Using Aspect Extraction Approaches to Generate Review Summaries and User Profiles

Christopher Mitcheltree, Skyler Wharton, Avneesh Saluja


Abstract
Reviews of products or services on Internet marketplace websites contain a rich amount of information. Users often wish to survey reviews or review snippets from the perspective of a certain aspect, which has resulted in a large body of work on aspect identification and extraction from such corpora. In this work, we evaluate a newly-proposed neural model for aspect extraction on two practical tasks. The first is to extract canonical sentences of various aspects from reviews, and is judged by human evaluators against alternatives. A k-means baseline does remarkably well in this setting. The second experiment focuses on the suitability of the recovered aspect distributions to represent users by the reviews they have written. Through a set of review reranking experiments, we find that aspect-based profiles can largely capture notions of user preferences, by showing that divergent users generate markedly different review rankings.
Anthology ID:
N18-3009
Original:
N18-3009v1
Version 2:
N18-3009v2
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers)
Month:
June
Year:
2018
Address:
New Orleans - Louisiana
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
68–75
Language:
URL:
https://aclanthology.org/N18-3009
DOI:
10.18653/v1/N18-3009
Bibkey:
Cite (ACL):
Christopher Mitcheltree, Skyler Wharton, and Avneesh Saluja. 2018. Using Aspect Extraction Approaches to Generate Review Summaries and User Profiles. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers), pages 68–75, New Orleans - Louisiana. Association for Computational Linguistics.
Cite (Informal):
Using Aspect Extraction Approaches to Generate Review Summaries and User Profiles (Mitcheltree et al., NAACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/N18-3009.pdf