In this work we describe the system built for the three English subtasks of
the SemEval 2016 Task 3 by the Department of Computer Science of the University
of Houston (UH) and the Pattern Recognition and Human Language Technology
(PRHLT) research center - Universitat Politecnica de Valencia: UH-PRHLT. Our
system represents instances by using both lexical and semantic-based similarity
measures between text pairs. Our semantic features include the use of
distributed representations of words, knowledge graphs generated with the
BabelNet multilingual semantic network, and the FrameNet lexical database.
Experimental results outperform the random and Google search engine baselines
in the three English subtasks. Our approach obtained the highest results of
subtask B compared to the other task participants.

生成讲解博客的中文版本

生成AI智能校验的中文版本