Dependency-based Convolutional Neural Networks for Sentence Embedding

2015-07-07 · IJCNLP 2015 7 · Mingbo Ma, Liang Huang, Bing Xiang, Bo-Wen Zhou

In sentence modeling and classification, convolutional neural network approaches have recently achieved state-of-the-art results, but all such efforts process word vectors sequentially and neglect long-distance dependencies. To exploit both deep learning and linguistic structures, we propose a tree-based convolutional neural network model which exploit various long-distance relationships between words. Our model improves the sequential baselines on all three sentiment and question classification tasks, and achieves the highest published accuracy on TREC.

📄 PDF Abstract BibTeX arXiv:1507.01839

Code (1)

cosmmb/DCNN 공식 구현

Tasks

AllClassification General ClassificationSentenceSentence EmbeddingSentence-Embedding

Dependency Sensitive Convolutional Neural Networks for Modeling Sentences and Documents

2016-11-08 · NAACL 2016 6 · Rui Zhang, Honglak Lee, Dragomir Radev

The goal of sentence and document modeling is to accurately represent the meaning of sentences and documents for various Natural Language Processing tasks. In this work, we present Dependency Sensitive Convolutional Neur…

Classification General Classification Sentence Sentence Embeddings+2

Aspect-Level Sentiment Analysis Via Convolution over Dependency Tree

2019-11-01 · IJCNLP 2019 11 · Kai Sun, Richong Zhang, Samuel Mensah, Yongyi Mao 외

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 Learning Sentence Sentiment Analysis Sentiment Classification

Sentence Modeling with Deep Neural Architecture using Lexicon and Character Attention Mechanism for Sentiment Classification

2017-11-01 · IJCNLP 2017 11 · Huy Thanh Nguyen, Minh Le Nguyen

Tweet-level sentiment classification in Twitter social networking has many challenges: exploiting syntax, semantic, sentiment, and context in tweets. To address these problems, we propose a novel approach to sentiment an…

Classification General Classification Sentence Sentiment Analysis+2

BeLLM: Backward Dependency Enhanced Large Language Model for Sentence Embeddings

2023-11-09 · Xianming Li, Jing Li

Sentence embeddings are crucial in measuring semantic similarity. Most recent studies employed large language models (LLMs) to learn sentence embeddings. Existing LLMs mainly adopted autoregressive architecture without e…

Language Modeling Language Modelling Large Language Model Semantic Similarity+4

Learning Word Representations with Cross-Sentence Dependency for End-to-End Co-reference Resolution

2018-10-01 · EMNLP 2018 10 · Hongyin Luo, Jim Glass

In this work, we present a word embedding model that learns cross-sentence dependency for improving end-to-end co-reference resolution (E2E-CR). While the traditional E2E-CR model generates word representations by runnin…

Coreference Resolution Sentence