PoD: 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 word embedding (PoD) which considers both dependency context and positional context for aspect term extraction. Specifically, the positional context is modeled via relative position encoding. Besides, we enhance the dependency context by integrating more lexical information (e.g., POS tags) along dependency paths. Experiments on SemEval 2014/2015/2016 datasets show that our approach outperforms other embedding methods in aspect term extraction.
Code (0)
등록된 구현이 없습니다.
Tasks
Aspect Term Extraction and Sentiment ClassificationPOSPositionTerm ExtractionSimilar Papers 제목 키워드 기반
An 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 AnalysisUnsupervised Word and Dependency Path Embeddings for Aspect Term Extraction
In this paper, we develop a novel approach to aspect term extraction based on unsupervised learning of distributed representations of words and dependency paths. The basic idea is to connect two words (w1 and w2) with th…
Term ExtractionBERT4GCN: Using BERT Intermediate Layers to Augment GCN for Aspect-based Sentiment Classification
Graph-based Aspect-based Sentiment Classification (ABSC) approaches have yielded state-of-the-art results, expecially when equipped with contextual word embedding from pre-training language models (PLMs). However, they i…
Sentiment AnalysisSentiment ClassificationAspect-Level Sentiment Analysis Via Convolution over Dependency Tree
We propose a method based on neural networks to identify the sentiment polarity of opinion words expressed on a specific aspect of a sentence. Although a large majority of works typically focus on leveraging the expressi…
Representation LearningSentenceSentiment AnalysisSentiment ClassificationModelling Context and Syntactical Features for Aspect-based Sentiment Analysis
The aspect-based sentiment analysis (ABSA) consists of two conceptual tasks, namely an aspect extraction and an aspect sentiment classification. Rather than considering the tasks separately, we build an end-to-end ABSA s…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Aspect ExtractionSentence+2