Overview
The AutoNLP competition, part of the AutoDL series, invites participants to create automated solutions for text categorization. This competition is significant as it addresses the challenges faced in the field of automated language processing, especially in the context of the World Artificial Intelligence Conference (WAIC) 2019 in Shanghai.
Background & Relevance
Text categorization, also known as text classification, is a crucial task in natural language processing that involves assigning predefined categories to documents. This task has wide-ranging applications in various sectors, including content management, information retrieval, and sentiment analysis. Traditionally, text categorization has relied heavily on human experts, making it labor-intensive and time-consuming. The AutoNLP competition aims to revolutionize this process by encouraging the development of automated solutions that can streamline and enhance text categorization efforts.
Key Details
- Competition Start Date: August 2, 2019, 11:59 a.m. (UTC+8)
- End of Online Phase: August 21, 2019, 11:59 p.m. (UTC+8)
- Announcement of Top 10 Teams: August 22, 2019, 11:59 a.m. (UTC+8)
- On-site Phase Start: August 29, 2019, 8:59 a.m. (UTC+8)
- Final Winners Announcement: August 31, 2019
- Prizes: 1st Place: $4,500; 2nd Place: $2,250; 3rd Place: $750
- Challenge Platform: AutoNLP Competition
Eligibility & Participation
The competition is open to participants worldwide, including those outside the Chinese Mainland, who can join the On-site phase remotely. It targets researchers, practitioners, and students interested in advancing automated text categorization techniques.
Submission or Application Guidelines
To participate, individuals should:
1. Visit the challenge platform.
2. Review the problem setup and available datasets.
3. Download the practice datasets to develop AutoNLP solutions offline.
4. Submit codes for immediate feedback on the leaderboard.
5. Follow the competition rules to qualify for the On-site phase.
Additional Context / Real-World Relevance
The AutoNLP competition poses several challenges that reflect real-world issues in text categorization, such as preprocessing for different languages, handling varying text lengths, feature extraction, and model selection. Addressing these challenges can lead to more efficient and effective solutions in various applications, enhancing the capabilities of automated systems in processing and understanding human language.
Conclusion
The AutoNLP competition presents a unique opportunity for participants to contribute to the advancement of automated text categorization. By engaging in this challenge, individuals can explore innovative solutions and potentially shape the future of language processing technologies. Interested participants are encouraged to register and start developing their solutions.
Category: Conferences & Workshops
Tags: text categorization, autodl, machine learning, artificial intelligence, data science, neural networks, competitions, hackathon, 4paradigm, chalearn, google
