2023:Word Match (Value Extractor): Difference between revisions

Revision as of 10:36, 6 December 2023

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The Word Match is an Extractor Type found in Grooper. This extractor is designed to collect full words and is often used in n-gram extraction.

About

The Word Match extractor is designed for n-gram extraction. An n-gram is "a contiguous sequence of n items from a given sample of text or speech." [1] Typically in Grooper, this refers to extracting words or phrases from a lexicon of terms.

Grooper generally uses n-grams for the purpose of feature collection for Lexical Classification. The Word Match extractor can capture 1-grams (single words) up to 5-grams (five word phrases). Lexicons are commonly used to dictate a dictionary of allowable returned words. This could be general Lexicon of common English words or a custom Lexicon, such as one with industry specific terms.

FYI

An n-gram is often referred to by a different name depending its n size.

1-grams (single words) - unigrams

2-grams (word pairs) - bigrams

3-grams (three word phrases) - trigrams

4-grams (four word phrases) - four-grams

5-grams (five word phrases) - five-grams

As an additional FYI, four-grams are not called "tetragrams" because the term already has usage as a single word consisting of four letters or characters. "Quadrigram" is occasionally used, but four-gram is the more common terminology. Five-grams are not called "pentagrams", because that already has common usage for a geometric figure.

How To

First, let's set the Word Match extractor on a Data Type.

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-=== Word Match ===
+<blockquote>
+The '''''Word Match''''' is an '''''Extractor Type''''' found in Grooper. This extractor is designed to collect full words and is often used in n-gram extraction.
+</blockquote>
+== About ==
+The ''Word Match'' extractor is designed for n-gram extraction.  An n-gram is "a contiguous sequence of n items from a given sample of text or speech." [https://en.wikipedia.org/wiki/N-gram]  Typically in Grooper, this refers to extracting words or phrases from a lexicon of terms.
+Grooper generally uses n-grams for the purpose of feature collection for Lexical Classification.  The ''Word Match'' extractor can capture 1-grams (single words) up to 5-grams (five word phrases).  '''''Lexicons''''' are commonly used to dictate a dictionary of allowable returned words.  This could be general '''Lexicon''' of common English words or a custom '''Lexicon''', such as one with industry specific terms.
-The ''Word Match'' extractor is designed for n-gram extraction.  An n-gram is "a contiguous sequence of n items from a given sample of text or speech." [https://en.wikipedia.org/wiki/N-gram]  Typically in Grooper, this refers to extracting words or phrases from a lexicon of terms.  Often, this is for the purposes of feature collection for ''[[Lexical]]'' [[Classification]].  The ''Word Match'' extractor can capture 1-grams (single words) up to 5-grams (five word phrases).  '''''Lexicons''''' are commonly used to dictate a dictionary of allowable returned words.  This could be general '''Lexicon''' of common English words or a custom '''Lexicon''', such as one with industry specific terms.
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-Just like with ''Pattern Match'', you can enter '''''Prefix''''' and '''''Suffix Patterns''''' to only return an n-gram if a regex pattern ''also'' matches before or after.  These are useful for anchoring the n-gram you want to return next to some other piece of text.  For example, a '''''Prefix Pattern''''' of <code>\n</code> could be used to ''only'' return n-grams at the start of a new line because the <code>\n</code> character precedes every new line in the text data.  Furthermore, ''only'' the n-gram is returned, not the text matched by the '''''Prefix''''' and '''''Suffix Patterns'''''.
+== How To ==
+First, let's set the ''Word Match'' extractor on a '''Data Type'''.
+[[File:2023 Word Match - 2023 01 How To 01 Setup 01.png]]
+[[File:2023 Word Match - 2023 01 How To 01 Setup 02.png]]
+[[File:2023 Word Match - 2023 01 How To 01 Setup 03.png]]
+<!--
+You can enter '''''Prefix''''' and '''''Suffix Patterns''''' to only return an n-gram if a regex pattern ''also'' matches before or after.  These are useful for anchoring the n-gram you want to return next to some other piece of text.  For example, a '''''Prefix Pattern''''' of <code>\n</code> could be used to ''only'' return n-grams at the start of a new line because the <code>\n</code> character precedes every new line in the text data.  Furthermore, ''only'' the n-gram is returned, not the text matched by the '''''Prefix''''' and '''''Suffix Patterns'''''.
 The '''''Join Pattern''''' property is unique to the ''Word Match'' extractor.  This determines how terms of bigrams, trigrams, four-grams, and five-grams can be joined.  Most often, terms (or grams) are simply joined by a single space, as in the bigram "''first second''".  If you leave this property blank, Grooper will assume n-grams are always separated by a single space.  However, you may want to include n-grams that are separated by other characters.  For example hyphenated words, as in "''first-second''".  The '''''Join Pattern''''' allows you to enter a regular expression for the allowable characters between two grams.  For example, a '''''Join Pattern''''' of <code>[ -]</code> would allow for a single space or hyphen to be between each term, matching "''first second''" as well as "''first-second''".
 The '''''Output Format''''' allows you to alter the output result for data cleansing or other purposes.
-The "Properties" tab allows you to further configure the n-gram matching.  Most importantly, the n-gram size is set here as well as any '''Lexicon''' used to lookup against the returned values.  You can also enable [[Tab Marking]], [[Fuzzy RegEx]] mode, filter results based on page location, determine case sensitivity, and more.
+The "Properties" tab allows you to further configure the n-gram matching.  Most importantly, the n-gram size is set here as well as any '''Lexicon''' used to lookup against the returned values.  You can also enable Tab Marking, Fuzzy RegEx mode, filter results based on page location, determine case sensitivity, and more.
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