Mri485
发表于 2025-3-23 11:52:55
The Role of Openness and Extension Modularization in Value Capture for Platform-Based Digital Transf companies are switching from predominantly product-focused to platform-based business models. However, it remains unclear how these platforms should be designed to enable platform owners to maximize value capture. In this study, we investigated the interactions between platform openness and extensi
debacle
发表于 2025-3-23 17:53:11
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aggressor
发表于 2025-3-23 18:56:16
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浮雕
发表于 2025-3-23 23:44:58
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泥沼
发表于 2025-3-24 04:21:43
1865-1348 take place in Colorado Springs, CO, USA. Due to the COVID-19 pandemic, the conference was held fully online during June 8–10, 2020. This year‘s theme was "Data Science and Security in Business Information Systems". ..The 30 contributions presented in this volume were carefully reviewed and selected
垫子
发表于 2025-3-24 08:05:08
The Black Mirror: What Your Mobile Phone Number Reveals About Youe tested 1,000 random phone numbers for their matching to social media accounts. The results raise concerns how network and communication layers are predominately connected. PSMs will support future organizational sensitivity for data linkability.
创造性
发表于 2025-3-24 11:48:52
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顽固
发表于 2025-3-24 15:46:24
Towards an Automatized Way for Modeling Big Data System Architecturesrs a foundation towards a standard for the modeling of BDSA. Further, a prototype is introduced that automatizes the creation of those models reducing the required effort and simultaneously increasing the maintainability.
OVER
发表于 2025-3-24 22:45:57
Empowering Domain Experts to Preprocess Massive Distributed Datasetsr conflict resolution and recommendations based on data not contained in the sample itself. We implemented a fully functional prototype and conducted a user study with 12 participants. We show that our approach delivers a significantly higher error correction than comparable approaches which only consider the sample dataset.
Minatory
发表于 2025-3-24 23:16:38
Efficient Construction of Behavior Graphs for Uncertain Event Datais paper we present a novel approach to efficiently compute a graph representation of the behavior contained in an uncertain process trace. We present our new algorithm, analyze its time complexity, and report experimental results showing order-of-magnitude performance improvements for behavior graph construction.