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n-Gram-Based Text Compression [PDF]
Computational Intelligence and Neuroscience, 2016 We propose an efficient method for compressing Vietnamese text usingn-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it inton-grams and then encodes them based onn-gram dictionaries.
Vu H. Nguyen +3 more
europepmc +8 more sources
N-gram MalGAN: Evading machine learning detection via feature n-gram
Digital Communications and Networks, 2022 In recent years, many adversarial malware examples with different feature strategies, especially GAN and its variants, have been introduced to handle the security threats, e.g., evading the detection of machine learning detectors. However, these solutions still suffer from problems of complicated deployment or long running time.
Enmin Zhu +4 more
openaire +3 more sources
Rapid Text Entry Using Mobile and Auxiliary Devices for People with Speech Disorders Communication [PDF]
International Journal of Electronics and Telecommunications, 2020 The article considers information technology for the realization of human communication using residual human capabilities, obtained by organizing text entry using mobile and auxiliary devices.
Iurii V. Krak +5 more
doaj +1 more source
Political Arabic Articles Orientation Using Rough Set Theory With Sentiment Lexicon
IEEE Access, 2021 Sentiment analysis is an emerging research field that can be integrated with other domains, including data mining, natural language processing and machine learning.
Jwan K. Alwan +5 more
doaj +1 more source
Simultaneous Removal of Prefix and Suffix [PDF]
Vietnam Journal of Computer Science, 2020 This work is an attempt to devise a Stemmer that can remove both prefix and suffix together from a given word in English language. For a given input word, our method considers all possible internal N-grams for detection of potential stems.
Pawan Tamta, B. P. Pande
doaj +1 more source
N-gram and Kernel Performance Using Support Vector Machine Algorithm for Fake News Detection System
Ilkom Jurnal Ilmiah, 2023 The modern technological advancements have made it simpler for fake news to circulate online. The researchers have developed several strategies to overcome this obstacle, including text classification, distribution network analysis, and human-machine ...
Deny Jollyta +3 more
doaj +1 more source
Proceedings of the 17th international conference on Computational linguistics -, 1998 It seems obvious that a successful model of natural language would incorporate a great deal of both linguistic and world knowledge. Interestingly, state of the art language models for speech recognition are based on a very crude linguistic model, namely conditioning the probability of a word on a small fixed number of preceding words.
Eric Brill +3 more
openaire +1 more source
N-gram models for Text Generation in Hindi Language [PDF]
ITM Web of Conferences, 2022 Native language plays a vital role for communication. Hindi is preferred by most Indians and it is the fifth most spoken language in the world. Hence, to make User Experience more effective while interacting with Software Applications, we aim to build a ...
Ghude Tejashree +4 more
doaj +1 more source
Similarity Identification Based on Word Trigrams Using Exact String Matching Algorithms
Intensif: Jurnal Ilmiah Penelitian Teknologi dan Penerapan Sistem Informasi, 2022 Several studies regarding excellent exact string matching algorithms can be used to identify similarity, including the Rabin-Karp, Winnowing, and Horspool Boyer-Moore algorithms.
Abdul Fadlil +2 more
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Semantic N-Gram Topic Modeling [PDF]
EAI Endorsed Transactions on Scalable Information Systems, 2020 In this paper a novel approach for effective topic modeling is presented. The approach is different fromtraditional vector space model-based topic modeling, where the Bag of Words (BOW) approach is followed.The novelty of our approach is that in phrase ...
Pooja Kherwa, Poonam Bansal
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