Retrospective and Conclusions In hindsight, certain outcomes seem obvious. Especially given modern systems languages like Go and Rust.
Examples[ edit ] A stemmer for English operating on the stem cat should identify such strings as cats, catlike, and catty. A stemming algorithm might also reduce the words fishing, fished, and fisher to the stem fish.
The stem need not be a word, however. In the Porter algorithm, argue, argued, argues, arguing, and argus reduce to the stem argu.
History[ edit ] The first published stemmer was written by Julie Beth Lovins in A later stemmer was written by Martin Porter and was published in the July issue of the journal Program. This stemmer was very widely used and became the de facto standard algorithm used for English stemming.
Porter received the Tony Kent Strix award in for his work on stemming and information retrieval. Many implementations of the Porter stemming algorithm were written and freely distributed; however, many of these implementations contained subtle flaws.
As a result, these stemmers did not match their potential. To eliminate this source of error, Martin Porter released an official free software mostly BSD -licensed implementation  of the algorithm around the year He extended this work over the next few years by building Snowballa framework for writing stemming algorithms, and implemented an improved English stemmer together with stemmers for several other languages.
Algorithms[ edit ] There are several types of stemming algorithms which differ in respect to performance and accuracy and how certain stemming obstacles are overcome. A simple stemmer looks up the inflected form in a lookup table.
The advantages of this approach are that it is simple, fast, and easily handles exceptions. The disadvantages are that all inflected forms must be explicitly listed in the table: For languages with simple morphology, like English, table sizes are modest, but highly inflected languages like Turkish may have hundreds of potential inflected forms for each root.
A lookup approach may use preliminary part-of-speech tagging to avoid overstemming. For example, if the word is "run", then the inverted algorithm might automatically generate the forms "running", "runs", "runned", and "runly".
The last two forms are valid constructions, but they are unlikely. Suffix-stripping algorithms[ edit ] Suffix stripping algorithms do not rely on a lookup table that consists of inflected forms and root form relations.
Instead, a typically smaller list of "rules" is stored which provides a path for the algorithm, given an input word form, to find its root form. Some examples of the rules include:Correct your English writing with benjaminpohle.com - The best grammar checker, sentence checker, punctuation checker, and online spell checker for second language learners.
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