New AI Method Teaches Computers to Sort News Without Human Help
This could save companies millions by automating how they organize information.
Event ontology is the foundational framework for defining events in a dataset. Event type induction generally involves domain experts who define guidelines for creating event types and their names based on the dataset's domain and scope.
However, this process is resource-intensive in terms of annotation costs and is prone to human biases. To alleviate the need for manual event ontology creation, we propose the CLUE framework for event type induction, naming, and annotation.
Our main contributions in this work are: 1) designing a novel joint embedding representation for expressing both the verb-centric view and the semantic view of events; 2) event type induction using contrastive loss guided clustering; 3) event naming and refinement. Experiments demonstrate the effectiveness of our method. Our code is available at https://github.com/PratikMaitra/CLUE.
- CLUE is a new AI method that sorts news events without human labeling, saving time and money.
- It uses contrastive learning, where the AI learns by comparing similar and different examples.
- While promising, it may still make mistakes and is not yet available in everyday apps.
Why It Matters
This could lead to faster, more personalized news and information sorting, saving you time and improving your online experience.