Text Categorization
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Greatest papers with code
Automatically Annotated Turkish Corpus for Named Entity Recognition and Text Categorization using Large-Scale Gazetteers
• juand-r/entity-recognition-datasets
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Turkish Wikipedia Named-Entity Recognition and Text Categorization (TWNERTC) dataset is a collection of automatically categorized and annotated sentences obtained from Wikipedia.
pke: an open source python-based keyphrase extraction toolkit
We describe pke, an open source python-based keyphrase extraction toolkit.
Inverse-Category-Frequency based supervised term weighting scheme for text categorization
• textvec/textvec
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Term weighting schemes often dominate the performance of many classifiers, such as kNN, centroid-based classifier and SVMs.
PySS3: A Python package implementing a novel text classifier with visualization tools for Explainable AI
A recently introduced text classifier, called SS3, has obtained state-of-the-art performance on the CLEF's eRisk tasks.
DOCUMENT CLASSIFICATION MULTI-LABEL TEXT CLASSIFICATION SENTENCE CLASSIFICATION TEXT CATEGORIZATION
t-SS3: a text classifier with dynamic n-grams for early risk detection over text streams
A recently introduced classifier, called SS3, has shown to be well suited to deal with early risk detection (ERD) problems on text streams.
DOCUMENT CLASSIFICATION MULTI-LABEL TEXT CLASSIFICATION SENTENCE CLASSIFICATION TEXT CATEGORIZATION
Massively Multilingual Word Embeddings
We introduce new methods for estimating and evaluating embeddings of words in more than fifty languages in a single shared embedding space.
Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications
• cair/TextUnderstandingTsetlinMachine
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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.
HFT-CNN: Learning Hierarchical Category Structure for Multi-label Short Text Categorization
The lower the HS level, the less the categorization performance.
EXTREME MULTI-LABEL CLASSIFICATION MULTI-LABEL CLASSIFICATION TEXT CATEGORIZATION
Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations
• HongyangGao/hConv-gPool-Net
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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.
Structure-Aware Convolutional Neural Networks
NeurIPS 2018
• vector-1127/SACNNs
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Convolutional neural networks (CNNs) are inherently subject to invariable filters that can only aggregate local inputs with the same topological structures.
ACTIVITY DETECTION IMAGE CLASSIFICATION SKELETON BASED ACTION RECOGNITION TEXT CATEGORIZATION