�ݺ�ߣshows by User: shuaiyuancn

�ݺ�ߣshows by User: shuaiyuancn / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: shuaiyuancn / Mon, 11 Apr 2016 09:25:20 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: shuaiyuancn RTBMA ECIR 2016 tutorial /slideshow/rtbma-ecir-2016-tutorial/60747286 final-slides-160411092520
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.]]>
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.]]> Mon, 11 Apr 2016 09:25:20 GMT /slideshow/rtbma-ecir-2016-tutorial/60747286 shuaiyuancn@slideshare.net(shuaiyuancn) RTBMA ECIR 2016 tutorial shuaiyuancn 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. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/final-slides-160411092520-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> 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.

RTBMA ECIR 2016 tutorial from Shuai Yuan

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0 CIKM 2013 Tutorial: Real-time Bidding: A New Frontier of Computational Advertising Research /slideshow/cikm-2013-tutorial/28164233 final-131112104554-phpapp02
Computational Advertising has been an important topical area in information retrieval and knowledge management. This tutorial will be focused on real-time advertising, aka Real-Time Bidding (RTB), the fundamental shift in the field of computational advertising. It is strongly related to CIKM areas such as user log analysis and modelling, information retrieval, text mining, knowledge extraction and management, behaviour targeting, recommender systems, personalization, and data management platform. This tutorial aims to provide not only a comprehensive and systemic introduction to RTB and computational advertising in general, but also the emerging research challenges and research tools and datasets in order to facilitate the research. Compared to previous Computational Advertising tutorials in relevant top-tier conferences, this tutorial takes a fresh, neutral, and the latest look of the field and focuses on the fundamental changes brought by RTB. We will begin by giving a brief overview of the history of online advertising and present the current eco-system in which RTB plays an increasingly important part. Based on our field study and the DSP optimisation contest organised by iPinyou, we analyse optimization problems both from the demand side (advertisers) and the supply side (publishers), as well as the auction mechanism design challenges for Ad exchanges. We discuss how IR, DM and ML techniques have been applied to these problems. In addition, we discuss why game theory is important in this area and how it could be extended beyond the auction mechanism design. CIKM is an ideal venue for this tutorial because RTB is an area of multiple disciplines, including information retrieval, data mining, knowledge discovery and management, and game theory, most of which are traditionally the key themes of the conference. As an illustration of practical application in the real world, we shall cover algorithms in the iPinyou global DSP optimisation contest on a production platform; for the supply side, we also report experiments of inventory management, reserve price optimisation, etc. in production systems. We expect the audience, after attending the tutorial, to understand the real-time online advertising mechanisms and the state of the art techniques, as well as to grasp the research challenges in this field. Our motivation is to help the audience acquire domain knowledge and obtain relevant datasets, and to promote research activities in RTB and computational advertising in general.]]>
Computational Advertising has been an important topical area in information retrieval and knowledge management. This tutorial will be focused on real-time advertising, aka Real-Time Bidding (RTB), the fundamental shift in the field of computational advertising. It is strongly related to CIKM areas such as user log analysis and modelling, information retrieval, text mining, knowledge extraction and management, behaviour targeting, recommender systems, personalization, and data management platform. This tutorial aims to provide not only a comprehensive and systemic introduction to RTB and computational advertising in general, but also the emerging research challenges and research tools and datasets in order to facilitate the research. Compared to previous Computational Advertising tutorials in relevant top-tier conferences, this tutorial takes a fresh, neutral, and the latest look of the field and focuses on the fundamental changes brought by RTB. We will begin by giving a brief overview of the history of online advertising and present the current eco-system in which RTB plays an increasingly important part. Based on our field study and the DSP optimisation contest organised by iPinyou, we analyse optimization problems both from the demand side (advertisers) and the supply side (publishers), as well as the auction mechanism design challenges for Ad exchanges. We discuss how IR, DM and ML techniques have been applied to these problems. In addition, we discuss why game theory is important in this area and how it could be extended beyond the auction mechanism design. CIKM is an ideal venue for this tutorial because RTB is an area of multiple disciplines, including information retrieval, data mining, knowledge discovery and management, and game theory, most of which are traditionally the key themes of the conference. As an illustration of practical application in the real world, we shall cover algorithms in the iPinyou global DSP optimisation contest on a production platform; for the supply side, we also report experiments of inventory management, reserve price optimisation, etc. in production systems. We expect the audience, after attending the tutorial, to understand the real-time online advertising mechanisms and the state of the art techniques, as well as to grasp the research challenges in this field. Our motivation is to help the audience acquire domain knowledge and obtain relevant datasets, and to promote research activities in RTB and computational advertising in general.]]> Tue, 12 Nov 2013 10:45:54 GMT /slideshow/cikm-2013-tutorial/28164233 shuaiyuancn@slideshare.net(shuaiyuancn) CIKM 2013 Tutorial: Real-time Bidding: A New Frontier of Computational Advertising Research shuaiyuancn Computational Advertising has been an important topical area in information retrieval and knowledge management. This tutorial will be focused on real-time advertising, aka Real-Time Bidding (RTB), the fundamental shift in the field of computational advertising. It is strongly related to CIKM areas such as user log analysis and modelling, information retrieval, text mining, knowledge extraction and management, behaviour targeting, recommender systems, personalization, and data management platform. This tutorial aims to provide not only a comprehensive and systemic introduction to RTB and computational advertising in general, but also the emerging research challenges and research tools and datasets in order to facilitate the research. Compared to previous Computational Advertising tutorials in relevant top-tier conferences, this tutorial takes a fresh, neutral, and the latest look of the field and focuses on the fundamental changes brought by RTB. We will begin by giving a brief overview of the history of online advertising and present the current eco-system in which RTB plays an increasingly important part. Based on our field study and the DSP optimisation contest organised by iPinyou, we analyse optimization problems both from the demand side (advertisers) and the supply side (publishers), as well as the auction mechanism design challenges for Ad exchanges. We discuss how IR, DM and ML techniques have been applied to these problems. In addition, we discuss why game theory is important in this area and how it could be extended beyond the auction mechanism design. CIKM is an ideal venue for this tutorial because RTB is an area of multiple disciplines, including information retrieval, data mining, knowledge discovery and management, and game theory, most of which are traditionally the key themes of the conference. As an illustration of practical application in the real world, we shall cover algorithms in the iPinyou global DSP optimisation contest on a production platform; for the supply side, we also report experiments of inventory management, reserve price optimisation, etc. in production systems. We expect the audience, after attending the tutorial, to understand the real-time online advertising mechanisms and the state of the art techniques, as well as to grasp the research challenges in this field. Our motivation is to help the audience acquire domain knowledge and obtain relevant datasets, and to promote research activities in RTB and computational advertising in general. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/final-131112104554-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Computational Advertising has been an important topical area in information retrieval and knowledge management. This tutorial will be focused on real-time advertising, aka Real-Time Bidding (RTB), the fundamental shift in the field of computational advertising. It is strongly related to CIKM areas such as user log analysis and modelling, information retrieval, text mining, knowledge extraction and management, behaviour targeting, recommender systems, personalization, and data management platform. This tutorial aims to provide not only a comprehensive and systemic introduction to RTB and computational advertising in general, but also the emerging research challenges and research tools and datasets in order to facilitate the research. Compared to previous Computational Advertising tutorials in relevant top-tier conferences, this tutorial takes a fresh, neutral, and the latest look of the field and focuses on the fundamental changes brought by RTB. We will begin by giving a brief overview of the history of online advertising and present the current eco-system in which RTB plays an increasingly important part. Based on our field study and the DSP optimisation contest organised by iPinyou, we analyse optimization problems both from the demand side (advertisers) and the supply side (publishers), as well as the auction mechanism design challenges for Ad exchanges. We discuss how IR, DM and ML techniques have been applied to these problems. In addition, we discuss why game theory is important in this area and how it could be extended beyond the auction mechanism design. CIKM is an ideal venue for this tutorial because RTB is an area of multiple disciplines, including information retrieval, data mining, knowledge discovery and management, and game theory, most of which are traditionally the key themes of the conference. As an illustration of practical application in the real world, we shall cover algorithms in the iPinyou global DSP optimisation contest on a production platform; for the supply side, we also report experiments of inventory management, reserve price optimisation, etc. in production systems. We expect the audience, after attending the tutorial, to understand the real-time online advertising mechanisms and the state of the art techniques, as well as to grasp the research challenges in this field. Our motivation is to help the audience acquire domain knowledge and obtain relevant datasets, and to promote research activities in RTB and computational advertising in general.

