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In the process of encoding, the sender (i.e. encoder) uses verbal (e.g. words, signs, images, video) and non-verbal (e.g. body language, hand gestures, face expressions) symbols for which he or she believes the receiver (that is, the decoder) will understand. The symbols can be words and numbers, images, face expressions, signals and/or actions.
Data can be seen as a random variable:, where appears with probability [=].. Data are encoded by strings (words) over an alphabet.. A code is a function : (or + if the empty string is not part of the alphabet).
Data entry is the process of digitizing data by entering it into a computer system for organization and management purposes. It is a person-based process [ 1 ] and is "one of the important basic" [ 2 ] tasks needed when no machine-readable version of the information is readily available for planned computer-based analysis or processing.
A codec is a computer hardware or software component that encodes or decodes a data stream or signal. [1] [2] [3] Codec is a portmanteau of coder/decoder. [4] In electronic communications, an endec is a device that acts as both an encoder and a decoder on a signal or data stream, [5] and hence is a type of codec. Endec is a portmanteau of ...
More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies [(())] [ (())], where is the number of symbols in a code word, is the coding function, is the number of symbols used to make output codes and is the probability of the source symbol. An entropy coding attempts to ...
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 encoding specificity principle is the general principle that matching the encoding contexts of information at recall assists in the retrieval of episodic memories.It provides a framework for understanding how the conditions present while encoding information relate to memory and recall of that information.
Skip-Thought trains an encoder-decoder structure for the task of neighboring sentences predictions; this has been shown to achieve worse performance than approaches such as InferSent or SBERT. An alternative direction is to aggregate word embeddings, such as those returned by Word2vec , into sentence embeddings.