Towards One-Shot Learning for Text Classification using Inductive Logic Programming

08/30/2023
by   Ghazal Afroozi Milani, et al.
0

With the ever-increasing potential of AI to perform personalised tasks, it is becoming essential to develop new machine learning techniques which are data-efficient and do not require hundreds or thousands of training data. In this paper, we explore an Inductive Logic Programming approach for one-shot text classification. In particular, we explore the framework of Meta-Interpretive Learning (MIL), along with using common-sense background knowledge extracted from ConceptNet. Results indicate that MIL can learn text classification rules from a small number of training examples. Moreover, the higher complexity of chosen examples, the higher accuracy of the outcome.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset