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Titlebook: Innovation Through Information Systems; Volume II: A Collect Frederik Ahlemann,Reinhard Schütte,Stefan Stieglit Conference proceedings 2021

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樓主: BRISK
21#
發(fā)表于 2025-3-25 05:44:23 | 只看該作者
22#
發(fā)表于 2025-3-25 08:11:10 | 只看該作者
Towards a Trust-Aware Item Recommendation System on a Graph Autoencoder with Attention Mechanismion such as past item ratings and personal data can be considered as inputs of these systems. In this study, we aim to utilize a trust-graph-based Neural Network in the recommendation process. The proposed method tries to increase the performance of graph-based RSs by considering the inferred level
23#
發(fā)表于 2025-3-25 12:40:14 | 只看該作者
A Holistic Framework for AI Systems in Industrial Applications Existing literature covers a variety of frameworks, methods and processes related to AI systems. However, the application of AI systems in manufacturing companies lacks a uniform understanding of components and functionalities as well as a structured process that supports developers and project man
24#
發(fā)表于 2025-3-25 18:28:41 | 只看該作者
25#
發(fā)表于 2025-3-25 21:26:27 | 只看該作者
26#
發(fā)表于 2025-3-26 03:06:40 | 只看該作者
Voice Assistants in Voice Commerce: The Impact of Social Cues on Trust and Satisfaction spoken dialogue (voice commerce). However, the widespread use of voice commerce is hindered by a lack of satisfaction and trust among VA users. This study investigates whether social cues and the accompanying perception of the VA’s humanness and social presence can overcome existing obstacles in vo
27#
發(fā)表于 2025-3-26 07:59:24 | 只看該作者
Design of Artificial Neural Networks for Traffic Forecasting in the Context of Smart Mobility Solutisis for future smart mobility solutions. After processing the acquired sensor data, information about the current traffic situation can be derived and events such as rush hour, weekends or holidays can be identified. Based on current research findings in the field of traffic forecasting using neural
28#
發(fā)表于 2025-3-26 10:52:08 | 只看該作者
29#
發(fā)表于 2025-3-26 14:57:15 | 只看該作者
Empirically Exploring the Cause-Effect Relationships of AI Characteristics, Project Management Chall creating new or enriched products and services. However, the failure rate of projects on implementing AI in organizations is still high, and prevents organizations from fully seizing the potential that AI exhibits. To contribute to closing this gap, we seize the unique opportunity to gain insights
30#
發(fā)表于 2025-3-26 19:35:53 | 只看該作者
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