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IWE combines Word2vec with a semantic dictionary mapping technique to tackle the major challenges of information extraction from clinical texts, which include ambiguity of free text narrative style, lexical variations, use of ungrammatical and telegraphic phases, arbitrary ordering of words, and frequent appearance of abbreviations and acronyms ...
Another very simple implementation technique, usable when the keys are restricted to a narrow range, is direct addressing into an array: the value for a given key k is stored at the array cell A[k], or if there is no mapping for k then the cell stores a special sentinel value that indicates the lack of a mapping. This technique is simple and ...
HKDF-Extract takes "input key material" (IKM) such as a shared secret generated using Diffie-Hellman, and an optional salt, and generates a cryptographic key called the PRK ("pseudorandom key"). This acts as a "randomness extractor", taking a potentially non-uniform value of high min-entropy and generating a value indistinguishable from a ...
An associative array stores a set of (key, value) pairs and allows insertion, deletion, and lookup (search), with the constraint of unique keys. In the hash table implementation of associative arrays, an array A {\displaystyle A} of length m {\displaystyle m} is partially filled with n {\displaystyle n} elements, where m ≥ n {\displaystyle m ...
An autoimmune response is prevented by eliminating cells that self-react. For T cells, this occurs in the thymus by testing the cell against an array of self antigens expressed through the function of the autoimmune regulator (AIRE). The immunoglobulin lambda light chain locus contains protein-coding genes that can be lost with its rearrangement.
A fuzzy Mediawiki search for "angry emoticon" has as a suggested result "andré emotions" In computer science, approximate string matching (often colloquially referred to as fuzzy string searching) is the technique of finding strings that match a pattern approximately (rather than exactly).
Sparse dictionary learning (also known as sparse coding or SDL) is a representation learning method which aims to find a sparse representation of the input data in the form of a linear combination of basic elements as well as those basic elements themselves. These elements are called atoms, and they compose a dictionary.
Sparse dictionary learning is a feature learning method where a training example is represented as a linear combination of basis functions and assumed to be a sparse matrix. The method is strongly NP-hard and difficult to solve approximately. [69] A popular heuristic method for sparse dictionary learning is the k-SVD algorithm. Sparse ...