Abstract
In e-commerce websites, user-generated question-answering text pairs generally contain rich aspect information of products. In this paper, we address a new task, namely Question-answering (QA) aspect classification, which aims to automatically classify the aspect category of a given QA text pair. In particular, we build a high-quality annotated corpus with specifically designed annotation guidelines for QA aspect classification. On this basis, we propose a hierarchical attention network to address the specific challenges in this new task in three stages. Specifically, we firstly segment both question text and answer text into sentences, and then construct (sentence, sentence) units for each QA text pair. Second, we leverage a QA matching attention layer to encode these (sentence, sentence) units in order to capture the aspect matching information between the sentence inside question text and the sentence inside answer text. Finally, we leverage a self-matching attention layer to capture different importance degrees of different (sentence, sentence) units in each QA text pair. Experimental results demonstrate that our proposed hierarchical attention network outperforms some strong baselines for QA aspect classification.
Original language | English |
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Title of host publication | Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data |
Subtitle of host publication | 17th China National Conference, CCL 2018 and 6th International Symposium, NLP-NABD 2018 Changsha, China, October 19–21, 2018 Proceedings |
Editors | Maosong Sun, Ting Liu, Xiaojie Wang, Zhiyuan Liu, Yang Liu |
Place of Publication | Cham Switzerland |
Publisher | Springer |
Pages | 225-237 |
Number of pages | 13 |
ISBN (Electronic) | 9783030017163 |
ISBN (Print) | 9783030017156 |
DOIs | |
Publication status | Published - 2018 |
Event | Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data 2018 - Changsha, China Duration: 19 Oct 2018 → 21 Oct 2018 Conference number: 17th & 6th http://www.cips-cl.org/static/CCL2018/index.html |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer |
Volume | 11221 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data 2018 |
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Abbreviated title | CCL 2018 & NLP-NABD 2018 |
Country/Territory | China |
City | Changsha |
Period | 19/10/18 → 21/10/18 |
Internet address |
Keywords
- Aspect classification
- Hierarchical attention
- Question answering