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    • 1. 发明申请
    • SELECTING ADVERTISEMENTS FOR PLACEMENT ON RELATED WEB PAGES
    • 选择相关网页放置广告
    • US20120191531A1
    • 2012-07-26
    • US13381037
    • 2010-12-27
    • Siyu YouPeng Liu
    • Siyu YouPeng Liu
    • G06Q30/02
    • G06F17/3089G06Q30/0241G06Q30/0243
    • Systems and methods are described that select advertisements for placement on a series of consecutively-accessed web pages, such as consecutively-accessed web search results pages generated in response to a particular search. The systems and methods perform a separate advertisement ranking process to select advertisements for placement on each web page in the series of consecutively-accessed web pages at the time the web page is accessed. For web pages that follow the first web page in the series, the systems and methods utilize an advertisement ranking technique that calculates a probability that a user will select an advertisement based on certain user selection feedback features. The user selection feedback features for an advertisement are determined by comparing attributes of the advertisement to attributes of user-selectable items that were presented on one or more of the previously-accessed web pages in the series that are known to have been selected or not selected by the user.
    • 描述了系统和方法,其选择用于放置在一系列连续访问的网页上的广告,诸如响应于特定搜索生成的连续访问的网页搜索结果页面。 系统和方法执行单独的广告排序过程,以在访问网页时选择在连续访问的一系列网页中的每个网页上的布置的广告。 对于遵循该系列中的第一网页的网页,系统和方法利用广告排序技术,其计算用户将基于特定用户选择反馈特征来选择广告的概率。 用于广告的用户选择反馈特征通过将广告的属性与在系列中已被选择或未被选择的一个或多个先前访问的网页上呈现的用户可选项目的属性进行比较来确定 由用户
    • 2. 发明授权
    • Selecting advertisements for placement on related web pages
    • 选择在相关网页上放置广告
    • US08620745B2
    • 2013-12-31
    • US13381037
    • 2010-12-27
    • Siyu YouPeng Liu
    • Siyu YouPeng Liu
    • G06Q30/00
    • G06F17/3089G06Q30/0241G06Q30/0243
    • Systems and methods are described that select advertisements for placement on a series of consecutively-accessed web pages, such as consecutively-accessed web search results pages generated in response to a particular search. The systems and methods perform a separate advertisement ranking process to select advertisements for placement on each web page in the series of consecutively-accessed web pages at the time the web page is accessed. For web pages that follow the first web page in the series, the systems and methods utilize an advertisement ranking technique that calculates a probability that a user will select an advertisement based on certain user selection feedback features. The user selection feedback features for an advertisement are determined by comparing attributes of the advertisement to attributes of user-selectable items that were presented on one or more of the previously-accessed web pages in the series that are known to have been selected or not selected by the user.
    • 描述了系统和方法,其选择用于放置在一系列连续访问的网页上的广告,诸如响应于特定搜索生成的连续访问的网页搜索结果页面。 系统和方法执行单独的广告排序过程,以在访问网页时选择在连续访问的一系列网页中的每个网页上的布置的广告。 对于遵循该系列中的第一网页的网页,系统和方法利用广告排序技术,其计算用户将基于特定用户选择反馈特征来选择广告的概率。 用于广告的用户选择反馈特征通过将广告的属性与在系列中已被选择或未被选择的一个或多个先前访问的网页上呈现的用户可选项目的属性进行比较来确定 由用户
    • 4. 发明申请
    • Systems and Methods for List Ranking and Ads Placement Using Interaction Freatures
    • 使用互动自由的列表排名和广告展示的系统和方法
    • US20120143672A1
    • 2012-06-07
    • US12982539
    • 2010-12-30
    • Siyu YouJiacheng GuoQuansheng Duan
    • Siyu YouJiacheng GuoQuansheng Duan
    • G06Q30/00
    • G06Q30/0247G06Q30/0243
    • Systems and methods for placing ads in a block on a webpage are disclosed. Generally, two ranking models are trained using a first and second ads data set. The first model predicts a first click probability for each ad in the first ads data and rank the ads based on the eCPM. The second model is trained using the second ads data set comprising a subset of the first ads data set and interaction features related to ad position in the block. The second model predicts a second click probability for each ad in the second ads data set. An overall expected revenue for each arrangement of ads in the second ads data set is then calculated. The computer system selects the arrangement with maximum computed overall expected revenue and places the ads in the block on the webpage according to the selected arrangement.
    • 公开了将广告放置在网页上的块中的系统和方法。 通常,使用第一和第二广告数据集来训练两个排名模型。 第一个模型预测了第一个广告数据中每个广告的首次点击概率,并根据有效每千次展示费用对广告进行排名。 使用第二广告数据集来训练第二模型,该第二广告数据集包括第一广告数据集的一部分和与该块中的广告位置相关的交互特征。 第二种模式预测第二个广告数据集中每个广告的第二次点击概率。 然后计算第二个广告数据集中每个广告排列的整体预期收入。 计算机系统选择具有最大计算总体预期收入的布置,并根据所选择的布置将广告放置在网页上。