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Data Analysis Expressions (DAX) is the native formula and query language for Microsoft PowerPivot, Power BI Desktop and SQL Server Analysis Services (SSAS) Tabular models. DAX includes some of the functions that are used in Excel formulas with additional functions that are designed to work with relational data and perform dynamic aggregation.
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).
In information retrieval, Okapi BM25 (BM is an abbreviation of best matching) is a ranking function used by search engines to estimate the relevance of documents to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson , Karen Spärck Jones , and others.
It can edit and format text in cells, calculate formulas, search within the spreadsheet, sort rows and columns, freeze panes, filter the columns, add comments, and create charts. It cannot add columns or rows except at the edge of the document, rearrange columns or rows, delete rows or columns, or add spreadsheet tabs.
The TM, in effect, "proposes" the match to the translator; it is then up to the translator to accept this proposal or to edit this proposal to more fully equate with the new source text that is undergoing translation. In this way, fuzzy matching can speed up the translation process and lead to increased productivity.
(empty set) ∅ denoting the set ∅. (empty string) ε denoting the set containing only the "empty" string, which has no characters at all. (literal character) a in Σ denoting the set containing only the character a. Given regular expressions R and S, the following operations over them are defined to produce regular expressions:
Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned).
The AMQ filter functions as a proxy to the set of keys of a database or remote memory. Before a presumably slow query to the database or to remote memory is performed, the AMQ filter is used to give an approximate answer as to whether the key is in the database or in remote memory. The slow query is only performed when the AMQ filter returns true.