Proceedings of the 2015 International ACM Recommender Systems Challenge最新文献

筛选

英文中文

Linear and Non-Linear Models for Purchase Prediction 采购预测的线性和非线性模型

Proceedings of the 2015 International ACM Recommender Systems Challenge Pub Date : 2015-09-16 DOI: 10.1145/2813448.2813518

Wenliang Chen, Zhenghua Li, Min Zhang

引用次数: 5

An ensemble approach for multi-label classification of item click sequences 项目点击序列多标签分类的集成方法

Proceedings of the 2015 International ACM Recommender Systems Challenge Pub Date : 2015-09-16 DOI: 10.1145/2813448.2813516

A. Murat, Ya Gcı, Tevfik Aytekin, F. Gürgen

{"title":"An ensemble approach for multi-label classification of item click sequences","authors":"A. Murat, Ya Gcı, Tevfik Aytekin, F. Gürgen","doi":"10.1145/2813448.2813516","DOIUrl":"https://doi.org/10.1145/2813448.2813516","url":null,"abstract":"In this paper, we describe our approach to RecSys 2015 challenge problem. Given a dataset of item click sessions, the problem is to predict whether a session results in a purchase and which items are purchased if the answer is yes. We define a simpler analogous problem where given an item and its session, we try to predict the probability of purchase for the given item. For each session, the predictions result in a set of purchased items or often an empty set. We apply monthly time windows over the dataset. For each item in a session, we engineer features regarding the session, the item properties, and the time window. Then, a balanced random forest classifier is trained to perform predictions on the test set. The dataset is particularly challenging due to privacy-preserving definition of a session, the class imbalance problem, and the volume of data. We report our findings with respect to feature engineering, the choice of sampling schemes, and classifier ensembles. Experimental results together with benefits and shortcomings of the proposed approach are discussed. The solution is efficient and practical in commodity computers.","PeriodicalId":324873,"journal":{"name":"Proceedings of the 2015 International ACM Recommender Systems Challenge","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127497581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Predicting User Purchase in E-commerce by Comprehensive Feature Engineering and Decision Boundary Focused Under-Sampling 基于综合特征工程和决策边界聚焦欠采样的电子商务用户购买预测

Proceedings of the 2015 International ACM Recommender Systems Challenge Pub Date : 2015-09-16 DOI: 10.1145/2813448.2813517

Chanyoung Park, Dong Hyun Kim, Jinoh Oh, Hwanjo Yu

引用次数: 11

首页上一页