A Semantic QA-Based Approach for Text Summarization Evaluation

Understand

Many Natural Language Processing and Computational Linguistics applications involves the generation of new texts based on some existing texts, such as summarization, text simplification and machine translation.

• However, there has been a serious problem haunting these applications for decades, that is, how to automatically and accurately assess quality of these applications.
• In this paper, we will present some preliminary results on one especially useful and challenging problem in NLP system evaluation: how to pinpoint content differences of two text passages (especially for large pas-sages such as articles and books).
• Our idea is intuitive and very different from existing approaches.