Integrating Question Classification and Deep Learning for improved Answer Selection (C18-1)
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| Challenge: | Question Answering (QA) is the task of automatically generating answers to questions posed in natural language. |
| Approach: | They propose a system for Answer Selection that integrates fine-grained Question Classification with a Deep Learning model designed for Answer selection. |
| Outcome: | The proposed system outperforms the current state of the art in all variations except one . the proposed system improves QA by reducing the search space of potential answers . |
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| Challenge: | Using a joint approach, we found that the model is more efficient than those developed in machine reading (MR) work. |
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Original Content Is All You Need! an Empirical Study on Leveraging Answer Summary for WikiHowQA Answer Selection Task (2022.coling-1)
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Liang Wen, Juan Li, Houfeng Wang, Yingwei Luo, Xiaolin Wang, Xiaodong Zhang, Zhicong Cheng, Dawei Yin
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Leveraging Structured Metadata for Improving Question Answering on the Web (2020.aacl-main)
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| Challenge: | Using metadata information from web pages can improve the performance of answer passage selection/reranking models. |
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