Paper: Unsupervised Approach to Extracting Problem Phrases from User Reviews of Products

ACL ID W14-4509
Title Unsupervised Approach to Extracting Problem Phrases from User Reviews of Products
Venue AHA!-Workshop on Information Discovery in Text
Session
Year 2014
Authors

This paper describes an approach to problem phrase extraction from texts that contain user expe- rience with products. In contrast to other works, we propose a straightforward approach to prob- lem phrase extraction based on syntactic and semantic connections between a problem indicator and mentions about the problem targets. In this paper, we discuss (i) grammatical dependencies between the target and the problem indicators and (ii) a number of domain-specific targets that were extracted using problem phrase structure and additional world knowledge. The algorithm achieves an average F1-measure of 77%, evaluated on reviews about electronic and automobile products.