基于概率的稀疏会话数据预测电子商务消费者行为方法

Proceedings of the 2015 International ACM Recommender Systems Challenge Pub Date : 2015-09-16 DOI:10.1145/2813448.2813514

Øyvind H. Myklatun, Thorstein K. Thorrud, H. Nguyen, H. Langseth, Anders Kofod-Petersen

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引用次数: 1

摘要

本文介绍了Tøyvind ørrud团队为RecSys 2015挑战赛提出的解决方案的一些关键特性。将突出三个贡献:i)特征提取，ii)分类器设计，以及iii)决策规则，以优化对RecSys挑战分数的预测结果。在250多支参赛队伍中，我们获得了第六名。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session Data

This paper describes some of the key properties of the proposed solution for the RecSys 2015 Challenge from the team Tøyvind thørrud. Three contributions will be highlighted: i) Feature extraction, ii) Classifier design, and iii) Decision rules to optimize the prediction results towards the RecSys Challenge's score. We finished sixth out of more than 250 active teams in the competition.

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Proceedings of the 2015 International ACM Recommender Systems Challenge

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