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A common alternative to using dictionaries is the hashing trick, where words are mapped directly to indices with a hashing function. [5] Thus, no memory is required to store a dictionary. Hash collisions are typically dealt via freed-up memory to increase the number of hash buckets [clarification needed]. In practice, hashing simplifies the ...
The original models were: Milton Erickson (hypnotherapy), Virginia Satir (family therapy), and Fritz Perls (gestalt therapy). NLP modeling methods are designed to unconsciously assimilate the tacit knowledge to learn what the master is doing of which the master is not aware. As an approach to learning it can involve modeling exceptional people. [7]
For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...
During the deep learning era, attention mechanism was developed to solve similar problems in encoding-decoding. [1] In machine translation, the seq2seq model, as it was proposed in 2014, [24] would encode an input text into a fixed-length vector, which would then be decoded into an output text. If the input text is long, the fixed-length vector ...
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
The models that constitute NLP are all formal models based on mathematical, logical principles such as predicate calculus and the mathematical equations underlying holography." [26] There is no mention of the mathematics of holography nor of holography in general in Spitzer's, [20] or Grinder's [27] account of the development of NLP.
Paraphrase or paraphrasing in computational linguistics is the natural language processing task of detecting and generating paraphrases.Applications of paraphrasing are varied including information retrieval, question answering, text summarization, and plagiarism detection. [1]
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.