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Text Analysis Within a Full-Text Search Engine

Full-Text Search refers to techniques for searching text content within a document or a collection of documents that hold textual content. A Full-Text search engine examines all the textual content within documents as it tries to match a single search term or several terms, text analysis being a pivotal component.

You’ve probably heard of the most well-known Full-Text Search engine: Lucene with Elasticsearch built on top of it. Couchbase’s Full-Text Search (FTS) Engine is powered by Bleve, and this article will showcase the various ways to analyze text within this engine.

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8 Ways to Customize Couchbase Full Text Search Indexes

Couchbase Search service supports the creation of special purpose indexes for Full Text Search to provide extensive capabilities for natural language querying on JSON documents. Couchbase Full Text Search indexes support an extensive range of query types, like:

  • Match, Match Phrase, Doc ID, and Prefix queries
  • Conjunction, Disjunction, and Boolean field queries
  • Numeric Range and Date Range queries
  • Geospatial queries
  • Query String queries, which employ a special syntax to express the details of each query

To perform a full text search, a Full Text Search Index has to be created first upon a bucket on which the search has to be targeted. The search could be performed on the textual and other contents of documents within a specified bucket.