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    • 1. 发明授权
    • Routing, alerting, and transportation guidance based on preferences and learned or inferred risks and desirabilities
    • 基于偏好和学习或推断的风险和需求的路由,警报和交通指导
    • US09086292B2
    • 2015-07-21
    • US12493131
    • 2009-06-26
    • Eric HorvitzJohn Krumm
    • Eric HorvitzJohn Krumm
    • G01C21/34G01C21/00G01C21/36
    • G01C21/3484G01C21/3697
    • Techniques and systems are disclosed that provide a risk-based assessment for a user based on user location information. Incident data is acquired for incidents that involve potential risks (e.g., to people and/or property) from a plurality of locations and contexts, considering such factors as date, time, weather, traffic, and velocity. The incident data is matched to the user's location and context directly or indirectly to provide one or more potential outcomes of interest (e.g., accidents, injuries, fatalities), and inferences regarding the likelihood of events are made available. These measures are compared to desired risk thresholds for the user. In one embodiment, routes, times, and conditions of travel may be preferred over others routes, times, and conditions. In another embodiment, users may be notified of a condition or a vehicle's maximum velocity may be reduced when the matched incident data meets/exceeds a user's risk threshold.
    • 公开了基于用户位置信息为用户提供基于风险的评估的技术和系统。 考虑到诸如日期,时间,天气,交通和速度等因素,从多个位置和情境中获取涉及潜在风险(例如对人和/或财产)的事件的事件数据。 事件数据与用户的位置和环境直接或间接地匹配,以提供一个或多个潜在的感兴趣的结果(例如,事故,伤害,死亡),并且关于事件的可能性可用的推论。 将这些措施与用户的期望风险阈值进行比较。 在一个实施例中,旅行的路线,时间和条件可能优于其他路线,时间和条件。 在另一个实施例中,可以向用户通知条件,或者当匹配的事件数据满足/超过用户的风险阈值时,可以减少车辆的最大速度。
    • 3. 发明授权
    • Online marketplace with shipping incentives
    • 在线市场与航运激励
    • US08768763B2
    • 2014-07-01
    • US13174309
    • 2011-06-30
    • Eric HorvitzGur KimchiLili ChengDoug BurgerStelios PaparizosMarc Davis
    • Eric HorvitzGur KimchiLili ChengDoug BurgerStelios PaparizosMarc Davis
    • G06Q30/00
    • G06Q30/0222G06Q10/0832G06Q10/08355G06Q30/06
    • A marketplace server and method for facilitating purchase transactions are provided. A marketplace server may include a routing engine configured to receive an order for goods from a first computing device associated with a first customer, with the order including a first delivery address of the customer. The routing engine also calculates a delivery route to the first delivery address. An offer engine is configured to create an offer for other goods. The offer includes a shipping incentive associated with a second delivery address of a second customer. The offer may be targeted to the second customer based on a proximity of the second delivery address to the delivery route. The offer engine sends the offer to a second computing device associated with the second customer. Upon receiving an acceptance of the offer from the computing device, the offer engine processes a purchase transaction for the offer.
    • 提供了一种用于促进采购交易的市场服务器和方法。 市场服务器可以包括路由引擎,路由引擎被配置为从与第一客户相关联的第一计算设备接收货物的订单,该订单包括客户的第一传送地址。 路由引擎还计算到第一个传送地址的传输路由。 优惠引擎被配置为为其他商品创建报价。 该优惠包括与第二客户的第二送货地址相关联的运送激励。 基于第二递送地址与递送路线的接近度,该优惠可以针对第二客户。 报价引擎将报价发送给与第二客户相关联的第二计算设备。 在接收到来自计算设备的报价的接收之后,报价引擎处理该报价的购买交易。
    • 4. 发明申请
    • MULTI-STEP IMPRESSION CAMPAIGNS
    • 多阶段印象裁判
    • US20130006754A1
    • 2013-01-03
    • US13174329
    • 2011-06-30
    • Eric HorvitzLili ChengRoger BargaXuedong HuangZachary ApterSemiha Ece Kamar
    • Eric HorvitzLili ChengRoger BargaXuedong HuangZachary ApterSemiha Ece Kamar
    • G06Q30/00
    • G06Q30/00G06Q30/0251
    • Various embodiments are described for computerized advertising systems and methods. The system may include an ad server that includes an impression campaign engine configured to associate a target user profile with a plurality of computing devices. The ad server is also configured to receive a multi-step impression plan including a plurality of triggers from an advertiser. Each trigger is associated with a different advertisement to be served to at least one of the plurality of devices. The system also includes an ad serving engine configured to serve a first advertisement to a first device in response to making an inference from sensors or detecting a first trigger, and a second advertisement to a second device in response to a second inference or detecting a second trigger, according to the impression plan. A predictive model developed from machine learning may be used to develop a learning-based multi-step impression plan.
