互联网广告与计算广告学资源

互联网广告与计算广告学资源整理,内容来源于互联网,仅供参考。

斯坦福的计算广告学入门

课程主要围绕搜索广告、展示广告、定向与重定向、推荐系统等讲解相关的广告市场与计算广告技术。

课程网址:http://web.stanford.edu/class/msande239/

课程内容:

  • Lecture 1: Introduction, Supplementary notes
  • Lecture 2: Marketplace design, In class presentation, Supplementary notes
  • Lecture 3: Sponsored search 1, In class presentation
  • Lecture 4: Sponsored search 2, In class presentation
  • Lecture 5: Display advertising 1, In class presentation
  • Lecture 6: Display advertising 2, In class presentation
  • Lecture 7: Targeting, In class presentation
  • Lecture 8: Recommender systems, In class presentation 1, In class presentation 2
  • Lecture 9: Mobile, video, and other emerging formats, In class presentation 1, In class presentation 2

刘鹏 – 计算广告学

刘鹏老师目前在 360 任商业产品首席架构师,在互联网广告领域实战经验丰富。其课程《计算广告学》内容深入浅出,由广告历史模式到新近技术,非常适合入门学习。

课程网址:http://study.163.com/course/introduction.htm?courseId=321007
文本版本:https://dirtysalt.github.io/computational-advertising.html

课程内容:

  • 广告的基本知识
  • 合约广告系统
  • 受众定向
  • 竞价广告系统
  • 搜索广告与广告网络Demand技术
  • 广告交易市场

UCS -计算广告学入门

系统的介绍计算广告学相关知识。

课程网址:http://classes.soe.ucsc.edu/ism293/Spring09/index_archivos/Page456.html

课程内容:

  • Introduction and Overview
  • Information Retrieval (IR) for Computational
  • Marketplace design
  • Machine Learning Techniques
  • Sponsored Search I
  • Sponsored Search II
  • Graphical ads and guaranteed delivery
  • Contextual Advertising I
  • Contextual Advertising II
  • Behavioral Targeting (BT)

秒针系统 – Computational Advertising Infrastructure

是由秒针系统在人大讲授的《Computational Advertising Infrastructure》课程内容。

资源网址:http://wenku.baidu.com/u/fengshicong?from=wenku

课程内容:

  • Lecture1-Course Overview and Introduction
  • Lecture2-Marketplace & Economics
  • Lecture3-Fraud Detection
  • Lecture4-?(未找到)
  • Lecture5-Display Advertising
  • Lecture6-RS Algorithms & Models
  • Lecture7-RS Products & Users
  • Lecture8-UV Estimation & Identification
  • Lecture9-CTR Prediction
  • Lecture10-Targeting
  • Lecture11-Sponsored Search Auctions
  • Lecture12-Ad serving, bidding, monitoring
  • Lecture13-Computational Advertising Infrastructure

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