Using a Skip-gram Architecture for Model Contextualization in CARS

Dimitris Poulopoulos; Athina Kalampogia

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Paper

Using a Skip-gram Architecture for Model Contextualization in CARS

In Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: ADITCA, 443-446, 2019 , Prague, Czech Republic

Authors: Dimitris Poulopoulos and Athina Kalampogia

Affiliation: QIVOS, Athens and Greece

Keyword(s): Context-aware Recommender Systems, Proximity Marketing, Deep Learning.

Abstract: In this paper, we describe how a major retailer’s recommender system contextualizes the information that is passed to it, to provide real-time in-store recommendations, at a high level. We specifically focus on the data pre-processing ideas that were necessary for the model to learn. The paper describes the ideas and reasoning behind crucial data transformations, and then illustrates a learning model inspired by the work done in Natural Language Processing.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Poulopoulos, D. and Kalampogia, A. (2019). Using a Skip-gram Architecture for Model Contextualization in CARS. In Proceedings of the 8th International Conference on Data Science, Technology and Applications - ADITCA; ISBN 978-989-758-377-3; ISSN 2184-285X, SciTePress, pages 443-446. DOI: 10.5220/0008256304430446

@conference{aditca19,
author={Dimitris Poulopoulos. and Athina Kalampogia.},
title={Using a Skip-gram Architecture for Model Contextualization in CARS},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - ADITCA},
year={2019},
pages={443-446},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008256304430446},
isbn={978-989-758-377-3},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - ADITCA
TI - Using a Skip-gram Architecture for Model Contextualization in CARS
SN - 978-989-758-377-3
IS - 2184-285X
AU - Poulopoulos, D.
AU - Kalampogia, A.
PY - 2019
SP - 443
EP - 446
DO - 10.5220/0008256304430446
PB - SciTePress