2021 Proceeding- General Chairs:
- Feida Zhu,
- Beng Chin Ooi,
- Chunyan Miao,
- Program Chairs:
- Haixun Wang,
- Iryna Skrypnyk,
- Wynne Hsu,
- Sanjay Chawla
On behalf of the organizing committee, we would like to extend our warmest welcome to all of you to the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, which is held virtually between August 14th and 18th, 2021, due to COVID-19. While a decision to move an offline gathering opportunity fully online is never easy, we are glad that we are able to present a truly global conference experience by combining the benefit of a virtual gathering and the unique flavor of Singapore - the Lion City.
Virtual conferences, often following a chosen time zone, are always challenging for the great number of attendees half a globe apart. At KDD 2021, it is our belief that a truly global conference should offer a good experience to a maximum number of people, instead of maximizing the experience for a good number of people. We therefore introduce three new features in the history of KDD: Firstly, KDD 2021 accommodates both Singapore Time and US Time by allocating events and sessions to time slots best fit for authors and organizers within a full 24-hour time window for each conference day. Wherever you are, there are some events you can attend live without staying up till midnight. Secondly, registered participants are able to view papers and videos one month before the actual conference date to better digest the material and interact with the authors through online chatting, enjoying the maximized benefit of getting rid of constraints of physical meeting space and time. Finally, live paper sessions are made more interactive and engaging with mini-panels at the end on topics of common interest to the audience of each session.
KDD 2021 continues the tradition of KDD of featuring an exciting program. We are honoured to have Dr. Janil Puthucheary, Senior Minister of State, Ministry of Communications & Information and Ministry of Health to welcome the audience with an opening speech. We bring to the community 4 keynote talks led by 2021 Turing Award winner, Prof. Jeff Ullman, and 20 Applied Data Science track invited talks featuring the best and state-of-the-art from the industry of data science community. The program includes 40 lecture-style tutorials and 52 workshops covering an amazingly wide range of both classic and trending topics in data science. Besides the usual Health Day and Deep Learning Day, KDD 2021 launches two new special-theme days --- the "Trust Day" and the "ESG (Environmental, Social and Corporate Governance) Day" --- to bring together researchers, practitioners and experts from various communities to exchange and explore ideas, frontiers, opportunities and challenges of these domains of ever-growing importance in a highly interdisciplinary manner. This year's KDD Cup has attracted thousands of teams around the world to compete in three challenges of great novelty. We feature "Women in KDD" to highlight Diversity and Inclusion in our community.
A virtual conference can still provide a riveting experience to sample and savour unique Singapore local attractions. KDD 2021 makes this possible by embedding a near-realistic virtual world into Gather.Town with 10 Singapore iconic attraction neighbourhoods, in which participants can roam, explore and interact with conference materials as well as multimedia showcasing Singapore local fun and delights.
Cited By
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Diehl J and Krieg R (2024). FRUITS: feature extraction using iterated sums for time series classification, Data Mining and Knowledge Discovery, 10.1007/s10618-024-01068-1
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Bauer J, Gonzalez E, Severa W, Vineyard C, Chen K, Overman T and Hammoud R (2024). SAR ATR analysis and implications for learning Automatic Target Recognition XXXIV, 10.1117/12.3014042, 9781510673960, (25)
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BOHORAN T, Kampaktsis P, McLaughlin L, Leb J, Moustakidis S, McCann G, Giannakidis A and Osten W (2024). Embracing uncertainty flexibility: harnessing a supervised tree kernel to empower ensemble modelling for 2D echocardiography-based prediction of right ventricular volume Sixteenth International Conference on Machine Vision (ICMV 2023), 10.1117/12.3023433, 9781510674622, (33)
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Krause T, Deriyeva A, Beinke J, Bartels G and Thomas O (2024). Mitigating Exposure Bias in Recommender Systems – A Comparative Analysis of Discrete Choice Models, ACM Transactions on Recommender Systems, 10.1145/3641291
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Jiang H, Yan L, Liu D, Wan X, Ahmad B and Subramaniyam K (2023). Meta-learning-based recommendation method for self-supervised hybrid comparison learning International Conference on Internet of Things and Machine Learning (IoTML 2023), 10.1117/12.3013361, 9781510671805, (47)
- Zeyu H, Yan L, Wendi F, Wei Z, Alenezi F and Tiwari P (2023). Causal embedding of user interest and conformity for long-tail session-based recommendations, Information Sciences: an International Journal, 644:C, Online publication date: 1-Oct-2023.
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Wang H, Chen X and Srivastava H (2023). Analysis and visualization of the parameter space of matrix factorization-based recommender systems 2023 3rd International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2023), 10.1117/12.2686703, 9781510667600, (209)
- Er-Rahmadi B, Oncevay A, Ji Y and Pan J KATIE: A System for Key Attributes Identification in Product Knowledge Graph Construction Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, (3320-3324)
Index Terms
- Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining