WebTopicRNN: when Topic model meets RNN Introduction "Topicrnn: A recurrent neural network with long-range semantic dependency"这篇论文介绍了一个基于RNN的语言模型(language model)，模型通过隐含主题(latent topics)捕捉全局语义信息从而连接词语。模型的目标是1）语法正确，2）主题语义的一致。 Web其将单词输入到RNN的每个cell中，通过最后的状态向量进行分类任务。Liu et al.提出了一种RNN模型能捕获长文本的语义特性。TopicRNN是一类可用来进行主题任务建模的模型，该方法能通过隐主题特征来表征词和文章之间的关系，并且隐主题模型能捕获全局语法依赖。
TopicRNN: A Recurrent Neural Network with Long-Range …
Web5. nov 2016 · In this paper, we propose TopicRNN, a recurrent neural network (RNN)-based language model designed to directly capture the global semantic meaning relating words in a document via latent topics. Because of their sequential nature, RNNs are good at capturing the local structure of a word sequence - both semantic and syntactic - but might face … WebTopicRNN [10], NVDM [25], the Sigmoid Belief Document Model [29] and DocNADE [22]. Finally, non-probabilistic approaches to topic modeling employ heuristically designed loss functions. For example, Cao et al. [7] used a ranking loss to train an LDA inspired neural topic model. 3 An alternative view of LDA cosentino the zin
Discriminative Topic Modeling with Logistic LDA - arXiv
Web1. aug 2024 · NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment analysis and related tasks, researchers have therefore used binarized emoticons and specific hashtags as forms of distant supervision. Our paper shows that by extending the distant supervision to a more diverse set of noisy labels, the models can … Web20. aug 2024 · 沒有賬号? 新增賬號. 注冊. 郵箱 WebIn this paper, we propose TopicRNN, a recurrent neural network (RNN)-based language model designed to directly capture the global semantic meaning relating words in a … bread loaf cabinet