Results 1 to 10 of about 13,021 (237)
The Spectral Underpinning of word2vec [PDF]
Frontiers in Applied Mathematics and Statistics, 2020 Word2vec introduced by Mikolov et al. is a word embedding method that is widely used in natural language processing. Despite its success and frequent use, a strong theoretical justification is still lacking.
Yuval Kluger +2 more
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Word2Vec: Optimal hyperparameters and their impact on natural language processing downstream tasks
Open Computer Science, 2022 Word2Vec is a prominent model for natural language processing tasks. Similar inspiration is found in distributed embeddings (word-vectors) in recent state-of-the-art deep neural networks.
Tosin Adewumi, Marcus Liwicki
exaly +2 more sources
Central Kurdish Sentiment Analysis Using Deep Learning [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2022 Sentiment Analysis (SA) as a type of opinion mining and as a more general topic than polarity detection, is widely used for analyzing user's reviews or comments of online expressions, which is implemented using various techniques among which the ...
Kozhin Awlla, Hadi Veisi
doaj +1 more source
Subjective Answers Evaluation Using Machine Learning and Natural Language Processing
IEEE Access, 2021 Subjective paper evaluation is a tricky and tiresome task to do by manual labor. Insufficient understanding and acceptance of data are crucial challenges while analyzing subjective papers using Artificial Intelligence (AI).
Muhammad Farrukh Bashir +4 more
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Prediction of Piwi-Interacting RNAs and Their Functions via Convolutional Neural Network
IEEE Access, 2021 In eukaryotic cells, Piwi-interacting RNAs (piRNAs) are the type of short chain non-coding RNA molecules, which interconnect with PIWI proteins. It performs various cellular and genetic functions such as gene-specific protein translation, expression ...
Muhammad Tahir +3 more
doaj +1 more source
Frontiers in Genetics, 2023 Neuropeptides contain more chemical information than other classical neurotransmitters and have multiple receptor recognition sites. These characteristics allow neuropeptides to have a correspondingly higher selectivity for nerve receptors and fewer side
Di Liu, Zhengkui Lin, Cangzhi Jia
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Unstructured Text Documents Summarization With Multi-Stage Clustering
IEEE Access, 2020 In natural language processing, text summarization is an important application used to extract desired information by reducing large text. Existing studies use keyword-based algorithms for grouping text, which do not give the documents' actual theme. Our
Muhammad Yahya Saeed +3 more
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Study on Title Encoding Methods for e-Commerce Downstream Tasks
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 In an e-Commerce marketplace there are usually many downstream tasks which have (relatively) less available resources than the few mainstream priority tasks, like recommendation or search.
Cristian Cardellino, Rafael Carrascosa
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Large scale text mining for deriving useful insights: A case study focused on microbiome
Frontiers in Physiology, 2022 Text mining has been shown to be an auxiliary but key driver for modeling, data harmonization, and interpretation in bio-medicine. Scientific literature holds a wealth of information and embodies cumulative knowledge and remains the core basis on which ...
Syed Ashif Jardary Al Ahmed +8 more
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Information, 2020 The ability to stop malware as soon as they start spreading will always play an important role in defending computer systems. It must be a huge benefit for organizations as well as society if intelligent defense systems could themselves detect and ...
Kien Tran, Hiroshi Sato, Masao Kubo
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