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Titlebook: Requirements Engineering in the Big Data Era; Second Asia Pacific Lin Liu,Mikio Aoyama Conference proceedings 2015 Springer-Verlag Berlin

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41#
發(fā)表于 2025-3-28 15:46:14 | 只看該作者
Conceptual Framework for Understanding Security Requirements: A Preliminary Study on Stuxnetways, and are not limited to just a single pattern. Even though threats are represented by using a variety of modeling techniques, very little research has been done to learn about the security requirements needed from the understanding of commonly rooted causes of these threats. We propose a layere
42#
發(fā)表于 2025-3-28 21:27:01 | 只看該作者
TimePF: A Tool for Modeling and Verifying Timing Requirements Based on Problem Frames constraints especially some safety critical systems such as high-speed railway systems. We have proposed an approach for modeling and verifying timing requirements [.–.]. By combining the Problem Frames (PF) approach [.] and CCSL (Clock Constraint Specification Language) [.], it can model timing re
43#
發(fā)表于 2025-3-29 00:22:11 | 只看該作者
44#
發(fā)表于 2025-3-29 06:30:28 | 只看該作者
EVALUATOR: An Automated Tool for Service Selection reviews and feedback by the past users provide a great opportunity to gauge their sentiments towards a particular product or service. The benefits of sentiment analysis have not been fully utilized in third party service selection. In this paper we present a tool that assists the business analysts
45#
發(fā)表于 2025-3-29 09:00:46 | 只看該作者
978-3-662-48633-7Springer-Verlag Berlin Heidelberg 2015
46#
發(fā)表于 2025-3-29 13:01:49 | 只看該作者
47#
發(fā)表于 2025-3-29 17:24:23 | 只看該作者
48#
發(fā)表于 2025-3-29 20:41:30 | 只看該作者
Communications in Computer and Information Sciencehttp://image.papertrans.cn/r/image/827667.jpg
49#
發(fā)表于 2025-3-30 00:13:10 | 只看該作者
50#
發(fā)表于 2025-3-30 06:05:25 | 只看該作者
Automated Service Selection Using Natural Language Processinge proposed approach, and found 53% similar results with respect to top-15 services of the manual ranking. The same task, performed with the traditional cosine similarity ranking, produces only 13% similar results. The outcomes of our experiment are promising, and new insights have also emerged for f
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