A. V. Smirnov, N. G. Shilov, A. V. Ponomarev, A. M. Kashevnik, V. G. Parfenov, “Group context-driven collaborative filtering recommending systems: main principles, architecture and models”, Artificial Intelligence and Decision Making, 2013, Issue 4,Pages <nobr>14

This article is cited in 6 papers

Intelligent systems and technologies

Group context-driven collaborative filtering recommending systems: main principles, architecture and models

A. V. Smirnov^a, N. G. Shilov^a, A. V. Ponomarev^a, A. M. Kashevnik^a, V. G. Parfenov^b

^a St. Petersburg Institute for Informatics and Automation of RAS
^b St. Petersburg National Research University of Information Technologies, Mechanics and Optics

Abstract: The paper proposes an architecture and main models of context-driven collaborative filtering recommending systems. The major problems arising during creation of such systems are identified and their possible solutions are suggested. The advantages of contextual pre-filtering methods for context analysis are justified. The main processes of recommendation generation are described. The usage of the system is demonstrated on a case study of mobile tourist application.

Keywords: recommending systems, collaborative filtering, context, ontology, profile management.