在线广告中点击率预测研究

doi:10.3969/j.issn.1000-5641.2017.05.008

华东师范大学学报(自然科学版) ›› 2017, Vol. 2017 ›› Issue (5): 80-86,100.doi: 10.3969/j.issn.1000-5641.2017.05.008

在线广告中点击率预测研究

肖垚¹, 毕军芳², 韩易¹, 董启文¹

1. 华东师范大学数据科学与工程学院, 上海 200062;
2. 长江口水文水资源勘测局, 上海 200136

收稿日期:2017-05-01 出版日期:2017-09-25 发布日期:2017-09-25
通讯作者: 董启文,男,硕士生导师,副教授,研究方向为网络信息学、生物信息学.E-mail:qwdong@dase.ecnu.edu.cn E-mail:qwdong@dase.ecnu.edu.cn
作者简介:肖垚,男,硕士研究生,研究方向为广告点击率预测
基金资助:
国家重点研发计划（2016YFB1000905）；国家自然科学基金广东省联合重点项目（U1401256）；国家自然科学基金（61672234，61402177）；华东师范大学信息化软课题

Study of click through rate prediction in online advertisement

XIAO YAO¹, BI Jun-fang², HAN YI¹, DONG Qi-wen¹

1. School of Data Science and Engineering, East China Normal University, Shanghai 200062, China;
2. Yangtze River Estuary Survey Bureau of Hydrology and Water Resource, CWRC, Ministry of Water Resources, Shanghai 200136, China

Received:2017-05-01 Online:2017-09-25 Published:2017-09-25

摘要/Abstract

摘要： 随着互联网的发展和用户的增长，广告行业从传统的线下广告模式，逐步转变为线上广告模式.同时，由于大数据分析技术的运用，线上广告模式相比于传统广告也体现了巨大的优越性.广告主之间相互竞争，通过竞价的方式，将自己的广告投放在运营媒体的广告位上.所以，在投放前预测该广告可能被用户点击的概率（CTR），对于广告主减少成本和增加可能收入来说非常重要.本文在调研了目前常用的广告点击率预测模型的基础上，选取广告主、广告和投放媒体平台信息作为预测模型的特征，采用真实数据集验证说明各种模型的优劣性，以及不同特征对广告点击率预测结果的影响.

关键词: 计算广告, CTR, 机器学习

Abstract: With the development of the Internet and the growth of users, the advertising industry originated from the traditional offline advertising model, is gradually transforming into online advertising model. At the same time, due to the use of large data analysis technology, online advertising shows great advantages when compared with traditional advertising. The advertisers deliver their advertisements to the platform's specific positions by competition auction of counterparts. Therefore, it is important to predict the click through rate (CTR) of a given advertisement before auction, which is important for advertisers to reduce costs and expand their likely revenue.This paper introduces the commonly used ad click rate prediction model, uses the information from different advertisers, advertisements and media platforms as the features of machine learning, and uses real data sets to illustrate the advantages of various models,and the impact of different features on the ad click rate.

Key words: computational advertising, CTR, machine learning

中图分类号:

TP391

肖垚, 毕军芳, 韩易, 董启文. 在线广告中点击率预测研究[J]. 华东师范大学学报(自然科学版), 2017, 2017(5): 80-86,100.

XIAO YAO, BI Jun-fang, HAN YI, DONG Qi-wen. Study of click through rate prediction in online advertisement[J]. Journal of East China Normal University(Natural Sc, 2017, 2017(5): 80-86,100.

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在线广告中点击率预测研究

Study of click through rate prediction in online advertisement

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