of inference statements, facts, and business rules. The semantic web, web ontologies, and linked data models are referenced in architecting a desirable system. A sample survey dataset is also reviewed to explicitly understand the business rules influencing the design of decision criteria, categories, and variables. For this reason, evaluating the size of the sample, decision criteria, and typical survey structures is important to establish a baseline semantic decision domain. Business users can derive constraints and conditions pertaining to empirical outcomes appearing in data analysis by reviewing semantic design patterns. Data mining constructs are also applied to the data to learn about patterns within the sample size and introduce new evaluation criteria to clarify survey questions. This discussion identifies the best practices of applying business rules to drive planning decisions.

Keywords

Decision Support System Unify Modeling Language Decision Criterion Requirement Engineering Resource Description Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSouthern Methodist UniversityDallasUSA

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