Paper: Product Feature Mining: Semantic Clues versus Syntactic Constituents

ACL ID P14-1032
Title Product Feature Mining: Semantic Clues versus Syntactic Constituents
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Product feature mining is a key subtask in fine-grained opinion mining. Previ- ous works often use syntax constituents in this task. However, syntax-based methods can only use discrete contextual informa- tion, which may suffer from data sparsity. This paper proposes a novel product fea- ture mining method which leverages lexi- cal and contextual semantic clues. Lexical semantic clue verifies whether a candidate term is related to the target product, and contextual semantic clue serves as a soft pattern miner to find candidates, which ex- ploits semantics of each word in context so as to alleviate the data sparsity prob- lem. We build a semantic similarity graph to encode lexical semantic clue, and em- ploy a convolutional neural model to cap- ture contextual semantic clue. Then Label Prop...