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
Term weighting schemes often dominate the performance of many classifiers, such as kNN, centroid-based classifier and SVMs.
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
EMNLP 2018 • ShimShim46/HFT-CNN
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
Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text Classification
WS 2018
• y3nk0/Graph-Based-TC
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Contrary to the traditional Bag-of-Words approach, we consider the Graph-of-Words(GoW) model in which each document is represented by a graph that encodes relationships between the different terms.
Neural Discourse Structure for Text Categorization
ACL 2017 • jiyfeng/disco4textcat
We show that discourse structure, as defined by Rhetorical Structure Theory and provided by an existing discourse parser, benefits text categorization.