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e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...
The open source code is developed and hosted on GitHub [11] and a public support forum is maintained on Google Groups [12] and Gitter. [ 13 ] Gensim is commercially supported by the company rare-technologies.com, who also provide student mentorships and academic thesis projects for Gensim via their Student Incubator programme.
Website. fasttext.cc. fastText is a library for learning of word embeddings and text classification created by Facebook 's AI Research (FAIR) lab. [3][4][5][6] The model allows one to create an unsupervised learning or supervised learning algorithm for obtaining vector representations for words. Facebook makes available pretrained models for ...
t. e. Eclipse Deeplearning4j is a programming library written in Java for the Java virtual machine (JVM). [2][3] It is a framework with wide support for deep learning algorithms. [4] Deeplearning4j includes implementations of the restricted Boltzmann machine, deep belief net, deep autoencoder, stacked denoising autoencoder and recursive neural ...
t. e. In natural language processing, a sentence embedding refers to a numeric representation of a sentence in the form of a vector of real numbers which encodes meaningful semantic information. [1][2][3][4][5][6][7] State of the art embeddings are based on the learned hidden layer representation of dedicated sentence transformer models.
Janus is a Roman god usually depicted with two faces, here symbolizing the previously separate Windows and MS-DOS products. [2] Jastro. —. Windows & MS-DOS 6. Combined bundle of Windows 3.1 and MS-DOS 6. Portmanteau of Janus and Astro, the codename of MS-DOS 6. [3] Sparta, Winball.
Vector space model. Vector space model or term vector model is an algebraic model for representing text documents (or more generally, items) as vectors such that the distance between vectors represents the relevance between the documents. It is used in information filtering, information retrieval, indexing and relevancy rankings.
The bag-of-words model (BoW) is a model of text which uses a representation of text that is based on an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly ...