Lexicon-Enhanced LSTM With Attention for General Sentiment Analysis
نویسندگان
چکیده
منابع مشابه
Lexicon Integrated CNN Models with Attention for Sentiment Analysis
With the advent of word embeddings, lexicons are no longer fully utilized for sentiment analysis although they still provide important features in the traditional setting. This paper introduces a novel approach to sentiment analysis that integrates lexicon embeddings and an attention mechanism into Convolutional Neural Networks. Our approach performs separate convolutions for word and lexicon e...
متن کاملAttention-based LSTM for Aspect-level Sentiment Classification
Aspect-level sentiment classification is a finegrained task in sentiment analysis. Since it provides more complete and in-depth results, aspect-level sentiment analysis has received much attention these years. In this paper, we reveal that the sentiment polarity of a sentence is not only determined by the content but is also highly related to the concerned aspect. For instance, “The appetizers ...
متن کاملAttention-based LSTM Network for Cross-Lingual Sentiment Classification
Most of the state-of-the-art sentiment classification methods are based on supervised learning algorithms which require large amounts of manually labeled data. However, the labeled resources are usually imbalanced in different languages. Cross-lingual sentiment classification tackles the problem by adapting the sentiment resources in a resource-rich language to resource-poor languages. In this ...
متن کاملTandem LSTM-SVM Approach for Sentiment Analysis
English. In this paper we describe our approach to EVALITA 2016 SENTIPOLC task. We participated in all the subtasks with constrained setting: Subjectivity Classification, Polarity Classification and Irony Detection. We developed a tandem architecture where Long Short Term Memory recurrent neural network is used to learn the feature space and to capture temporal dependencies, while the Support V...
متن کامل$\rho$-hot Lexicon Embedding-based Two-level LSTM for Sentiment Analysis
Sentiment analysis is a key component in various text mining applications. Numerous sentiment classification techniques, including conventional and deep learning-based methods, have been proposed in the literature. In most existing methods, a high-quality training set is assumed to be given. Nevertheless, constructing a high-quality training set that consists of highly accurate labels is challe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2018
ISSN: 2169-3536
DOI: 10.1109/access.2018.2878425