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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. The word2vec algorithm estimates these representations by modeling text in a large corpus.
Better yet, add data-sort-type=number to the column header. Later editing by other editors will not break numerical sorting. A dash, of any kind, in a blank cell in one of the first 5 cells in a column breaks default numerical sorting of a column. A dash in front of a number does not break numerical sorting.
Shuffling can also be implemented by a sorting algorithm, namely by a random sort: assigning a random number to each element of the list and then sorting based on the random numbers. This is generally not done in practice, however, and there is a well-known simple and efficient algorithm for shuffling: the Fisher–Yates shuffle .
The frequency and location of each word determines the first sorting. [1] The order of the words determines the second sorting. If the two words happen to be found in the same order on a page, that page is boosted again. The number of incoming links. [2] These attributes for a word earn that page a higher score: position in the title
Google Docs is an online word processor and part of the free, web-based Google Docs Editors suite offered by Google. Google Docs is accessible via a web browser as a web-based application and is also available as a mobile app on Android and iOS and as a desktop application on Google's ChromeOS .
The non-conservative packed sorting algorithm of Albers & Hagerup (1997) uses a subroutine, based on Ken Batcher's bitonic sorting network, for merging two sorted sequences of keys that are each short enough to be packed into a single machine word. The input to the packed sorting algorithm, a sequence of items stored one per word, is ...
Other advantages are that one can easily find the first or last elements on the list (most likely to be useful in the case of numerically sorted data), or elements in a given range (useful again in the case of numerical data, and also with alphabetically ordered data when one may be sure of only the first few letters of the sought item or items).
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]