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WSDM'21: The 14th ACM International Conference on Web Search and Data Mining

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Evgeniy GabrilovichAuthors Info & Claims

ACM SIGWEB Newsletter, Volume 2021, Issue Summer

Article No.: 1, Pages 1 - 3

https://doi.org/10.1145/3473044.3473045

Published: 12 October 2021 Publication History

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Abstract

The ACM International Conference on Web Search and Data Mining (WSDM) is one of the premier conferences on web-related research involving web search and data mining, with a dynamic and growing community from academia and industry. This year, WSDM was held virtually on March 8th -- 12th, 2021, due to the Covid-19 pandemic, instead of the originally-planned location in Jerusalem, Israel. WSDM'21 program reflects the breadth and diversity of research in the field and showcases the latest developments in these domains.

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Liu YZhu RGao M(2024)Personalized Programming Guidance Based on Deep Programming Learning Style CapturingComputer Science and Education. Computer Science and Technology10.1007/978-981-97-0730-0_20(214-231)Online publication date: 26-Feb-2024
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Xu HZheng CZhao ZSun X(2023)Multi-Hypergraph Neural Networks for Emotion Recognition in Multi-Party ConversationsApplied Sciences10.3390/app1303166013:3(1660)Online publication date: 28-Jan-2023
https://doi.org/10.3390/app13031660
Li YRadev DRafiei DLi YRadev DRafiei D(2023)InteractivityNatural Language Interfaces to Databases10.1007/978-3-031-45043-3_7(177-229)Online publication date: 25-Nov-2023
https://doi.org/10.1007/978-3-031-45043-3_7
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Published In

ACM SIGWEB Newsletter Volume 2021, Issue Summer

Summer 2021

32 pages

ISSN:1931-1745

EISSN:1931-1435

DOI:10.1145/3473044

Editor:
Martin Veselý

Issue’s Table of Contents

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 12 October 2021

Published in SIGWEB Volume 2021, Issue Summer

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Liu YZhu RGao M(2024)Personalized Programming Guidance Based on Deep Programming Learning Style CapturingComputer Science and Education. Computer Science and Technology10.1007/978-981-97-0730-0_20(214-231)Online publication date: 26-Feb-2024
https://doi.org/10.1007/978-981-97-0730-0_20
Xu HZheng CZhao ZSun X(2023)Multi-Hypergraph Neural Networks for Emotion Recognition in Multi-Party ConversationsApplied Sciences10.3390/app1303166013:3(1660)Online publication date: 28-Jan-2023
https://doi.org/10.3390/app13031660
Li YRadev DRafiei DLi YRadev DRafiei D(2023)InteractivityNatural Language Interfaces to Databases10.1007/978-3-031-45043-3_7(177-229)Online publication date: 25-Nov-2023
https://doi.org/10.1007/978-3-031-45043-3_7
Waqas AFarooq HBouaynaya NRasool G(2022)Exploring robust architectures for deep artificial neural networksCommunications Engineering10.1038/s44172-022-00043-21:1Online publication date: 17-Dec-2022
https://doi.org/10.1038/s44172-022-00043-2
Zhan HPei X(2022)Dealing with the unevenness: deeper insights in graph-based attack and defenseMachine Language10.1007/s10994-022-06234-4113:5(2921-2953)Online publication date: 7-Oct-2022
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Shu LChen CXing XLiao XZheng Z(2021)AHNAInternational Journal of Intelligent Systems10.1002/int.2266437:2(1157-1185)Online publication date: 28-Dec-2021
https://dl.acm.org/doi/10.1002/int.22664

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