Constituency Lattice Encoding for Aspect Term Extraction
One of the remaining challenges for aspect term extraction in sentiment analysis resides in the extraction of phrase-level aspect terms, which is non-trivial to determine the boundaries of such terms. In this paper, we aim to address this issue by incorporating the span annotations of constituents of a sentence to leverage the syntactic information in neural network models. To this end, we first construct a constituency lattice structure based on the constituents of a constituency tree. Then, we present two approaches to encoding the constituency lattice using BiLSTM-CRF and BERT as the base models, respectively. We experimented on two benchmark datasets to evaluate the two models, and the results confirm their superiority with respective 3.17 and 1.35 points gained in F1-Measure over the current state of the art. The improvements justify the effectiveness of the constituency lattice for aspect term extraction.
Code (1)
Tasks
Aspect Term Extraction and Sentiment ClassificationSentenceSentiment AnalysisTerm ExtractionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Shift-Reduce Constituency Parsing with Dynamic Programming and POS Tag Lattice
A Multi-Task Dual-Tree Network for Aspect Sentiment Triplet Extraction
Aspect Sentiment Triplet Extraction (ASTE) aims at extracting triplets from a given sentence, where each triplet includes an aspect, its sentiment polarity, and a corresponding opinion explaining the polarity. Existing m…
Aspect Sentiment Triplet ExtractionSentenceTripletA Graph-based Lattice Dependency Parser for Joint Morphological Segmentation and Syntactic Analysis
Space-delimited words in Turkish and Hebrew text can be further segmented into meaningful units, but syntactic and semantic context is necessary to predict segmentation. At the same time, predicting correct syntactic str…
Dependency ParsingMorphological AnalysisMorphological TaggingSegmentation+1PoD: Positional Dependency-Based Word Embedding for Aspect Term Extraction
Dependency context-based word embedding jointly learns the representations of word and dependency context, and has been proved effective in aspect term extraction. In this paper, we design the positional dependency-based…
Aspect Term Extraction and Sentiment ClassificationPOSPositionTerm ExtractionAn Aspect Extraction Framework using Different Embedding Types, Learning Models, and Dependency Structure
Aspect-based sentiment analysis has gained significant attention in recent years due to its ability to provide fine-grained insights for sentiment expressions related to specific features of entities. An important compon…
Aspect-Based Sentiment AnalysisAspect ExtractionDependency ParsingSentiment Analysis