TY - GEN
T1 - ConCaT
T2 - 37th IEEE International Conference on Data Engineering, ICDE 2021
AU - Avron, Uri
AU - Gershtein, Shay
AU - Guy, Ido
AU - Milo, Tova
AU - Novgorodov, Slava
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/1
Y1 - 2021/4/1
N2 - Category trees play a central role in e-commerce platforms, enabling browsing-style information access. Building category trees that reflect users' dynamic information needs is a challenging task, mostly carried out by in-house taxonomists. This manual construction often leads to trees that are lacking or outdated since it is hard to keep track of market trends, seasonal changes, holidays, and special events.To support a browsing experience that better matches the user information needs, and to considerably reduce the manual work performed by taxonomists, we propose CONCAT - a system that leverages the demand-based nature of the query paradigm to automatically build a category tree that is maximally similar to the result sets for search queries. We demonstrate the effectiveness of CONCAT on real-world data, taken from a large e-commerce platform, by interacting with the ICDE'21 participants who act both as the consumers and the taxonomists.
AB - Category trees play a central role in e-commerce platforms, enabling browsing-style information access. Building category trees that reflect users' dynamic information needs is a challenging task, mostly carried out by in-house taxonomists. This manual construction often leads to trees that are lacking or outdated since it is hard to keep track of market trends, seasonal changes, holidays, and special events.To support a browsing experience that better matches the user information needs, and to considerably reduce the manual work performed by taxonomists, we propose CONCAT - a system that leverages the demand-based nature of the query paradigm to automatically build a category tree that is maximally similar to the result sets for search queries. We demonstrate the effectiveness of CONCAT on real-world data, taken from a large e-commerce platform, by interacting with the ICDE'21 participants who act both as the consumers and the taxonomists.
UR - http://www.scopus.com/inward/record.url?scp=85112868049&partnerID=8YFLogxK
U2 - 10.1109/ICDE51399.2021.00308
DO - 10.1109/ICDE51399.2021.00308
M3 - Conference contribution
AN - SCOPUS:85112868049
T3 - Proceedings - International Conference on Data Engineering
SP - 2701
EP - 2704
BT - Proceedings - 2021 IEEE 37th International Conference on Data Engineering, ICDE 2021
PB - Institute of Electrical and Electronics Engineers
Y2 - 19 April 2021 through 22 April 2021
ER -