Recommendation Systems in a Conversational Web

Konstantinos N. Vavliakis, Maria Th. Kotouza, Andreas L. Symeonidis, Pericles A. Mitkas

2018

Abstract

In this paper we redefine the concept of Conversation Web in the context of hyper-personalization. We argue that hyper-personalization in the WWW is only possible within a conversational web where websites and users continuously “discuss” (interact in any way). We present a modular system architecture for the conversational WWW, given that adapting to various user profiles and multivariate websites in terms of size and user traffic is necessary, especially in e-commerce. Obviously there cannot be a unique fit-to-all algorithm, but numerous complementary personalization algorithms and techniques are needed. In this context, we propose PRCW, a novel hybrid approach combining offline and online recommendations using RFMG, an extension of RFM modeling. We evaluate our approach against the results of a deep neural network in two datasets coming from different online retailers. Our evaluation indicates that a) the proposed approach outperforms current state-of-art methods in small-medium datasets and can improve performance in large datasets when combined with other methods, b) results can greatly vary in different datasets, depending on size and characteristics, thus locating the proper method for each dataset can be a rather complex task, and c) offline algorithms should be combined with online methods in order to get optimal results since offline algorithms tend to offer better performance but online algorithms are necessary for exploiting new users and trends that turn up.

Paper Citation

in Harvard Style

Vavliakis K., Kotouza M., Symeonidis A. and Mitkas P. (2018). Recommendation Systems in a Conversational Web.In Proceedings of the 14th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-324-7, pages 68-77. DOI: 10.5220/0006935300680077

in Bibtex Style

@conference{webist18,
author={Konstantinos N. Vavliakis and Maria Th. Kotouza and Andreas L. Symeonidis and Pericles A. Mitkas},
title={Recommendation Systems in a Conversational Web},
booktitle={Proceedings of the 14th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2018},
pages={68-77},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006935300680077},
isbn={978-989-758-324-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Recommendation Systems in a Conversational Web
SN - 978-989-758-324-7
AU - Vavliakis K.
AU - Kotouza M.
AU - Symeonidis A.
AU - Mitkas P.
PY - 2018
SP - 68
EP - 77
DO - 10.5220/0006935300680077