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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 CBOW can be viewed as a ‘fill in the blank’ task, where the word embedding represents the way the word influences the relative probabilities of other words in the context window. Words which are semantically similar should influence these probabilities in similar ways, because semantically similar words should be used in similar contexts.
An alternative direction is to aggregate word embeddings, such as those returned by Word2vec, into sentence embeddings. The most straightforward approach is to simply compute the average of word vectors, known as continuous bag-of-words (CBOW). [9] However, more elaborate solutions based on word vector quantization have also been proposed.
In computing, the term text processing refers to the theory and practice of automating the creation or manipulation of electronic text.Text usually refers to all the alphanumeric characters specified on the keyboard of the person engaging the practice, but in general text means the abstraction layer immediately above the standard character encoding of the target text.
Here are some commonly used embedding models: Word2Vec: [4] Word2Vec is a popular embedding model used in natural language processing (NLP). It learns word embeddings by training a neural network on a large corpus of text. Word2Vec captures semantic and syntactic relationships between words, allowing for meaningful computations like word analogies.
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.
A word processor (WP) [1] [2] is a device or computer program that provides for input, editing, formatting, and output of text, often with some additional features.. Early word processors were stand-alone devices dedicated to the function, but current word processors are word processor programs running on general purpose computers.
For example, a desktop publishing system might send some text to a word processor or a picture to a bitmap editor using OLE. [1] The main benefit of OLE is to add different kinds of data to a document from different applications, like a text editor and an image editor.