What is meant by Full text search?

The term "full-text search" refers to a search function that enables the scanning of entire documents, databases, or text collections for any keywords or phrases. Unlike a basic keyword search, full-text search analyzes all textual content, including within documents, data fields, or unstructured text. Modern full-text search systems typically use indexing techniques and relevance algorithms to deliver fast and precise search results.

Typical software functions in the area of "full-text search":

Indexing: Automatic capture and structural preparation of text content for rapid searching.
Relevance Ranking: Weighting and sorting of search results based on their relevance to the search query.
Search Suggestions (Auto-Suggest): Displaying relevant terms or phrases during input.
Faceted Search: Filtering results by specific categories, data fields, or metadata.
Synonym Recognition: Including semantically similar terms to broaden the search scope.
Fuzzy Search: Detection and correction of typos or similar spellings.
Highlighting: Emphasizing occurrences of search terms in the result content.
Multilingual Search: Support for searching across multiple languages, including translation capabilities.
Search History & Personalization: Using previous queries to improve future search results.

Examples of "full-text search":

An employee searches the intranet for a specific passage within a PDF document.
A customer finds a product on an e-commerce platform by entering a description instead of a product name.
A legal software application automatically searches relevant rulings and legal texts for a specific term.
A CRM system offers global full-text search across all contact notes, emails, and activities.
A knowledge management system instantly retrieves matching articles and documents from various sources in response to a query.