One technique for improving retrieval effectiveness and reducing the size of indexing files is to provide searchers with ways of finding morphological variants of search terms. If, for example, a searcher enters the term stemming as part of a query, it is likely that he or she will also be interested in such variants as stemmed and stem. Since a single stem typically corresponds to several full terms, by storing stems instead of terms, compression factors of over 50 percent can be achieved.
Stemming/conflation is the process for reducing inflected (or sometimes derived) words to their stem, base or root form—generally a written word form.The stem need not be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem, even if this stem is not in itself a valid root.
| Stemming can be either manual—using regular expressions—or automatic via stemmers. The figure shows a taxonomy for stemming algorithms including four automatic approaches: |
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- Table lookup, where stemming is done via lookups in the table because terms and their corresponding stems can also be stored in a table,
- N-gram method, which conflates terms based on the number of digrams or n-grams they share,
- Successor variety stemmers, which use the frequencies of letter sequences in a body of text as the basis of stemming, and
- Affix removal algorithms, which remove suffixes and/or prefixes from terms leaving a stem.
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My uncle is very sick and has one foot in the grave (near death). |