Text Categorization
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pke: an open source python-based keyphrase extraction toolkit
We describe pke, an open source python-based keyphrase extraction toolkit.
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.
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.
IMAGE CLASSIFICATION SKELETON BASED ACTION RECOGNITION TEXT CATEGORIZATION