Paper: Terminology Extraction Approaches for Product Aspect Detection in Customer Reviews

ACL ID W13-3524
Title Terminology Extraction Approaches for Product Aspect Detection in Customer Reviews
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2013
Authors

In this paper, we address the problem of identifying relevant product aspects in a collection of online customer reviews. Be- ing able to detect such aspects represents an important subtask of aspect-based re- view mining systems, which aim at auto- matically generating structured summaries of customer opinions. We cast the task as a terminology extraction problem and ex- amine the utility of varying term acquisi- tion heuristics, filtering techniques, vari- ant aggregation methods, and relevance measures. We evaluate the different ap- proaches on two distinct datasets (hotel and camera reviews). For the best config- uration, we find significant improvements over a state-of-the-art baseline method.