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    • 1. 发明申请
    • Management Of The Display Of Online Ad Content Consistent With One Or More Performance Objectives For A Webpage And/Or Website
    • 管理在线广告内容显示符合一个或多个性能目标的页面和/或网站
    • US20150220972A1
    • 2015-08-06
    • US14170096
    • 2014-01-31
    • Wal-Mart Stores, Inc.
    • Shankara B. SubramanyaGirish NatarajanGuoxun YuanJunhao JiangMadhusudan MathihalliChris Bolte
    • G06Q30/02
    • G06Q30/0246
    • Systems and methods are disclosed for managing the display of online ad content consistent with one or more e-commerce objectives. A collection module may be operable to collect attribute values for a set of attributes characterizing user visits to a set of training webpages and subsequent attribute values for a subsequent user visit to a subsequent webpage. A model-generation module may be operable to train a probability model with the attribute values that predicts outcomes for at least one performance metric. A display module may be operable to determine whether to display ad content on the subsequent webpage for the subsequent user visit depending on whether a predicted outcome from the probability model that is relevant to the subsequent attribute values is consistent with one or more e-commerce objectives. The probability model may be a decision tree with different predicted outcomes for different combinations of attribute values.
    • 公开了用于管理与一个或多个电子商务目标一致的在线广告内容的显示的系统和方法。 收集模块可以用于收集表征用户访问一组训练网页的属性集合的属性值,并且随后的用户访问后续网页的后续属性值。 模型生成模块可以用于利用预测至少一个性能度量的结果的属性值来训练概率模型。 显示模块可操作以根据与随后的属性值相关的来自概率模型的预测结果是否与一个或多个电子商务目标一致来确定是否在后续网页上显示广告内容以供随后的用户访问 。 概率模型可以是对不同属性值组合具有不同预测结果的决策树。
    • 8. 发明申请
    • Recommending Product Groups in Ecommerce
    • 推荐电子商务中的产品组
    • US20150095202A1
    • 2015-04-02
    • US14042340
    • 2013-09-30
    • Wal-Mart Stores, Inc.
    • Shankara B. SubramanyaAndy LinMadhusudan MathihalliGirish Nath Natarajan
    • G06Q10/08
    • G06Q10/087G06Q30/0281G06Q30/0631
    • Systems and methods are disclosed herein for supplementing product records with product groups that are relevant to the product records. Queries form users may be analyzed to extract keywords. Search results for keywords are evaluated to determine category consistency among product records, including such values as entropy and taxonomy depth. Those keywords with search results having adequate category consistency are selected as product groups and the search results associated with the product groups. Product groups are associated with product records according to a random walk of a graph having as nodes products and product groups and links representing belonging of a product to a product group. Product groups may be selected based on a transition probability based on a random walk and a quality score based on usage of a product group page for the product group.
    • 本文公开的系统和方法用于对与产品记录相关的产品组补充产品记录。 查询表单用户可能会被分析以提取关键字。 对关键字的搜索结果进行评估,以确定产品记录之间的类别一致性,包括熵和分类深度等值。 选择具有足够类别一致性的搜索结果的关键字作为产品组和与产品组相关联的搜索结果。 产品组根据具有作为节点产品和产品组的图形的随机游走与代表产品属于产品组的链接相关联的产品记录。 可以基于基于随机游走的转移概率和基于产品组的产品组页面的使用的质量得分来选择产品组。