数据和人工智能模型市场:数据和模型共享、发现和集成的机会

IF 2.6 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Jian Pei, Raul Castro Fernandez, Xiaohui Yu
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引用次数: 0

摘要

数据和人工智能模型市场正在迅速崛起,在数据科学和人工智能领域和实践中越来越重要。这些市场正在从不同的角度进行研究,如电子商务、经济学、机器学习和数据管理。鉴于这些发展,迫切需要向数据库和数据管理界提出一份关于这一主题的全面和前瞻性调查报告。在本教程中,我们的目标是为数据和人工智能模型市场提供全面和跨学科的介绍。与最近一些只关注经济学方面的调查和教程不同,我们采取了一种新颖的视角,并将数据和人工智能模型市场视为解决数据和模型共享、发现和集成等长期问题的大好机会。我们使用实际的例子来激发数据和模型市场的重要性,呈现这些市场的当前行业格局,并从多个维度探索这些市场的模块和选项,包括市场中的资产(例如,数据与模型)、平台和参与者。此外,我们总结了最新的进展,并研究了数据和人工智能模型市场的未来方向,作为实现和促进共享、发现和集成的机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data and AI Model Markets: Opportunities for Data and Model Sharing, Discovery, and Integration
The markets for data and AI models are rapidly emerging and increasingly significant in the realm and the practices of data science and artificial intelligence. These markets are being studied from diverse perspectives, such as e-commerce, economics, machine learning, and data management. In light of these developments, there is a pressing need to present a comprehensive and forward-looking survey on the subject to the database and data management community. In this tutorial, we aim to provide a comprehensive and interdisciplinary introduction to data and AI model markets. Unlike a few recent surveys and tutorials that concentrate only on the economics aspect, we take a novel perspective and examine data and AI model markets as grand opportunities to address the long-standing problem of data and model sharing, discovery, and integration. We motivate the importance of data and model markets using practical examples, present the current industry landscape of such markets, and explore the modules and options of such markets from multiple dimensions, including assets in the markets (e.g., data versus models), platforms, and participants. Furthermore, we summarize the latest advancements and examine the future directions of data and AI model markets as mechanisms for enabling and facilitating sharing, discovery, and integration.
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来源期刊
Proceedings of the Vldb Endowment
Proceedings of the Vldb Endowment Computer Science-General Computer Science
CiteScore
7.70
自引率
0.00%
发文量
95
期刊介绍: The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.
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