基于显式高阶接近度推荐的面向任务的协同图嵌入

IF 3.5 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Big Data Research Pub Date : 2023-04-01 DOI:10.1016/j.bdr.2023.100382

Mintae Kim, Wooju Kim

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Task-Oriented Collaborative Graph Embedding Using Explicit High-Order Proximity for Recommendation

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Task-Oriented Collaborative Graph Embedding Using Explicit High-Order Proximity for Recommendation

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来源期刊

Big Data Research Computer Science-Computer Science Applications

CiteScore

8.40

自引率

3.00%

发文量

期刊介绍： The journal aims to promote and communicate advances in big data research by providing a fast and high quality forum for researchers, practitioners and policy makers from the very many different communities working on, and with, this topic. The journal will accept papers on foundational aspects in dealing with big data, as well as papers on specific Platforms and Technologies used to deal with big data. To promote Data Science and interdisciplinary collaboration between fields, and to showcase the benefits of data driven research, papers demonstrating applications of big data in domains as diverse as Geoscience, Social Web, Finance, e-Commerce, Health Care, Environment and Climate, Physics and Astronomy, Chemistry, life sciences and drug discovery, digital libraries and scientific publications, security and government will also be considered. Occasionally the journal may publish whitepapers on policies, standards and best practices.