The continuous cold start problem in e-commerce recommender systems

L. Bernardi, J. Kamps, Y. Kiseleva, M.J.I. Mueller

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

11 Citations (Scopus)
3 Downloads (Pure)

Abstract

Many e-commerce websites use recommender systems to recommend items to users. When a user or item is new, the system may fail because not enough information is available on this user or item. Various solutions to this `cold-start problem' have been proposed in the literature. However, many real-life e-commerce applications suffer from an aggravated, recurring version of cold-start even for known users or items, since many users visit the website rarely, change their interests over time, or exhibit different personas. This paper exposes the `Continuous Cold Start' (CoCoS) problem and its consequences for content- and context-based recommendation from the viewpoint of typical e-commerce applications, illustrated with examples from a major travel recommendation website, Booking.com. Keywords: Recommender systems, continous cold-start problem, industrial applications
Original languageEnglish
Title of host publication2nd Workshop on New Trends on Content-Based Recommender Systems (CBRecSys 2015, Vienna, Austria, September 20, 2015; co-located with RecSys 2015)
EditorsT. Bogers, M. Koolen
PublisherCEUR-WS.org
Pages30-33
Publication statusPublished - 2015

Publication series

NameCEUR Workshop Proceedings
Volume1448
ISSN (Print)1613-0073

Fingerprint

Recommender systems
Websites
Industrial applications

Cite this

Bernardi, L., Kamps, J., Kiseleva, Y., & Mueller, M. J. I. (2015). The continuous cold start problem in e-commerce recommender systems. In T. Bogers, & M. Koolen (Eds.), 2nd Workshop on New Trends on Content-Based Recommender Systems (CBRecSys 2015, Vienna, Austria, September 20, 2015; co-located with RecSys 2015) (pp. 30-33). (CEUR Workshop Proceedings; Vol. 1448). CEUR-WS.org.
Bernardi, L. ; Kamps, J. ; Kiseleva, Y. ; Mueller, M.J.I. / The continuous cold start problem in e-commerce recommender systems. 2nd Workshop on New Trends on Content-Based Recommender Systems (CBRecSys 2015, Vienna, Austria, September 20, 2015; co-located with RecSys 2015). editor / T. Bogers ; M. Koolen. CEUR-WS.org, 2015. pp. 30-33 (CEUR Workshop Proceedings).
@inproceedings{ad63ddf291014017a93b227b048cf218,
title = "The continuous cold start problem in e-commerce recommender systems",
abstract = "Many e-commerce websites use recommender systems to recommend items to users. When a user or item is new, the system may fail because not enough information is available on this user or item. Various solutions to this `cold-start problem' have been proposed in the literature. However, many real-life e-commerce applications suffer from an aggravated, recurring version of cold-start even for known users or items, since many users visit the website rarely, change their interests over time, or exhibit different personas. This paper exposes the `Continuous Cold Start' (CoCoS) problem and its consequences for content- and context-based recommendation from the viewpoint of typical e-commerce applications, illustrated with examples from a major travel recommendation website, Booking.com. Keywords: Recommender systems, continous cold-start problem, industrial applications",
author = "L. Bernardi and J. Kamps and Y. Kiseleva and M.J.I. Mueller",
year = "2015",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "CEUR-WS.org",
pages = "30--33",
editor = "T. Bogers and M. Koolen",
booktitle = "2nd Workshop on New Trends on Content-Based Recommender Systems (CBRecSys 2015, Vienna, Austria, September 20, 2015; co-located with RecSys 2015)",

}

Bernardi, L, Kamps, J, Kiseleva, Y & Mueller, MJI 2015, The continuous cold start problem in e-commerce recommender systems. in T Bogers & M Koolen (eds), 2nd Workshop on New Trends on Content-Based Recommender Systems (CBRecSys 2015, Vienna, Austria, September 20, 2015; co-located with RecSys 2015). CEUR Workshop Proceedings, vol. 1448, CEUR-WS.org, pp. 30-33.

The continuous cold start problem in e-commerce recommender systems. / Bernardi, L.; Kamps, J.; Kiseleva, Y.; Mueller, M.J.I.

2nd Workshop on New Trends on Content-Based Recommender Systems (CBRecSys 2015, Vienna, Austria, September 20, 2015; co-located with RecSys 2015). ed. / T. Bogers; M. Koolen. CEUR-WS.org, 2015. p. 30-33 (CEUR Workshop Proceedings; Vol. 1448).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - The continuous cold start problem in e-commerce recommender systems

AU - Bernardi, L.

AU - Kamps, J.

AU - Kiseleva, Y.

AU - Mueller, M.J.I.

PY - 2015

Y1 - 2015

N2 - Many e-commerce websites use recommender systems to recommend items to users. When a user or item is new, the system may fail because not enough information is available on this user or item. Various solutions to this `cold-start problem' have been proposed in the literature. However, many real-life e-commerce applications suffer from an aggravated, recurring version of cold-start even for known users or items, since many users visit the website rarely, change their interests over time, or exhibit different personas. This paper exposes the `Continuous Cold Start' (CoCoS) problem and its consequences for content- and context-based recommendation from the viewpoint of typical e-commerce applications, illustrated with examples from a major travel recommendation website, Booking.com. Keywords: Recommender systems, continous cold-start problem, industrial applications

AB - Many e-commerce websites use recommender systems to recommend items to users. When a user or item is new, the system may fail because not enough information is available on this user or item. Various solutions to this `cold-start problem' have been proposed in the literature. However, many real-life e-commerce applications suffer from an aggravated, recurring version of cold-start even for known users or items, since many users visit the website rarely, change their interests over time, or exhibit different personas. This paper exposes the `Continuous Cold Start' (CoCoS) problem and its consequences for content- and context-based recommendation from the viewpoint of typical e-commerce applications, illustrated with examples from a major travel recommendation website, Booking.com. Keywords: Recommender systems, continous cold-start problem, industrial applications

UR - http://ceur-ws.org/Vol-1448/paper6.pdf

M3 - Conference contribution

T3 - CEUR Workshop Proceedings

SP - 30

EP - 33

BT - 2nd Workshop on New Trends on Content-Based Recommender Systems (CBRecSys 2015, Vienna, Austria, September 20, 2015; co-located with RecSys 2015)

A2 - Bogers, T.

A2 - Koolen, M.

PB - CEUR-WS.org

ER -

Bernardi L, Kamps J, Kiseleva Y, Mueller MJI. The continuous cold start problem in e-commerce recommender systems. In Bogers T, Koolen M, editors, 2nd Workshop on New Trends on Content-Based Recommender Systems (CBRecSys 2015, Vienna, Austria, September 20, 2015; co-located with RecSys 2015). CEUR-WS.org. 2015. p. 30-33. (CEUR Workshop Proceedings).