WIT: Workshop On Deriving Insights From User-Generated Text Co-located with SIGKDD 2021, (Virtual) Singapore, Aug 14th-18th, 2021
Workshop Overview Users from Web platforms and online services generate tremendous amounts of user-generated data in the form of search requests, reviews, questions, and answers. We believe there is tremendous opportunity to exploit advanced AI/NLP techniques on user-generated text data which are rich in user insights and experiences. The WIT workshop provides a venue for researchers from the academia and industry to address challenges around harnessing text-heavy user-generated data that is available to different types of organizations, especially on topics pertaining to the pipeline of extracting data from unstructured text to a structured form to obtain insights. We will have a great line-up of Invited Speakers and Panelists. WIT will be held as a virtual single-day event at SIGKDD 2021.
We encourage submissions that describe a well-defined piece of research or is thought-provoking. Topics will include but are not limited to information extraction, data cleaning, entity matching, schema matching, semantic search, summarization, language generation, (common-sense) knowledge-bases and information seeking Q&A/Dialogue. Submitted papers can be regular papers or extended abstracts. If there is sufficient interest from the authors of accepted papers, we may publish the post-proceedings at CEUR. The maximum length of a regular paper is 8 pages plus unlimited number of pages for references. The maximum length of an extended abstract is 4 pages plus unlimited number of pages for references. At least one author of every accepted paper is expected to attend the workshop. Regular papers will be given an oral presentation slot. Extended abstracts will be presented in the form of poster/demo/short talks, depending on the workshop schedule. Important Dates
• Submission deadline (All submission types): May 20th, 2021
• Notification of acceptance: June 10, 2021
• Camera ready papers due: TBD
Submissions Papers should be formatted following KDD2021 template (as describe in guidelines here: https://www.acm.org/publications/proceedings-template) and submitted using the submission system available in this link: https://easychair.org/conferences/?conf=wit2021
• Estevam Hruschka, Megagon Labs (estevam at megagon.ai <mailto:estevam at megagon.ai>)
• Tom Mitchell, Carnegie Mellon University, (tom.mitchell at cmu.edu <mailto:tom.mitchell at cmu.edu>)
• Marko Grobelnik, Jozef Stefan Institute (JSI), (marko.grobelnik at ijs.si <mailto:marko.grobelnik at ijs.si>)
• Behzad Golshan, Megagon Labs (behzad at megagon.ai <mailto:behzad at megagon.ai>) Contact If you have any questions or inquiries regarding the workshop, need Mentorship on the suitability of your paper, or need further information, please do not hesitate to send an email to wit at megagon.ai.
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