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  2. Elasticsearch - Wikipedia

    en.wikipedia.org/wiki/Elasticsearch

    Elasticsearch is a search engine based on Apache Lucene. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. Official clients are available in Java, [2].NET [3] , PHP, [4] Python, [5] Ruby [6] and many other languages. [7]

  3. Apache Lucene - Wikipedia

    en.wikipedia.org/wiki/Apache_Lucene

    Apache Solr – an enterprise search server; CrateDB – open source, distributed SQL database built on Lucene [15] DocFetcher – a multiplatform desktop search application [citation needed] Elasticsearch – an enterprise search server released in 2010 [16] [17] Kinosearch – a search engine written in Perl and C [18] and a loose port of ...

  4. Full-text search - Wikipedia

    en.wikipedia.org/wiki/Full-text_search

    In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references).

  5. List of search engines - Wikipedia

    en.wikipedia.org/wiki/List_of_search_engines

    Desktop search product with Outlook plugin and limited support for other formats via IFilters, uses Lucene search engine. Proprietary (14-day trial) [7] Nepomuk: Linux: Open-source semantic desktop search tool for Linux. Has been replaced by Baloo in KDE Applications from release 4.13 onward. License SA 3.0 and the GNU Free Documentation ...

  6. Inverted index - Wikipedia

    en.wikipedia.org/wiki/Inverted_index

    The purpose of an inverted index is to allow fast full-text searches, at a cost of increased processing when a document is added to the database. [2] The inverted file may be the database file itself, rather than its index. It is the most popular data structure used in document retrieval systems, [3] used on a large scale for example in search ...

  7. Okapi BM25 - Wikipedia

    en.wikipedia.org/wiki/Okapi_BM25

    In information retrieval, Okapi BM25 (BM is an abbreviation of best matching) is a ranking function used by search engines to estimate the relevance of documents to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson , Karen Spärck Jones , and others.

  8. ‘The Crossing’ by Huffington Post

    testkitchen.huffingtonpost.com/thecrossing

    Watch firsthand, in 360 video, as Susan Sarandon listens and learns about refugees' hopes, dreams and journeys

  9. Apache Solr - Wikipedia

    en.wikipedia.org/wiki/Apache_Solr

    Its major features include full-text search, hit highlighting, faceted search, real-time indexing, dynamic clustering, database integration, NoSQL features [2] and rich document (e.g., Word, PDF) handling. Providing distributed search and index replication, Solr is designed for scalability and fault tolerance. [3]