Sequential Selection of Correlated Ads by POMDPsShuai Yuan
This document summarizes a research paper that proposes a framework for sequential ad selection to optimize online advertising revenue. It formulates the problem as a partially observable Markov decision process (POMDP) and provides exact and approximate solutions. The paper evaluates the proposed approach on a public dataset and finds that considering dependencies between ads and using a POMDP formulation outperforms baseline methods like selecting ads randomly or based only on immediate reward.
Gunosyデータマイニング研究会 #97でA/Bテストに関して述べている KDD2007の論文"Practical Guide to Controlled Experiments on the Web:
Listen to Your Customers
not to the HiPPO"を紹介した記事になります。著者はMicrosoftの方です。
This document discusses demand-side platforms (DSPs) and prediction in DSPs. It explains how DSPs work with supply-side platforms (SSPs) through real-time bidding (RTB) to buy impressions for advertisers. Prediction in DSPs involves estimating click-through rates (CTRs) using models like logistic regression, factorization machines, and follow-the-regularized-leader optimization to determine optimal bid prices. The models are trained on click logs and tested offline before being implemented online through A/B testing.
In display and mobile advertising, the most significant development in recent years is the Real-Time Bidding (RTB), which allows selling and buying in real-time one ad impression at a time. The ability of making impression level bid decision and targeting to an individual user in real-time has fundamentally changed the landscape of the digital media. The further demand for automation, integration and optimisation in RTB brings new research opportunities in the IR fields, including information matching with economic constraints, CTR prediction, user behaviour targeting and profiling, personalised advertising, and attribution and evaluation methodologies. In this tutorial, teamed up with presenters from both the industry and academia, we aim to bring the insightful knowledge from the real-world systems, and to provide an overview of the fundamental mechanism and algorithms with the focus on the IR context. We will also introduce to IR researchers a few datasets recently made available so that they can get hands-on quickly and enable the said research.
Sequential Selection of Correlated Ads by POMDPsShuai Yuan
This document summarizes a research paper that proposes a framework for sequential ad selection to optimize online advertising revenue. It formulates the problem as a partially observable Markov decision process (POMDP) and provides exact and approximate solutions. The paper evaluates the proposed approach on a public dataset and finds that considering dependencies between ads and using a POMDP formulation outperforms baseline methods like selecting ads randomly or based only on immediate reward.
Gunosyデータマイニング研究会 #97でA/Bテストに関して述べている KDD2007の論文"Practical Guide to Controlled Experiments on the Web:
Listen to Your Customers
not to the HiPPO"を紹介した記事になります。著者はMicrosoftの方です。
This document discusses demand-side platforms (DSPs) and prediction in DSPs. It explains how DSPs work with supply-side platforms (SSPs) through real-time bidding (RTB) to buy impressions for advertisers. Prediction in DSPs involves estimating click-through rates (CTRs) using models like logistic regression, factorization machines, and follow-the-regularized-leader optimization to determine optimal bid prices. The models are trained on click logs and tested offline before being implemented online through A/B testing.
In display and mobile advertising, the most significant development in recent years is the Real-Time Bidding (RTB), which allows selling and buying in real-time one ad impression at a time. The ability of making impression level bid decision and targeting to an individual user in real-time has fundamentally changed the landscape of the digital media. The further demand for automation, integration and optimisation in RTB brings new research opportunities in the IR fields, including information matching with economic constraints, CTR prediction, user behaviour targeting and profiling, personalised advertising, and attribution and evaluation methodologies. In this tutorial, teamed up with presenters from both the industry and academia, we aim to bring the insightful knowledge from the real-world systems, and to provide an overview of the fundamental mechanism and algorithms with the focus on the IR context. We will also introduce to IR researchers a few datasets recently made available so that they can get hands-on quickly and enable the said research.
Problem-based Based Learning Meets Web 2.0annielibrarian
1) The document describes using a YouTube video in a problem-based learning (PBL) format to teach information literacy to undergraduate students.
2) PBL involves having students learn to conduct research by working through an ill-defined problem. The session uses a short YouTube video to illustrate the problem and has students work through defining facts, creating a problem statement, and determining what additional information is needed to solve the problem.
3) Pilots of this approach received positive feedback from students, who felt the video helped grab their attention and the exercises helped them understand how to effectively research topics.
The document asks the reader to select a slide show presentation and prepare for something. It ends by wishing the reader a nice day and is signed by Brad.
This document provides information on verb tenses and the passive voice in English. It discusses the present, past, and future tenses, including the present progressive, present perfect, past perfect, future perfect, and future perfect continuous. It also covers using verbs in the passive voice and provides examples of converting sentences from active to passive voice. Exercises are included to identify auxiliary verbs, convert state meanings to habit meanings, and complete a story using verb tenses.
Problem-based Based Learning Meets Web 2.0annielibrarian
1) The document describes using a YouTube video in a problem-based learning (PBL) format to teach information literacy to undergraduate students.
2) PBL involves having students learn to conduct research by working through an ill-defined problem. The session uses a short YouTube video to illustrate the problem and has students work through defining facts, creating a problem statement, and determining what additional information is needed to solve the problem.
3) Pilots of this approach received positive feedback from students, who felt the video helped grab their attention and the exercises helped them understand how to effectively research topics.
The document asks the reader to select a slide show presentation and prepare for something. It ends by wishing the reader a nice day and is signed by Brad.
This document provides information on verb tenses and the passive voice in English. It discusses the present, past, and future tenses, including the present progressive, present perfect, past perfect, future perfect, and future perfect continuous. It also covers using verbs in the passive voice and provides examples of converting sentences from active to passive voice. Exercises are included to identify auxiliary verbs, convert state meanings to habit meanings, and complete a story using verb tenses.