Time series data has become ubiquitous across numerous web systems, including web services, cloud computing, IoT devices, digital health platforms, wearable technology, financial markets, biological sciences, and environmental sciences. With the availability of massive amounts of data, complex underlying structures & distributions, and advanced high-performance computing platforms, there is a growing demand for new theories and algorithms to address fundamental challenges (e.g., representation, prediction, generation, and causal analysis) across a variety of applications.

Time series analysis now plays a crucial role in addressing key challenges in web-based environments, including server load balancing, anomaly detection in e-commerce traffic, and tourism demand forecasting. This workshop aims to provide a platform for researchers and AI practitioners from both academia and industry to discuss potential research directions, key technical issues, and present solutions to tackle related challenges in practical web-based applications involving time series data. We invite researchers, AI practitioners, and policymakers from the related areas of machine learning, data science, statistics, econometrics, and many others to contribute to this workshop.

This workshop encourages submissions of innovative solutions for a broad range of web-centric time series analysis problems. Topics of interest include but are not limited to the following:

• Time series forecasting and prediction
• Spatio-temporal forecasting and prediction
• Time series anomaly detection and diagnosis
• Time series change point detection
• Time series classification and clustering
• Time series similarity search
• Time series indexing
• Time series compression
• Time series pattern discovery
• Interpretation and explanation in time series
• Causal inference in time series
• Bias and fairness in time series
• Benchmarks, experimental evaluation, and comparison for time series analysis tasks
• Foundation models and LLMs for time series analysis
• Time series applications in various areas: E-commerce, Cloud computing, Transportation, Fintech, Healthcare, Internet of things, Wireless networks, Predictive maintenance, Education, Energy, Climate, etc.

Submissions should be 4-8 pages long, excluding references, and must follow the new standard ACM conference proceedings template. The review process is double-blind, so authors should ensure their identities are not revealed to reviewers. An optional appendix of arbitrary length is allowed and should be put at the end of the paper (after references). All manuscripts should be submitted in a single PDF file including all content, figures, tables, references, and other information.

For LaTeX users: unzip acmart.zip, make, and use sample-sigconf.tex as a template; Additional information about formatting and style files is available online at: https://www.acm.org/publications/proceedings-template

We will use EasyChair to manage the submission and peer-reviewing process for this workshop. Accepted papers will be presented as posters during the workshop and listed on the website (non-archival/without proceedings). A small number of accepted papers will be selected to be presented as contributed talks (15-minute oral presentations). We also welcome submissions of unpublished papers, including those submitted/accepted to other venues if that other venue allows.

Submission site: https://easychair.org/my/conference?conf=ai4ts25

Dual submission policy: This workshop is non-archival; all accepted papers will be available on this website, there are no formally-published proceedings. If a paper is currently under review at another venue, it can still be submitted to this workshop. If a paper has previously appeared in a journal, workshop, or conference, it should be reasonably extended in order to be accepted at this workshop. Parallel submission of papers under review at WWW 2025 is allowed.

!! TheWebConf 2025 fast-track submissions: Authors should include an Appendix following the references section, where they must directly paste the reviews received during the main review process. These reviews will be utilized to determine acceptance into the workshop. Modifying or altering reviewer comments is strictly prohibited. In the appendix, authors are required to include a section titled "Improvements", where they should briefly outline whether they were able to address any of the issues highlighted in the main review and provide details of the revisions made. Only minor revisions are permitted; substantial changes are not allowed. Additionally, it is entirely acceptable to report no revisions if the work is already in satisfactory condition. The provided reviews will not be shared with any third parties or individuals other than the workshop organizers. Strict adherence to privacy and the double-blind policy will be maintained.