One who recompenses.
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A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym
The British Army is the principal land warfare force of the United Kingdom, a part of British Armed Forces. As of 2019, the British Army comprises just over 79,300 trained regular (full-time) personnel and just over 27,200 trained reserve (part-time) personnel.
The Soothsayer's Recompense
The Soothsayers Recompense is a 1913 painting by the Italian artist Giorgio de Chirico
Royal Medal of Recompense
The Royal Medal of Recompense (Danish: Den Kongelige Belønningsmedalje) is a Danish medal
Knowledge-based recommender system
Knowledge-based recommender systems (knowledge based recommenders) are a specific type
The Sansculottides (French pronunciation: [sɑ̃kylɔtid]; also Epagomènes; French Sans-culottides, Sanculottides, jours complémentaires, jours épagomènes) are holidays following the last month of the year on the French Republican Calendar which was used following the French Revolution from approximately 1793 to 1805. The Sansculottides belong to the summer quarter. They begin on 17 or 18 September and approximately end on the autumn equinox, on 22 or 23 September on the Gregorian calendar.
Per il gusto di uccidere
Per il gusto di uccidere (internationally released as Taste for Killing, Lanky Fellow and For the Taste of Killing and originally titled as Cacciatore di taglie) is the 1966 Italian Spaghetti Western film debut directed by Tonino Valerii. It is also the first film to use the camera system known as 2P. It was filmed in Almería. It is produced by Francesco Genesi, Vincenzo Genesi, Daniele Senatore, Stefano Melpignano and Jose Lopez Moreno, scored by Nico Massi and edited by Rosa G. Salgado.
Recompense is a lost 1925 American drama film directed by Harry Beaumont and written by Dorothy
Cold start (recommender systems)
Cold start is a potential problem in computer-based information systems which involve a degree of automated data modelling. Specifically, it concerns the issue that the system cannot draw any inferences for users or items about which it has not yet gathered sufficient information.