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Fine-grained Opinion Mining with Recurrent Neural Networks and Word Embeddings
TLDR
We propose a general class of discriminative models based on recurrent neural networks (RNNs) and word embeddings that can be successfully applied to fine-grained opinion mining tasks without any taskspecific feature engineering effort. Expand
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CODRA: A Novel Discriminative Framework for Rhetorical Analysis
TLDR
We present CODRA— a COmplete probabilistic Discriminative framework for performing Rhetorical Analysis in accordance withRhetorical Structure Theory, which posits a tree representation of a discourse. Expand
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Combining Intra- and Multi-sentential Rhetorical Parsing for Document-level Discourse Analysis
TLDR
We propose a novel approach for developing a two-stage document-level discourse parser based on probabilistic discriminative parsing models, represented as Conditional Random Fields. Expand
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Distributed Representations of Tuples for Entity Resolution
Despite the efforts in 70+ years in all aspects of entity resolution (ER), there is still a high demand for democratizing ER – by reducing the heavy human involvement in labeling data, performingExpand
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Robust Classification of Crisis-Related Data on Social Networks Using Convolutional Neural Networks
TLDR
The role of social media, in particular microblogging platforms such as Twitter, as a conduit for actionable and tactical information during disasters brings challenges to machine learning techniques, especially the ones that use supervised learning. Expand
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ANR: Aspect-based Neural Recommender
TLDR
We propose a novel end-to-end Aspect-based Neural Recommender (ANR) to perform aspect-based representation learning for both users and items via an attention-based component. Expand
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Sleep Quality Prediction From Wearable Data Using Deep Learning
Background The importance of sleep is paramount to health. Insufficient sleep can reduce physical, emotional, and mental well-being and can lead to a multitude of health complications among peopleExpand
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Unsupervised Modeling of Dialog Acts in Asynchronous Conversations
TLDR
We present unsupervised approaches to the problem of modeling dialog acts in asynchronous conversations. Expand
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A Novel Discriminative Framework for Sentence-Level Discourse Analysis
TLDR
We propose a complete probabilistic discriminative framework for performing sentence-level discourse analysis. Expand
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Applications of Online Deep Learning for Crisis Response Using Social Media Information
TLDR
We propose a new online algorithm based on stochastic gradient descent to train DNNs in an online fashion during disaster situations to address two types of information needs of humanitarian organizations. Expand
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