Open AccessCombined recommender algorithms for enterprises
Author(s) -
A. Kurennykh,
Vladimir Anatolievich Sudakov
Publication year - 2021
Publication title -
preprint/preprinty ipm im. m.v. keldyša
Language(s) - English
Resource type - Journals
eISSN - 2071-2901
pISSN - 2071-2898
DOI - 10.20948/prepr-2021-60
Subject(s) - computer science , recommender system , schema (genetic algorithms) , relation (database) , software , algorithm , data mining , information retrieval , programming language
The authors describe an approach to the implementation of combined algorithms for recommender systems considered with the example of a separate module of the information system of an enterprise. We propose four groups of criteria, which, using various approaches, allows one to explore and evaluate objects in relation to the problem of developing recommendations. During a research database schema required for the implementation of the algorithm has been developed, as well as the software.