Development of a Movie Selection System

2019;
: pp. 53 - 58
1
Lviv Polytechnic National University
2
Lviv Polytechnic National University
3
Lviv Polytechnic National University

The recommendation system for content-based movie search has been developed. Used Mongo DB database and utilities with machine learning elements to speed up the search. Using the developed system will save time when selecting movies by certain criteria.

  1. Kh. Chen, L. Hou, Kh. Chzhan, K. Dzhails Spivrobitnyk: poshukova systema dlia vidkryttia spivpratsi v spilnii konferentsii ACM / IEEE z tsyfrovykh bibliotek (JCDL) 2011.
  2. “Facebook, Pandora Lead Rise of Recommendation Engines – TIME”. TIME.com. 27 May 2010. Retrieved 1 June 2015.
  3. Elakhi, Mekhdi; Richchi, Franchesko; Rubens, Nil (2016). “Ohliad aktyvnoho navchannia v systemakh rekomendatsii spilnoi filtratsii”. Ohliad kompiuternykh nauk. 20: 29–50. doi: 10.1016 / j.cosrev.2016.05.002.
  4. Herlocker, J. L.; Konstan, J. A.; Terveen, L. G.; Riedl, J. T. (sichen 2004). "Otsiniuvannia system rekomendatsii spilnoi filtratsii". ACM Trans. Inf. Syst. 22 (1): 5–53.
  5. Dzhon S. Briz; Devid Khekkerman i Karl Kadi (1998). Empirychnyi analiz alhorytmiv prohnozuvannia dlia spilnoi filtratsii. V dopovidiakh chotyrnadtsiatoi konferentsii «Nevyznachenist u shtuchnomu intelekti» (UAI98).
  6. R. J. Mooney & L. Roy (1999). Content-based book recommendation using learning for text categorization. In Workshop Recom. Sys.: Algo. and Evaluation.