Archived project

Hybrid Recommender System Based on Collaborative Filtering and User Demographic Data

Goal: Using user demographic data in collaborative-base recommender systems

Date: 1 April 2017 - 1 May 2017

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Project log

Reza Hamouleh
added a research item
Recommender systems are systems that help internet users to decide according to their personality based characteristics by giving some suggestions. Because these systems confront with numerous data and must offer the best suggestion to users in a reasonable time, these suggestions should provide some specifications together include accuracy, novelty, stability and rapidity. In this paper, a new hybrid recommender system is proposed regarding Collaborative Filtering (CF) based recommender system as one of the most important and practical recommender system and user demographic data. In the proposed system, for an active user, at first, the nearest users are identified considering user demographic data, and then using collaborative filtering based recommender system, some suggestions are presented to the active user. The results on experiments show the efficiency of the proposed system.
Reza Hamouleh
added a project goal
Using user demographic data in collaborative-base recommender systems