CIKM 2013 Tutorial: Real-time Bidding: A New Frontier of Computational Advertising Research from Shuai Yuan

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0 Sequential Selection of Correlated Ads by POMDPs /slideshow/slides-14951394/14951394 slides-121030105418-phpapp01
�ݺ�ߣs presented by Shuai Yuan at CIKM '12.]]>
�ݺ�ߣs presented by Shuai Yuan at CIKM '12.]]> Tue, 30 Oct 2012 10:54:17 GMT /slideshow/slides-14951394/14951394 shuaiyuancn@slideshare.net(shuaiyuancn) Sequential Selection of Correlated Ads by POMDPs shuaiyuancn �ݺ�ߣs presented by Shuai Yuan at CIKM '12. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/slides-121030105418-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> �ݺ�ߣs presented by Shuai Yuan at CIKM '12.

Sequential Selection of Correlated Ads by POMDPs from Shuai Yuan

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0 https://cdn.slidesharecdn.com/profile-photo-shuaiyuancn-48x48.jpg?cb=1572264771 http://www.yuan-shuai.info https://cdn.slidesharecdn.com/ss_thumbnails/final-slides-160411092520-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/rtbma-ecir-2016-tutorial/60747286 RTBMA ECIR 2016 tutorial https://cdn.slidesharecdn.com/ss_thumbnails/final-131112104554-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/cikm-2013-tutorial/28164233 CIKM 2013 Tutorial: Re... https://cdn.slidesharecdn.com/ss_thumbnails/slides-121030105418-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/slides-14951394/14951394 Sequential Selection o...