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There are some issues arise in recommender systems which they need a lot of data to efficiently build recommendations. Large amount of items and user data are best for getting good recommendations. ... This paper presents the case study of Netflix and other case studies in the development of recommendation system and analyzes some of the problems and challenges in implementing recommender systems. ... A. L. Garrido et al.  developed a mobile phone application by implementing Knowledge-based Geographical News Recommender (KGNR) approach. ...fatcat:abf4hsdeqfa5pbeid4asw6ld2i
An empirical discriminant function based on relative basin area and a surrogate measure of distal tributary stream power is particularly successful, although its general applicability cannot be assessed ... A corresponding logistic model estimates the probability that a given tributary is associated with a textural discontinuity. ... This relation does not add new insight (it is based on the same empirical data used to define the discriminant function) but rather provides an assessment of the uncertainty associated with a given categorisation ...doi:10.14288/1.0087248 fatcat:nefophwfpvhfpcbxv45k5jbo5a