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It provides a bit more flexibility by including variations and additional terms within the search query. This match type covers search terms that include your targeted keyword phrase, along with other words before or after it. When a shopper searches for a keyword phrase containing your targeted phrase and other terms, your ad may appear.
The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: [1] insertion: cot → coat; deletion: coat → cot; substitution: coat → cost
matches the entire line (because the entire line begins and ends with a double-quote) instead of matching only the first part, "Ganymede,". The aforementioned quantifiers may, however, be made lazy or minimal or reluctant , matching as few characters as possible, by appending a question mark: ".+?"
Google Sheets is a spreadsheet application and part of the free, web-based Google Docs Editors suite offered by Google. Google Sheets is available as a web application; a mobile app for: Android, iOS, and as a desktop application on Google's ChromeOS. The app is compatible with Microsoft Excel file formats. [5]
A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.
When an exact match cannot be found in the TM database for the text being translated, there is an option to search for a match that is less than exact; the translator sets the threshold of the fuzzy match to a percentage value less than 100%, and the database will then return any matches in its memory corresponding to that percentage.
Radius matching: all matches within a particular radius are used -- and reused between treatment units. Kernel matching: same as radius matching, except control observations are weighted as a function of the distance between the treatment observation's propensity score and control match propensity score. One example is the Epanechnikov kernel.
A maximal unique match or MUM, for short, is part of a key step [1] in the multiple sequence alignment of genomes in computational biology. Identification of MUMs and other potential anchors is the first step in larger alignment systems such as MUMmer. Anchors are the areas between two genomes where they are highly similar.