TY - GEN
T1 - In-house solution for the RecSys challenge 2015
AU - Cohen, Nadav
AU - Shapira, Bracha
AU - Gerzi, Adi
AU - Rokach, Lior
AU - Ben-Shimon, David
AU - Friedmann, Michael
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/9/16
Y1 - 2015/9/16
N2 - RecSys Challenge 2015 is about predicting the items a user will buy in a given click session. We describe the in-house solution to the challenge as guided by the YOOCHOOSE team. The presented solution achieved 14th place in the challenge's final leaderboard with a score of 51,932 points, while the winner obtained 63,102 points. We suggest two simple and easy to reconstruct approaches for obtaining a prediction in each session. In the first approach we suggest one classifier to determine whether each item in the session will be bought. In the second approach we suggest a two level classification model in which the first level determines whether the session is going to end with a purchase or not, and if it ends with a purchase, the second level classification determines the items that are going to be purchased.
AB - RecSys Challenge 2015 is about predicting the items a user will buy in a given click session. We describe the in-house solution to the challenge as guided by the YOOCHOOSE team. The presented solution achieved 14th place in the challenge's final leaderboard with a score of 51,932 points, while the winner obtained 63,102 points. We suggest two simple and easy to reconstruct approaches for obtaining a prediction in each session. In the first approach we suggest one classifier to determine whether each item in the session will be bought. In the second approach we suggest a two level classification model in which the first level determines whether the session is going to end with a purchase or not, and if it ends with a purchase, the second level classification determines the items that are going to be purchased.
KW - In-house solution
KW - RecSys challenge 2015
KW - Recommender systems
UR - http://www.scopus.com/inward/record.url?scp=84960867377&partnerID=8YFLogxK
U2 - 10.1145/2813448.2813519
DO - 10.1145/2813448.2813519
M3 - Conference contribution
AN - SCOPUS:84960867377
T3 - Proceedings of the International ACM Recommender Systems Challenge 2015
BT - Proceedings of the International ACM Recommender Systems Challenge 2015
PB - Association for Computing Machinery, Inc
T2 - International ACM Recommender Systems Challenge, RecSys 2015
Y2 - 16 September 2015
ER -