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What is Completeness

Chapter 445
Encyclopedia of Information Science and Technology, Fourth Edition
The state or condition of having all the necessary or appropriate parts of a model or document.
Published in Chapter:
Nominalizations in Requirements Engineering Natural Language Models
Claudia S. Litvak (Universidad Nacional de La Matanza, Argentina & Universidad Nacional del Oeste, Argentina), Graciela Dora Susana Hadad (Universidad Nacional del Oeste, Argentina & Universidad de Belgrano, Argentina), and Jorge Horacio Doorn (Universidad Nacional del Oeste, Argentina & Universidad Nacional de La Matanza, Argentina)
Copyright: © 2018 |Pages: 9
DOI: 10.4018/978-1-5225-2255-3.ch445
Abstract
It is a usual practice to use natural language in any document intended for clients and users in the requirements engineering process of a software development. This facilitates the comprehension of the requirements engineer's proposals to clients and users. However, natural language introduces some drawbacks, such as ambiguity and incompleteness, which attempt against a good comprehension of those documents. Glossaries help by reducing ambiguity, though they introduce their own linguistic weaknesses. The nominalization of verbs is one of them. There are sometimes appreciable differences between using a verb form or its nominal form, while in other cases they may be synonyms. Therefore, the requirements engineer must be aware of the precise meaning of each term used in the application domain, in order to correctly define them and properly use them in every document. In this chapter, guidelines about treatment of verb nominalization are given when constructing a specific glossary, called Language Extended Lexicon.
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Chapter 20
Decision Making by a Multiple-Rule Classifier: The Role of Rule Qualities
Completeness of a decision rule characterizes its power, that is, a rule with high completeness factor should cover the maximum of objects belonging to the rule’s class.
Published in Chapter: Decision Making by a Multiple-Rule Classifier: The Role of Rule Qualities; From: Encyclopedia of Decision Making and Decision Support Technologies
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Chapter 17
Text Summarization and Its Types: A Literature Review
Summary comprising of all-important information covered in input data.
Published in Chapter: Text Summarization and Its Types: A Literature Review; From: Handbook of Research on Natural Language Processing and Smart Service Systems
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Chapter 5
Web Intelligence: A Fuzzy Knowledge-Based Framework for the Enhancement of Querying and Accessing Web Data
In Artificial Intelligence (AI), completeness theorem is among the methods used for checking the validity of axioms and logical inference in the knowlegde base. However, a knowledge base is said to be complete if no formular can be added in the knowledge base.
Published in Chapter: Web Intelligence: A Fuzzy Knowledge-Based Framework for the Enhancement of Querying and Accessing Web Data; From: Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence
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Chapter 42
Measuring Data Quality in Context
A data quality dimension that reflects the inclusion of all the anticipated data and the extent to which exclusion of certain items affects fitness to use.
Published in Chapter: Measuring Data Quality in Context; From: Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends
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Chapter 49
Evaluating Online Resources
The comprehensiveness of the information.
Published in Chapter: Evaluating Online Resources; From: Encyclopedia of Information Technology Curriculum Integration
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Chapter 12
Rules Verification and Validation
For every potential input there exists at least one user-defined rule that can be fired to react in a designed way to the input.
Published in Chapter: Rules Verification and Validation; From: Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches
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Chapter 100
Explainable Artificial Intelligence
Characteristic of a good explanation that aims to describe a fact as precisely and accurately as possible ( Gilpin et al., 2019 AU58: The citation "Gilpin et al., 2019" matches multiple references. Please add letters (e.g. "Smith 2000a"), or additional authors to the citation, to uniquely match references and citations. ).
Published in Chapter: Explainable Artificial Intelligence; From: Encyclopedia of Data Science and Machine Learning
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Chapter 8
Computer Forensics and Cyber Attacks
The quality of being whole or perfect and having nothing missing.
Published in Chapter: Computer Forensics and Cyber Attacks; From: Handbook of Research on Cyber Crime and Information Privacy
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