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In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]
The reasons for successful word embedding learning in the word2vec framework are poorly understood. Goldberg and Levy point out that the word2vec objective function causes words that occur in similar contexts to have similar embeddings (as measured by cosine similarity) and note that this is in line with J. R. Firth's distributional hypothesis ...
word choice/wrong word: Incorrect or awkward word choice hr # Insert hair space: s/b: should be: Selection should be whatever edit follows this mark s/r: substitute/replace: Make the substitution tr: transpose: Transpose the two words selected vf: verb form (Mostly used when translating) The version of the verb is used incorrectly e: ending
In practice however, BERT's sentence embedding with the [CLS] token achieves poor performance, often worse than simply averaging non-contextual word embeddings. SBERT later achieved superior sentence embedding performance [8] by fine tuning BERT's [CLS] token embeddings through the usage of a siamese neural network architecture on the SNLI dataset.
An embedding, or a smooth embedding, is defined to be an immersion that is an embedding in the topological sense mentioned above (i.e. homeomorphism onto its image). [4] In other words, the domain of an embedding is diffeomorphic to its image, and in particular the image of an embedding must be a submanifold.
A separate invisible hot area interface allows for swapping skins or labels within the linked hot areas without repetitive embedding of links in the various skin elements. Text hyperlink. Hyperlink is embedded into a word or a phrase and makes this text clickable. Image hyperlink. Hyperlink is embedded into an image and makes this image clickable.
Font embedding is the inclusion of font files inside an electronic document for display across different platforms.
In linguistics, center embedding is the process of embedding a phrase in the middle of another phrase of the same type. This often leads to difficulty with parsing which would be difficult to explain on grammatical grounds alone. The most frequently used example involves embedding a relative clause inside another one as in: