Comprehensive Multi-Modal Classification System for News Outlets and Digital Platforms Outlets in Mongolia
Building a multi-modal classification system tailored for the Mongolian online environment, this initiative leverages insights from a variety of data modalities, including text, social features, user information, and network propagation. The primary objective is to achieve a thorough detection and categorization of content, ensuring that the Mongolian digital audience has access to accurate and reliable information. In this 8-week challenge, you will join a collaborative team of 50 AI engineers from all around the world.
Ready to make a difference in your community?
Join Omdena’s local chapter, established as a part of the Media and Civil Society Strengthening (MACSS) project in Mongolia implemented by The Asia Foundation with the generous support from the United States Agency for International Development, and be at the forefront of empowering citizens for effective governance. Whether you’re a data scientist, AI enthusiast, or passionate about social impact, there’s a place for you in our community. Let’s collaborate, learn, and drive positive change together
The central challenge this initiative seeks to address is the effective categorization and discernment of online content within the Mongolian digital landscape. By developing a multi-modal classification system, the project aims to harness diverse data sources — ranging from text and social features to user information and network propagation patterns. The goal is to establish a robust mechanism that can meticulously detect and categorize the vast array of content circulating online. This system strives to ensure that the digital audience in Mongolia has access to content that is accurate and reliable, thereby enhancing the overall quality and trustworthiness of information available in the Mongolian online environment.
The project goals
The project sets forth several goals aimed at enhancing the digital experience for users in Mongolia:
- Comprehensive Content Classification: Develop a sophisticated multi-modal classification system that can effectively detect and categorize various types of online content, using a combination of text analysis, social features, user information, and network propagation patterns.
- Enhanced Information Reliability: Ensure that the digital audience in Mongolia has access to accurate and reliable information, thereby raising the overall standard of content available online.
- Utilization of Diverse Data Modalities: Leverage insights from multiple data sources, acknowledging the complexity of online interactions and the multifaceted nature of digital content.
- Advanced Detection Mechanisms: Implement cutting-edge techniques for the detection and categorization of content, making the process more efficient and reliable.
- Tailored to the Mongolian Online Environment: Customize the system to align with the specific characteristics and needs of the Mongolian digital landscape, ensuring it is highly effective and relevant in this context.
By achieving these goals, the project aims to substantially improve the digital landscape in Mongolia, offering a more reliable and high-quality online experience for users.
Why join? The uniqueness of Omdena AI Innovation Challenges
A collaborative experience you never had in your working life! For the next eight weeks, you will not only build AI solutions to make a real-world impact but also go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.
And the best part is that you will join a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.