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Titlebook: Enterprise Information Systems; 16th International C José Cordeiro,Slimane Hammoudi,Joaquim Filipe Conference proceedings 2015 Springer Int

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樓主: deliberate
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發(fā)表于 2025-3-23 11:00:17 | 只看該作者
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發(fā)表于 2025-3-23 17:28:12 | 只看該作者
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發(fā)表于 2025-3-23 20:52:04 | 只看該作者
ValueApping: An Analysis Method to Identify Value-Adding Mobile Enterprise Apps in Business Processeta acquisitioning or ubiquitous access to up-to-date information. To leverage these business potentials, a critical success factor is the identification and evaluation of value-adding MEAs based on an analysis of the business process. For this purpose, we present ValueApping, a systematic analysis m
14#
發(fā)表于 2025-3-23 22:40:22 | 只看該作者
An Overview on Aspect-Oriented Requirements Engineering Areaand composition of crosscutting concerns (also called early-aspects). Several AORE approaches have been developed recently, with different features, strengths and limitations. .: the aim of this paper is threefold: (i) cataloguing existing AORE approaches based on the activities encompassed by them;
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發(fā)表于 2025-3-24 03:57:15 | 只看該作者
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發(fā)表于 2025-3-24 06:37:40 | 只看該作者
https://doi.org/10.1007/978-3-030-12014-6hich has an effect on the human interpretation on information. This paper pioneers a new perspective of digital visualisation by positioning digital visualisation as a process of abduction and proposes the key principles in digital visualisation.
17#
發(fā)表于 2025-3-24 13:00:28 | 只看該作者
Why Do Organizations Need Conflicts?ay state the hypothesis that while the ethics behavior of people decreases over time the data fraud rate is continuously increasing..There does not exist an omnibus data fraud detector, and the author supposes there will be never one upcoming due to the heterogeneity of the domain. For instance, com
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發(fā)表于 2025-3-24 16:00:51 | 只看該作者
https://doi.org/10.1057/9781137312662xperiments using real traffic data of a brazilian city, Fortaleza, and compared our approach with the centralized and the MapReduce-based approaches. Our preliminary results confirmed that our approach is scalable and more efficient than the other ones. We also present an incremental version of DBSC
19#
發(fā)表于 2025-3-24 21:50:58 | 只看該作者
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發(fā)表于 2025-3-25 01:14:27 | 只看該作者
https://doi.org/10.1007/978-1-349-17060-9ng methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). T
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