Cold-start Problem of Mobile News Client with Personalization Recommendation

DOI

10.2991/meici-16.2016.202How to use a DOI?

Keywords

Personalization recommendation; Cold-start; User feature; Start-up system

Abstract

With news clients appeared in different fields, start-up systems, due to lack of user data, will cause the cold-start problem of personalization recommendation service. In the cold-start problem, this paper proposes a data migration-based cold-start algorithm, a cold-start algorithm based on user mobile device interest preference and a location services-based cold-start algorithm. Through analysis of performance differences and defects existed of these algorithms, so as to provide a reference of selection algorithms to users in solving the cold-start problem.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jun Li
AU  - Zhixin Shi
AU  - Jingang Liu
AU  - Gao Lu
PY  - 2016/09
DA  - 2016/09
TI  - Cold-start Problem of Mobile News Client with Personalization Recommendation
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 973
EP  - 977
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.202
DO  - 10.2991/meici-16.2016.202
ID  - Li2016/09
ER  -