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Text Classification

125 papers with code · Natural Language Processing

Text classification is the task of assigning a sentence or document an appropriate category. The categories depend on the chosen dataset and can range from topics.

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Greatest papers with code

Adversarial Training Methods for Semi-Supervised Text Classification

25 May 2016tensorflow/models

Adversarial training provides a means of regularizing supervised learning algorithms while virtual adversarial training is able to extend supervised learning algorithms to the semi-supervised setting.

SENTIMENT ANALYSIS TEXT CLASSIFICATION WORD EMBEDDINGS

Semi-supervised Sequence Learning

NeurIPS 2015 tensorflow/models

In our experiments, we find that long short term memory recurrent networks after being pretrained with the two approaches are more stable and generalize better.

LANGUAGE MODELLING TEXT CLASSIFICATION

FastText.zip: Compressing text classification models

12 Dec 2016facebookresearch/fastText

We consider the problem of producing compact architectures for text classification, such that the full model fits in a limited amount of memory.

QUANTIZATION TEXT CLASSIFICATION WORD EMBEDDINGS

StarSpace: Embed All The Things!

12 Sep 2017facebookresearch/ParlAI

A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

COLLABORATIVE FILTERING TEXT CLASSIFICATION WORD EMBEDDINGS

PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts

IJCNLP 2017 beamandrew/medical-data

First, the majority of datasets for sequential short-text classification (i. e., classification of short texts that appear in sequences) are small: we hope that releasing a new large dataset will help develop more accurate algorithms for this task.

SENTENCE CLASSIFICATION

Revisiting Semi-Supervised Learning with Graph Embeddings

29 Mar 2016tkipf/gcn

We present a semi-supervised learning framework based on graph embeddings.

DOCUMENT CLASSIFICATION ENTITY EXTRACTION NODE CLASSIFICATION

Simple Recurrent Units for Highly Parallelizable Recurrence

EMNLP 2018 taolei87/sru

Common recurrent neural architectures scale poorly due to the intrinsic difficulty in parallelizing their state computations.

MACHINE TRANSLATION QUESTION ANSWERING TEXT CLASSIFICATION

Universal Sentence Encoder

29 Mar 2018facebookresearch/InferSent

For both variants, we investigate and report the relationship between model complexity, resource consumption, the availability of transfer task training data, and task performance.

SEMANTIC TEXTUAL SIMILARITY SENTENCE EMBEDDINGS SENTIMENT ANALYSIS SUBJECTIVITY ANALYSIS TEXT CLASSIFICATION TRANSFER LEARNING WORD EMBEDDINGS