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Titlebook: Machine Learning and Knowledge Extraction; Second IFIP TC 5, TC Andreas Holzinger,Peter Kieseberg,Edgar Weippl Conference proceedings 2018

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樓主: Defect
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發(fā)表于 2025-3-26 23:27:18 | 只看該作者
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發(fā)表于 2025-3-27 01:43:26 | 只看該作者
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發(fā)表于 2025-3-27 09:34:17 | 只看該作者
LawStats – Large-Scale German Court Decision Evaluation Using Web Service Classifiers00 court decisions and extracted the outcomes and relevant entities. The modular architecture of the application allows continuous improvements of the ML model as more annotations become available over time. The tool can provide a critical foundation for further quantitative research in the legal do
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發(fā)表于 2025-3-27 16:16:05 | 只看該作者
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發(fā)表于 2025-3-27 19:15:57 | 只看該作者
Current Advances, Trends and Challenges of Machine Learning and Knowledge Extraction: From Machine cifically. Due to the huge ongoing success in machine learning, particularly in statistical learning from big data, there is rising interest of academia, industry and the public in this field. Industry is investing heavily in AI, and spin-offs and start-ups are emerging on an unprecedented rate. The
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發(fā)表于 2025-3-28 01:10:26 | 只看該作者
38#
發(fā)表于 2025-3-28 02:34:01 | 只看該作者
Mouse Tracking Measures and Movement Patterns with Application for Online Surveys personality. Previous work has defined various patterns of mouse movement behavior. However, there is a paucity of mouse tracking measures and defined movement patterns for use in the specific context of data collection with online surveys. The present study aimed to define and visualize patterns o
39#
發(fā)表于 2025-3-28 08:49:19 | 只看該作者
Knowledge Compilation Techniques for Model-Based Diagnosis of Complex Active Systems inspired by this idea, a diagnosis technique of a class of discrete-event systems, called complex active systems, is presented. A complex active system is a hierarchical graph, where each node is a network of communicating automata, called an active unit. Specific interaction patterns among automat
40#
發(fā)表于 2025-3-28 12:14:34 | 只看該作者
Recognition of Handwritten Characters Using Google Fonts and Freeman Chain Codeshis research is to be able to transcribe this dataset into machine readable text. The approach used in this study is able to convert the document image without any prior knowledge of the text. In fact, the training set used in this study is a synthetic dataset built on the Google Fonts database. A f
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