Abstract
In this paper we introduce the problem of identifying usage expression sentences in a consumer product review. We create a human-annotated gold standard dataset of 565 reviews spanning five distinct product categories. Our dataset consists of more than 3,000 annotated sentences. We further introduce a classification system to label sentences according to whether or not they describe some “usage”. The system combines lexical, syntactic, and semantic features in a product-agnostic fashion to yield good classification performance. We show the effectiveness of our approach using importance ranking of features, error analysis, and cross-product classification experiments.- Anthology ID:
- I17-1040
- Volume:
- Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Month:
- November
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Greg Kondrak, Taro Watanabe
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 394–403
- Language:
- URL:
- https://aclanthology.org/I17-1040
- DOI:
- Cite (ACL):
- Shibamouli Lahiri, V.G.Vinod Vydiswaran, and Rada Mihalcea. 2017. Identifying Usage Expression Sentences in Consumer Product Reviews. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 394–403, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- Identifying Usage Expression Sentences in Consumer Product Reviews (Lahiri et al., IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/I17-1040.pdf