Hierarchical Aspect-guided Explanation Generation for Explainable Recommendation

no code implementations • 20 Oct 2021 • Yidan Hu, Yong liu, Chunyan Miao, Gongqi Lin, Yuan Miao

In this paper, we propose a novel explanation generation framework, named Hierarchical Aspect-guided explanation Generation (HAG), for explainable recommendation.

Explainable Recommendation Explanation Generation +2

Commonsense Knowledge + BERT for Level 2 Reading Comprehension Ability Test

no code implementations • 8 Sep 2019 • Yidan Hu, Gongqi Lin, Yuan Miao, Chunyan Miao

In this research, we propose a system which aims to allow computers to read articles and answer related questions with commonsense knowledge like a human being for CAT level 2.

Reading Comprehension

Reading Comprehension Ability Test-A Turing Test for Reading Comprehension

no code implementations • 5 Sep 2019 • Yuan Miao, Gongqi Lin, Yidan Hu, Chunyan Miao

In order to be able to compare the difference between people reading and machines reading, we proposed a test called (reading) Comprehension Ability Test (CAT). CAT is similar to Turing test, passing of which means we cannot differentiate people from algorithms in term of their comprehension ability.

Reading Comprehension