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Titlebook: Service-Oriented Computing; 21st International C Flavia Monti,Stefanie Rinderle-Ma,Massimo Mecella Conference proceedings 2023 The Editor(s

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發(fā)表于 2025-3-23 13:33:14 | 只看該作者
Data-Driven Generation of?Services for?IoT-Based Online Activity Detectiond a software architecture to execute these services. Our proof-of-concept implementation is based on an extensible complex event processing platform enabling the online detection of activities from IoT data. We use a running example from smart manufacturing to showcase the framework.
12#
發(fā)表于 2025-3-23 15:07:06 | 只看該作者
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發(fā)表于 2025-3-23 18:29:04 | 只看該作者
LoVizQL: A Query Language for?Visualizing and?Analyzing Business Processes from?Event Logsiscover, analyze, and optimize business processes. Process mining tools offer many functionalities such as data filtering, process discovery, process visualization, or conformance checking. Process visualization is generally based on Directly-Follows Graphs (DFGs), where each node represents an acti
14#
發(fā)表于 2025-3-23 23:48:46 | 只看該作者
On the?Nature of?Data in?RPA Botsare based on graphical notations, data, a key component of RPA, is often not explicitly represented, making it difficult to understand how data contributes to the automation. This paper explores the role of data in RPA, extends the ontology of RPA operations by data aspects, and proposes a visualiza
15#
發(fā)表于 2025-3-24 03:49:17 | 只看該作者
Remaining Time Prediction for?Collaborative Business Processes with?Privacy Preservationivities. This makes it challenging to predict remaining time without access to data on completed activities of other organizations. To address this challenge, this research proposes a strategy for predicting remaining time in collaborative business processes, which involve sequential sub-processes e
16#
發(fā)表于 2025-3-24 07:59:02 | 只看該作者
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發(fā)表于 2025-3-24 13:12:52 | 只看該作者
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發(fā)表于 2025-3-24 18:09:59 | 只看該作者
19#
發(fā)表于 2025-3-24 21:00:05 | 只看該作者
Observation Is Reality? A?Graph Diffusion-Based Approach for?Service Tags Recommendatione tags recommendation studies fail to consider real-world scenarios, greatly limiting their performance and capability of handling complex situations. First, the simplification of service tags recommendation to single-tag classification or clustering overlooks the complexity and diversity of crossov
20#
發(fā)表于 2025-3-25 02:02:01 | 只看該作者
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