Implementation of agile concepts in recommender systems for data processing and analyses

Abstract

Recommender systems have recently become an essential part of the majority of modern information systems. In the paper recommender systems oriented on supporting data and information processing and analyses are considered. The systems are aimed to give recommendations to end users on selection and usage of data processing methods and algorithms. Both commonly used and newly developed algorithms are taken into account by the systems. The algorithms have diverse technological and program implementation. Agile features of the recommendation systems allow continuously modify and enlarge the set of the used methods and algorithms. The key advantage of the systems is possibility to test new algorithms on real data processing tasks. An example of recommender system for binary data streams processing is described.