Titlebook: Advances in Conceptual Modeling; ER 2014 Workshops, E Marta Indulska,Sandeep Purao Conference proceedings 2014 The Editor(s) (if applicable

CAB

Modeling Regulatory Compliance in Requirements Engineeringn this chapter are based on the following study letter: Lubienetzki, U. & Schüler-Lubienetzki, H. (2016). SAG MAL: WO GEHT’S LANG UND WIE KOMMEN WIR DAHIN? FACILITATION. Study letter of the Hochschule Fresenius online plus GmbH. Idstein: Hochschule Fresenius online plus GmbH.

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Practical Goal Modeling for Enterprise Change Context: A Problem Statements professor from Teachers College, Columbia University and Senior Scholar at the Carnegie Foundation for the Advancement of Teaching...."Mary Kooy is a gifted writer and teacher. She takes the obvious truth that we read books with other people and turns it into a compelling work of professional deve

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0302-9743 tlanta, GA, USA in October 2014. The 24 revised full and 6 short papers were carefully reviewed and selected out of 59 submissions and are presented together with 4 demonstrations. The papers are organized in sections related to the individual workshops: the First International Workshop on Enterpris

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https://doi.org/10.1007/978-3-662-49457-8ritical requirement of users, new types of systems have been developed to deal more efficiently with changing requirements: the Self-Service Systems. In this paper, we provide an overall discussion about what self systems are, what they imply in terms of engineering, how they can be designed, and what type of questions they raise to RE.

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Stefan Bornemann,Martin Klementutation, in order to evenly distribute a large-scale graph into a number of data partitions. Our semi-clustering scheme drastically improves the performance: total elapsed time including the cost of the semi-clustering computation reduced by up to 36%. Furthermore, the effectiveness of our scheme increases as the size of the graph increases.

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Der Sport und die Nachhaltigkeitsstrategien mining and supported by external knowledge. This external knowledge is represented by a torrent of information that, in many cases, is hidden across heterogeneous and unstructured data sources, which is recuperated by an Information Extraction system. This paper is complemented with a real case study that shows promising partial results.