Text Categorization

24 papers with code · Natural Language Processing
Subtask of Text Classification

Text Categorization is the task of automatically assigning pre-defined categories to documents written in natural languages. Several types of Text Categorization have been studied, each of which deals with different types of documents and categories, such as topic categorization to detect discussed topics (e.g., sports, politics), spam detection, and sentiment classification to determine the sentiment typically in product or movie reviews.

Source: Effective Use of Word Order for Text Categorization with Convolutional Neural Networks

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Greatest papers with code

Automatically Annotated Turkish Corpus for Named Entity Recognition and Text Categorization using Large-Scale Gazetteers

8 Feb 2017juand-r/entity-recognition-datasets

Turkish Wikipedia Named-Entity Recognition and Text Categorization (TWNERTC) dataset is a collection of automatically categorized and annotated sentences obtained from Wikipedia.

NAMED ENTITY RECOGNITION TEXT CATEGORIZATION

pke: an open source python-based keyphrase extraction toolkit

COLING 2016 boudinfl/pke

We describe pke, an open source python-based keyphrase extraction toolkit.

TEXT CATEGORIZATION

t-SS3: a text classifier with dynamic n-grams for early risk detection over text streams

11 Nov 2019sergioburdisso/pyss3

SS3 was created to deal with ERD problems naturally since: it supports incremental training and classification over text streams, and it can visually explain its rationale.

ANOREXIA DETECTION DOCUMENT CLASSIFICATION MULTI-LABEL TEXT CLASSIFICATION SENTENCE CLASSIFICATION TEXT CATEGORIZATION

Inverse-Category-Frequency based supervised term weighting scheme for text categorization

13 Dec 2010textvec/textvec

Term weighting schemes often dominate the performance of many classifiers, such as kNN, centroid-based classifier and SVMs.

INFORMATION RETRIEVAL TEXT CATEGORIZATION

Massively Multilingual Word Embeddings

5 Feb 2016idiap/mhan

We introduce new methods for estimating and evaluating embeddings of words in more than fifty languages in a single shared embedding space.

MULTILINGUAL WORD EMBEDDINGS TEXT CATEGORIZATION

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

12 Sep 2018cair/TextUnderstandingTsetlinMachine

The Tsetlin Machine either performs on par with or outperforms all of the evaluated methods on both the 20 Newsgroups and IMDb datasets, as well as on a non-public clinical dataset.

NATURAL LANGUAGE UNDERSTANDING TEXT CATEGORIZATION

Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations

21 Jan 2019HongyangGao/hConv-gPool-Net

Another limitation of GCN when used on graph-based text representation tasks is that, GCNs do not consider the order information of nodes in graph.

TEXT CATEGORIZATION

Structure-Aware Convolutional Neural Networks

NeurIPS 2018 vector-1127/SACNNs

Convolutional neural networks (CNNs) are inherently subject to invariable filters that can only aggregate local inputs with the same topological structures.

ACTION RECOGNITION ACTIVITY DETECTION IMAGE CLASSIFICATION SKELETON BASED ACTION RECOGNITION TEXT CATEGORIZATION