Results 11 to 20 of about 32,474 (200)
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.
Ariel Jaffe +7 more
doaj +4 more sources
Linking GloVe with word2vec [PDF]
, 2014 The Global Vectors for word representation (GloVe), introduced by Jeffrey Pennington et al. is reported to be an efficient and effective method for learning vector representations of words.
Liu, Zhiyuan, Shi, Tianze
core +2 more sources
Fast2Vec, a modified model of FastText that enhances semantic analysis in topic evolution. [PDF]
PeerJ Comput SciBackground Topic modeling approaches, such as latent Dirichlet allocation (LDA) and its successor, the dynamic topic model (DTM), are widely used to identify specific topics by extracting words with similar frequencies from documents.
Pertiwi A, Azhari A, Mulyana S.
europepmc +3 more sources
Considerations about learning Word2Vec [PDF]
The Journal of Supercomputing, 2021 AbstractDespite the large diffusion and use of embedding generated through Word2Vec, there are still many open questions about the reasons for its results and about its real capabilities. In particular, to our knowledge, no author seems to have analysed in detail how learning may be affected by the various choices of hyperparameters.
Giovanni Di Gennaro +2 more
openaire +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
doaj +1 more source
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
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019 The \em word2vec methodology such as Skip-gram and CBOW has seen significant interest in recent years because of its ability to model semantic notions of word similarity and distances in sentences. A related methodology, referred to as \em doc2vec is also able to embed sentences and paragraphs. These methodologies, however, lead to different embeddings
Suhang Wang, Charu Aggarwal, Huan Liu
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Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018 Clustering narrow-domain short texts, such as academic abstracts, is an extremely difficult clustering problem. Firstly, short texts lead to low frequency and sparseness of words, making clustering results highly unstable and inaccurate; Secondly, narrow domain leads to great overlapping of insignificant words and makes it hard to distinguish between ...
Changzhou Li +9 more
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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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