2026-05-29T20:50:19.446Z http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai

ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:1:7021 2019-05-30T11:32:12Z 1

Recommendation System with Personalizable Distributed Collaborative Filtering 2017 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/7021 Д. Видаковић М. Сегединац Đ. Obradović Г. Савић Collaborative Filtering technique is a state-of-theart method in recommender systems. This technique has proved to be successful both in research and industry. However, it is challenging to find an adequate algorithm for calculating user similarity, which enables the recommender system to generate the best recommendation for given domain and data set. In this paper, we proposed an architecture which allows users to additionally personalize the recommendation by letting them choose algorithm for calculating user similarities, or to implement their own algorithm on a distributed service. Online tests on implemented application for movie recommendation show that architecture proposed in this paper gives users the ability to personalize recommendation for more efficient results. conferenceObject 29 32 7th International Conference on Information Society Technology and Management, ICIST 2017