The Workshop of Artificial Intelligence for Web-Centric Time Series Analysis (AI4TS): Theory, Algorithms, and Applications

The Artificial Intelligence for Web-Centric Time Series Analysis (AI4TS) Workshop at The Web Conference 2025 aims to unite experts from academia and industry to advance artificial intelligence for web-centric time series analysis. This full-day workshop will feature at least five keynote talks, paper presentations, and a panel discussion, engaging attendees in topics that span theory, algorithms, and applications within web-based time series analysis. With a focus on web-sourced data from IoT devices, social media, and cloud platforms, the workshop addresses pressing challenges such as anomaly detection, forecasting, classification, and generation across diverse fields, including finance, healthcare, transportation, and biological sciences. AI researchers, practitioners, and policymakers are anticipated to join, fostering a collaborative environment to explore innovative approaches in time series for web applications. Building on the success of prior AI4TS workshops, this event will continue to honor outstanding research contributions. Supported by organization and committee members from both industry and academia, this will mark a new instance of the AI4TS series, following previous workshops hosted with KDD, ICDM, AAAI, IJCAI, etc., each drawing over 80 participants on average.

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Publication Details

Published
2025-05-08
DOI
https://doi.org/10.1145/3701716.3717379
Primary Topic
Time Series Analysis and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

The Workshop of Artificial Intelligence for Web-Centric Time Series Analysis (AI4TS): Theory, Algorithms, and Applications

Shirui Pan, Dongjin Song, Yuxuan Liang, Mahsa Salehi et al.
Time Series Analysis and Forecasting
article

The Workshop of Artificial Intelligence for Web-Centric Time Series Analysis (AI4TS): Theory, Algorithms, and Applications

Shirui Pan, Dongjin Song, Yuxuan Liang, Mahsa Salehi, Qingsong Wen, Flora Dilys Salim, Min Wu, Ming Jin
article en

Abstract

The Artificial Intelligence for Web-Centric Time Series Analysis (AI4TS) Workshop at The Web Conference 2025 aims to unite experts from academia and industry to advance artificial intelligence for web-centric time series analysis. This full-day workshop will feature at least five keynote talks, paper presentations, and a panel discussion, engaging attendees in topics that span theory, algorithms, and applications within web-based time series analysis. With a focus on web-sourced data from IoT devices, social media, and cloud platforms, the workshop addresses pressing challenges such as anomaly detection, forecasting, classification, and generation across diverse fields, including finance, healthcare, transportation, and biological sciences. AI researchers, practitioners, and policymakers are anticipated to join, fostering a collaborative environment to explore innovative approaches in time series for web applications. Building on the success of prior AI4TS workshops, this event will continue to honor outstanding research contributions. Supported by organization and committee members from both industry and academia, this will mark a new instance of the AI4TS series, following previous workshops hosted with KDD, ICDM, AAAI, IJCAI, etc., each drawing over 80 participants on average.

Griffith University (AU), University of Connecticut (US), UNSW Sydney (AU), A*STAR Graduate Academy (SG), Monash University (AU), Seattle University (US)
Openalex Percentile: Top 88%
Time Series Analysis and Forecasting
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The Workshop of Artificial Intelligence for Web-Centric Time Series Analysis (AI4TS): Theory, Algorithms, and Applications — Shirui Pan, Dongjin Song, et al. · (2025) | TGRS Research Map | TGRS