Abstract is missing.
- Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session DataØyvind H. Myklatun, Thorstein K. Thorrud, Hai Thanh Nguyen 0001, Helge Langseth, Anders Kofod-Petersen. [doi]
- Solving RecSys Challenge 2015 by Linear Models, Gradient Boosted Trees and Metric OptimizationRóbert Pálovics, Peter Szalai, Levente Kocsis, Adrienn Szabó, Erzsébet Frigó, Júlia Pap, Zsófia K. Nyikes, András A. Benczúr. [doi]
- Purchase Prediction and Item Suggestion based on HTTP sessions in absence of User InformationPouya Esmailian, Mahdi Jalili. [doi]
- Neural Modeling of Buying Behaviour for E-Commerce from Clicking PatternsZhenzhou Wu, Bao Hong Tan, Rubing Duan, Yong Liu, Rick Siow Mong Goh. [doi]
- E-Commerce Item Recommendation Based on Field-aware Factorization MachinePeng Yan, Xiaocong Zhou, Yitao Duan. [doi]
- Linear and Non-Linear Models for Purchase PredictionWenliang Chen, Zhenghua Li, Min Zhang. [doi]
- In-House Solution for the RecSys Challenge 2015Nadav Cohen, Adi Gerzi, David Ben-Shimon, Bracha Shapira, Lior Rokach, Michael Friedmann. [doi]
- RecSys Challenge 2015: ensemble learning with categorical featuresPeter Romov, Evgeny Sokolov. [doi]
- Multi-Perspective Modeling for Click Event PredictionTzu-Chun Lin, Xia Ning. [doi]
- Predicting User Purchase in E-commerce by Comprehensive Feature Engineering and Decision Boundary Focused Under-SamplingChanyoung Park, Dong-hyun Kim, Jinoh Oh, Hwanjo Yu. [doi]
- An ensemble approach for multi-label classification of item click sequencesA. Murat Yagci, Tevfik Aytekin, Fikret S. Gürgen. [doi]
- Two-Stage Approach to Item Recommendation from User SessionsMaksims Volkovs. [doi]