WIT: Workshop on deriving Insights from user-generated Text
Pages 4131 - 4132
Abstract
User-Generated text is a rich source of user insights and experiences that can be very helpful in many different daily life situations, such as when deciding what product to buy, what hotel to stay, what company to apply for a job, what region to buy a house, etc. This kind of text also plays a very relevant role in current research efforts in academic research groups, technology companies, as well as big publishers, telecommunications players, recruiting and job-market focuses organizations, etc. The goal of this new workshop is to bring together researchers interested in the application of novel techniques in AI/ML/NLP and Knowledge Discovery to address challenges around harnessing text-heavy user-generated data that is available to organizations and over the Web. The workshop program contains invited speakers, contributed talks, poster sessions and a discussion panel
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- WIT: Workshop on deriving Insights from user-generated Text
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August 2021
4259 pages
ISBN:9781450383325
DOI:10.1145/3447548
- General Chairs:
- Feida Zhu,
- Beng Chin Ooi,
- Chunyan Miao,
- Program Chairs:
- Haixun Wang,
- Iryna Skrypnyk,
- Wynne Hsu,
- Sanjay Chawla
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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
Publication History
Published: 14 August 2021
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- Abstract
Conference
KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
August 14 - 18, 2021
Virtual Event, Singapore
Acceptance Rates
Overall Acceptance Rate 1,133 of 8,635 submissions, 13%
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