Knowledge Management for Model Driven Data Cleaning of Very Large Database

Computer and Information Science

Cruz

Elfaki

et al. 2013

Self Cite

Abstract. Many theories and solutions have been proposed for the improvement of the learning efficiency of secondary language(L2) learning. However neither an unified view on the functionality of semantics in aiding learning nor an objective measure of the efficiency improvement at theoretical level has been presented in existing literature. This situation hinders the efficient adoption of the semantics aided learning and the explicit planning of a semantics aided learning process. We aim to fill these gaps by adopting an evolutionary strategy towards approaching a holistic solution. Firstly we model the general learning process from cognitive linguistic perspective at the memory level. Then we justify the functionality of semantics aided approach according to specific conditions. Thereafter we propose the quantity measure for the improvement of learning efficiency in terms of reuse level for semantics aided secondary language learning from the perspective of value based analysis.

Section: Model Driven Based Strategy On Resolving Complexitymentioning

confidence: 99%

Modeling Value Evaluation of Semantics Aided Secondary Language Acquisition as Model Driven Knowledge Management

Computer and Information Science

Cruz

Elfaki

et al. 2013

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“…Over Design/OD is a form of Negative Information Introduction (NPII) [8]. Considering system design from perspective of dichotomy, the deviation ('D) in design is the discrepancy between the ideal design (IDD) and the actual design (ACD).…”

Section: Figure 2 Constraint Driven Designmentioning

confidence: 99%

Variability based Approach for Minimizing over Design and under Design

MATEC Web of Conferences

Narendra

Gao

et al. 2016

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Abstract. In this paper, we have considered Over Design (OD) and Under Design (UD) as two basic forms of negative variability construction that lead to both functional incompleteness and unexpected software quality degradation during design time and run time. To make our approach economically practical to the quality assurance at the whole life cycle of software production process, we aim to ensure that OD and UD are minimized in terms of values under economical goals. These requirements are concretized with the functionality implementation and the quality management of a quality lifecycle.

“…We call it "knowledge based value" which will be an advancement level of the trends of "data as a service" or "information as a service". Knowledge [12], [18] based value is related to the implementation of knowledge as a service (KaaS) in XaaS/EaaS [8]. We define KaaS as using knowledge to help to solve a problem or provide a problem solution from the problem solving perspective.…”

Section: Modeling Exchange and Introducing Broker Patternmentioning

confidence: 99%

Modeling Service Value Transfer Beyond Normalization

2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed C

2012

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Modeling of the value transfer of service based business systems is often based on the value normalization in terms of the value of money. We identify that the normalization is neither applicable for not normalizable properties of services of XaaS/EaaS(everything as a service) nor contributing to modeling the business nature of service based systems. We explore from a knowledge engineering approach the foundation of value modeling factors including "unit of account" and "value normalization". We propose a holistic formula for assisting tradeoffs on the modeling factors. We identify possible not normalizable situations and introduce a service value broker mode as solution initiatives with demonstrative cases.