Search engine

A software system that finds and ranks information matching a query in an indexed collection, such as web pages or documents.

Web crawler: A program that automatically discovers and fetches pages or other resources on the web. Crawlers gather web pages that a search engine can analyze and index.
Tokenization: The process of dividing text into units such as words, subwords, or symbols. Search engines tokenize documents and queries before matching their terms.
Web search engine: A search engine that indexes and retrieves resources from the World Wide Web. It is the most familiar application of search-engine technology.
Web directory: A curated collection of web resources organized into categories and subcategories. Unlike a search engine, it relies primarily on human-organized browsing rather than query-time retrieval.
Inverted index: A data structure mapping terms to the documents in which they appear. It lets search engines find candidate documents without scanning every page.
Term frequency–inverse document frequency: A weighting scheme that scores terms using their frequency in a document and rarity across a collection. It offers a classic way to estimate how informative a query term is in a page.
Desktop search: Software that indexes files and content stored on a personal computer for retrieval. It applies indexing and query matching to local files rather than the open web.
Database query language: A formal language for requesting or modifying data in a structured database. Database queries target defined fields and rules, unlike broad relevance-ranked document search.
Information retrieval: The field concerned with finding relevant information in collections of documents. Search engines are practical systems built from information-retrieval methods.
Vector space model: A representation of documents and queries as vectors whose similarity can estimate their relevance. It turns textual matching into a computable comparison between query and document.

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