cogent
发表于 2025-3-25 05:58:37
0302-9743 5 submissions. It covers the science and technology of leveraging computing and information technology to model, create, operate, and manage business services..978-3-031-23514-6978-3-031-23515-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
神圣将军
发表于 2025-3-25 11:02:09
0302-9743 during December 10-14, 2022 in Honolulu, USA..The 8 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 15 submissions. It covers the science and technology of leveraging computing and information technology to model, create, operate, and manage business
Neutral-Spine
发表于 2025-3-25 14:47:54
,Research Directions in Process Modeling and Mining Using Knowledge Graphs and Machine Learning,owed promise for the automation of services discovery and composition (orchestration/choreography). The current large-scale deployment of enterprise knowledge graphs by many organizations coupled with huge advancements in machine learning (particularly deep learning) provides new opportunities for advancing this automation forward.
Pathogen
发表于 2025-3-25 15:51:07
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Concrete
发表于 2025-3-25 20:45:48
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火花
发表于 2025-3-26 02:35:12
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寒冷
发表于 2025-3-26 08:09:27
,Context Preserving Data Augmentation for Sequential Recommendation, recommender systems to learn relevant relationships between items. SR researchers rely on User Historical Interactions (UHI) for effective item representations. While it is well understood that UHI inherently suffers from data sparsity, which weakens item relation signals, seldom considered is the
Neutral-Spine
发表于 2025-3-26 09:40:43
Defending Environmental Competence: A Moral Principle for Data Use,oring and privacy invasion. In order to resolve these crises, various countries have initially established some ethical principles and frameworks in this field. It’s time to move from principles and frameworks to ethical data use practices. But integrating the principles of AI ethical framework into
Heart-Rate
发表于 2025-3-26 16:30:02
ELECTRA-KG: A Transformer-Knowledge Graph Recommender System,chers rely on KGs to help resolve the issues of cold start, diversity, and explainability in recommendations. However, the existing approaches usually ignore entity descriptions, which are essential in providing content information for entities in KGs. In this work, we propose a contextual language
fastness
发表于 2025-3-26 16:58:26
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