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同义词与词干提取

通过词干提取过滤器和同义词过滤器，让 Elasticsearch 了解词语的变体和等价形式，从而提升全文搜索的召回率。

第 4 / 4 课13 个步骤

同义词与词干提取 是 CoddyKit 上的免费 Elasticsearch & Full Text Search Systems 课时。这是第 4 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Elasticsearch & Full Text Search Systems 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Elasticsearch & Full Text Search Systems 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

Closing the Vocabulary Gap

Users rarely type the exact words stored in your documents. They search running but your text says run, or they type laptop when the doc says notebook. Two analysis techniques bridge this gap: stemming and synonyms.

What Stemming Does

Stemming reduces words to a common root form. running, runs, and ran may all become run. This means a query matches regardless of the grammatical form used.

Algorithmic Stemmers

Elasticsearch ships algorithmic stemmers like porter_stem and the language-aware stemmer filter. They apply rules to strip suffixes quickly without a dictionary.

"filter": {
  "my_stemmer": {
    "type": "stemmer",
    "language": "english"
  }
}

Dictionary Stemmers

Dictionary stemmers such as hunspell use real word lists for more accurate, linguistically correct roots. They are slower and need dictionary files but avoid over-stemming.

Over- and Under-Stemming

Stemming has failure modes:

Over-stemming: unrelated words map to the same root (e.g. universe and university).
Under-stemming: related words fail to share a root.

Use keyword_marker to protect specific words from stemming.

What Synonyms Do

Synonyms map words with the same meaning to each other. Searching tv can match television. They are applied via a synonym token filter in the analyzer chain.

"filter": {
  "my_synonyms": {
    "type": "synonym",
    "synonyms": [ "tv, television", "laptop, notebook" ]
  }
}

Equivalent vs Explicit

Synonym rules come in two styles:

Equivalent (tv, television): all terms are interchangeable.
Explicit (i-pod => ipod, music player): the left maps to the right only.

Index-Time vs Search-Time

Synonyms can be applied when indexing or when searching. Search-time synonyms (via synonym_graph) are preferred because you can update the list without re-indexing the whole corpus.

"filter": {
  "graph_syns": {
    "type": "synonym_graph",
    "synonyms_path": "analysis/synonyms.txt"
  }
}

Multi-Word Synonyms

Multi-word synonyms like ny, new york need the graph-aware synonym_graph filter at search time to be tokenized correctly. The older synonym filter mishandles phrases.

Combining Both

A typical chain applies synonyms first, then stemming, after lowercasing. Order matters: stem after expanding synonyms so all variants get normalized consistently.

"my_analyzer": {
  "tokenizer": "standard",
  "filter": [ "lowercase", "graph_syns", "my_stemmer" ]
}

Testing With _analyze

Always verify your chain with the _analyze API to confirm the produced tokens match your expectations before relying on it in production.

GET my_index/_analyze
{
  "analyzer": "my_analyzer",
  "text": "running televisions"
}

Quick Check

Test your understanding of recall-boosting filters.

在交互式课程中回答

Recap

You learned to widen search recall:

Stemming reduces word forms to a shared root; watch for over/under-stemming.
Synonyms map equivalent terms; equivalent vs explicit rules behave differently.
Prefer synonym_graph at search time for editable, multi-word-safe synonyms.
Verify analyzer output with the _analyze API.

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常见问题解答

「同义词与词干提取」课时是免费的吗？

是的 — 「同义词与词干提取」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Elasticsearch & Full Text Search Systems 课程的其余内容，请升级到 CoddyKit PRO。 Elasticsearch & Full Text Search Systems 课程共包含 4 节课。

「同义词与词干提取」这节课中我会学到什么？

通过词干提取过滤器和同义词过滤器，让 Elasticsearch 了解词语的变体和等价形式，从而提升全文搜索的召回率。你通过在浏览器中直接运行的动手代码来练习 Elasticsearch & Full Text Search Systems，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Elasticsearch & Full Text Search Systems 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Elasticsearch & Full Text Search Systems 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 4 节课，共 4 节。

「同义词与词干提取」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Elasticsearch & Full Text Search Systems 课中编写并运行代码吗？

能。每节 Elasticsearch & Full Text Search Systems 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

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