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Titlebook: Business Information Systems; 17th International C Witold Abramowicz,Angelika Kokkinaki Conference proceedings 2014 Springer International

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Prescriptive Analytics for Recommendation-Based Business Process Optimizationly generates action recommendations during process execution to avoid a predicted metric deviation. We discuss data mining techniques and data structures for real-time prediction and recommendation generation and present a proof of concept based on a prototypical implementation in manufacturing.
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App‘ification of Enterprise Software: A Multiple-Case Study of Big Data Business Applications and distributed using enterprise app stores. A multiple-case study and an app’ification assessment model are used to produce insights into this phenomenon and to identify tangible measures to increase the app store readiness.
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Data State Description for the Migration to Activity-Centric Business Process Model Maintaining Legapropose a methodology and a set of mechanisms to support the data adaption, from a legacy database to an activity-centric business process. This methodology lets the description of the data object states, and their equivalences with the relational database by means of an Object-Relational Mapping and a Domain Specific Language.
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Intelligent System for Time Series Prediction in Stock Exchange Marketses obtained by prediction by the neural network at previous time. Analysis of the performance parameters of the neural network uses the method of the coefficient of certainty of neural prediction. Experimental study highlights the effectiveness of the proposed learning model for hybrid neural predictive system properties and its usefulness.
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LCBM: Statistics-Based Parallel Collaborative Filteringier of Beta distributions Means (LCBM), a novel collaborative filtering algorithm for binary ratings that is (i) inherently parallelizable and (ii) provides results whose quality is on-par with state-of-the-art solutions (iii) at a fraction of the computational cost.
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Resource Mining: Applying Process Mining to Resource-Oriented Systemsnly on SOAP-based Web Services leaving RESTful Web Service (resource-oriented) unsupported. In this article the relevance of adapting the Web Service Mining methods to new resource-oriented domain is introduced with initial work on process discovery in such systems.
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