Ngram intro - Elasticsearch 权威指南中文版


Ngram intro

发布于 2019-07-04 字数 2039 浏览 932 评论 0

=== Ngrams for Partial Matching

As we have said before, `You can find only terms that exist in the inverted index.'' Although theprefix,wildcard, andregexp` queries demonstrated that
that is not strictly true, it is true that doing a single-term lookup is
much faster than iterating through the terms list to find matching terms on
the fly.(((“partial matching”, “index time optimizations”, “n-grams”))) Preparing your data for partial matching ahead of time will increase
your search performance.

Preparing your data at index time means choosing the right analysis chain, and
the tool that we use for partial matching is the n-gram.(((“n-grams”))) An n-gram can be
best thought of as a moving window on a word. The n stands for a length.
If we were to n-gram the word quick, the results would depend on the length
we have chosen:


  • Length 1 (unigram): [ q, u, i, c, k ]
  • Length 2 (bigram): [ qu, ui, ic, ck ]
  • Length 3 (trigram): [ qui, uic, ick ]
  • Length 4 (four-gram): [ quic, uick ]
  • Length 5 (five-gram): [ quick ]

Plain n-grams are useful for matching somewhere within a word, a technique
that we will use in <>. However, for search-as-you-type,
we use a specialized form of n-grams called edge n-grams. (((“edge n-grams”))) Edge
n-grams are anchored to the beginning of the word. Edge n-gramming the word
quick would result in this:

  • q
  • qu
  • qui
  • quic
  • quick

You may notice that this conforms exactly to the letters that a user searching for “quick” would type. In other words, these are the
perfect terms to use for instant search!

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