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Supervised term-category feature weighting for improved text classification
Published 2022“…Text classification is a central task in Natural Language Processing (NLP) that aims at categorizing text documents into predefined classes or categories. …”
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Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…The application of DL to cyberbullying detection problems within Arabic text classification can be considered a novel approach due to the complexity of the problem and the tedious process involved, besides the scarcity of relevant research studies.…”
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A neuro-heuristic approach for segmenting handwritten Arabic text. (c2001)
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Topics in graph algorithms
Published 2003“…This is a notable improvement over the previous best known algorithm, which runs in O(8kn). In addition to the structural and algorithmic results, this text tries to illustrate the practicality of fixed-parameter algorithms. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis
Published 2023“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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A feature‐based approach for guiding the selection of Internet of Things cybersecurity standards using text mining
Published 2021“…Second, an up-to-date overview of the IoT cybersecurity standards landscape has been mapped by combining existing overviews. Third, a text mining algorithm has been implemented. Fourth, the systematic approach has been modeled using business process modeling notation. …”
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Fast Text Classification using Lean Gradient Descent Feed Forward Neural Network for Category Feature Augmentation
Published 2024“…Text classification is a key task of the Natural Language Processing (NLP) field that aims at assigning predefined categories to textual documents. …”
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A hybrid graph representation for recursive backtracking algorithms
Published 2017“…The performance of these algorithms often suffers from the increasing number of graph modifications, such as deletions, that reduce the problem instance and have to be “taken back” frequently during the search process. …”
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