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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 ...
In computer science, an associative array, map, symbol table, or dictionary is an abstract data type that stores a collection of (key, value) pairs, such that each possible key appears at most once in the collection. In mathematical terms, an associative array is a function with finite domain. [1] It supports 'lookup', 'remove', and 'insert ...
William Whitaker's Words is a computer program that parses the inflection or conjugation of a given Latin word entered by the user, and also translates the root into English. . Conversely, given a basic English word, the program can output a Latin translation, generally with several possible Latin alternatives, although the database of translatable English words is not comprehen
The clock is ticking for families hoping to send letters to Santa Claus at the North Pole this holiday season.. Letters need to be postmarked by Monday, a spokesperson for the U. S. Postal Service ...
A Florida man was taken into custody on Monday after being accused of stabbing a delivery driver in Fort Lauderdale, Florida, earlier this month, according to police.
(Reuters) -GameStop's shares jumped on Thursday after a cryptic post from meme stock influencer Keith Gill, who shot to notoriety after his online personas and bullish bets on the video game ...
For example, one could define a dictionary having a string "toast" mapped to the integer 42 or vice versa. The keys in a dictionary must be of an immutable Python type, such as an integer or a string, because under the hood they are implemented via a hash function. This makes for much faster lookup times, but requires keys not change.
In applied mathematics, k-SVD is a dictionary learning algorithm for creating a dictionary for sparse representations, via a singular value decomposition approach. k-SVD is a generalization of the k-means clustering method, and it works by iteratively alternating between sparse coding the input data based on the current dictionary, and updating the atoms in the dictionary to better fit the data.