    • 针对计算机广告系统和方法描述了各种实施例。 系统可以包括广告服务器,其包括被配置为将目标用户简档与多个计算设备相关联的印象活动引擎。 广告服务器还被配置为接收包括来自广告主的多个触发器的多步展示计划。 每个触发器与要被提供给多个设备中的至少一个的不同广告相关联。 该系统还包括一个广告服务引擎,该广告服务引擎被配置为响应于从传感器进行推断或检测第一触发而向第一设备发送第一广告,并响应于第二推断或检测第二个推断,向第二设备发送第二广告 触发,按照印象计划。 可以使用从机器学习开发的预测模型来开发基于学习的多步印象计划。
    • 6. 发明授权
    • Commercially subsidized mobile communication devices and services
    • 商业补贴的移动通信设备和服务
    • US08340689B2
    • 2012-12-25
    • US12701539
    • 2010-02-06
    • Eric HorvitzXuedong HuangKamal JainMilind Vasudeo Mahajan
    • Eric HorvitzXuedong HuangKamal JainMilind Vasudeo Mahajan
    • H04W24/00
    • G06Q30/0267G06Q30/0261H04M15/00H04M15/09H04M2215/0192H04W4/00H04W4/025H04W4/24H04W48/02H04W64/00
    • Mobile communication devices, such as mobile phones, may be capable of recommending to a user various providers of one or more solicited services, e.g., by identifying a user location and identifying providers near the user location that provide the services, and by initiating a call between the user and a selected provider. However, the equipment and service costs of such devices may be prohibitive, particularly for mid-range mobile communication devices that may appeal to cost-conscious users. The prohibitive costs may be diminished by redirecting part or all of the cost of providing the recommendation service from the providers, e.g., by charging the provider a service cost upon initiating a call from the user to the provider, or upon representing the provider in a provider database. In one such embodiment, all service costs may be borne by providers, providing to the user a free recommendation service via the mobile communication device.
    • 诸如移动电话的移动通信设备可以能够向用户推荐一个或多个被请求的服务的各种提供者,例如通过识别用户位置并识别用户位置附近的提供服务的提供者,并且通过发起呼叫 在用户和选定的提供商之间。 然而,这些设备的设备和服务成本可能是过高的,特别是对于可能吸引具有成本意识的用户的中档移动通信设备。 通过将提供推荐服务的成本的部分或全部重定向到提供者,例如,通过在向用户发起呼叫到提供者的呼叫中向服务商收取服务成本,或者以 提供者数据库。 在一个这样的实施例中,所有服务成本可以由提供商承担,经由移动通信设备向用户提供免费的推荐服务。
    • 7. 发明申请
    • COMMERCIALLY SUBSIDIZED MOBILE COMMUNICATION DEVICES AND SERVICES
    • 商业化的移动通信设备和服务
    • US20110195726A1
    • 2011-08-11
    • US12701539
    • 2010-02-06
    • Eric HorvitzXuedong HuangKamal JainMilind Vasudeo Mahajan
    • Eric HorvitzXuedong HuangKamal JainMilind Vasudeo Mahajan
    • H04W64/00
    • G06Q30/0267G06Q30/0261H04M15/00H04M15/09H04M2215/0192H04W4/00H04W4/025H04W4/24H04W48/02H04W64/00
    • Mobile communication devices, such as mobile phones, may be capable of recommending to a user various providers of one or more solicited services, e.g., by identifying a user location and identifying providers near the user location that provide the services, and by initiating a call between the user and a selected provider. However, the equipment and service costs of such devices may be prohibitive, particularly for mid-range mobile communication devices that may appeal to cost-conscious users. The prohibitive costs may be diminished by redirecting part or all of the cost of providing the recommendation service from the providers, e.g., by charging the provider a service cost upon initiating a call from the user to the provider, or upon representing the provider in a provider database. In one such embodiment, all service costs may be borne by providers, providing to the user a free recommendation service via the mobile communication device.
    • 诸如移动电话的移动通信设备可以能够向用户推荐一个或多个被请求的服务的各种提供者,例如通过识别用户位置并识别用户位置附近的提供服务的提供者,并且通过发起呼叫 在用户和选定的提供商之间。 然而,这些设备的设备和服务成本可能是过高的,特别是对于可能吸引具有成本意识的用户的中档移动通信设备。 通过将提供推荐服务的成本的部分或全部重定向到提供者,例如,通过在向用户发起呼叫到提供者的呼叫中向服务商收取服务成本,或者以 提供者数据库。 在一个这样的实施例中,所有服务成本可以由提供商承担,经由移动通信设备向用户提供免费的推荐服务。
    • 10. 发明申请
    • GENERALIZED ACTIVE LEARNING
    • 一般主动学习
    • US20100332423A1
    • 2010-12-30
    • US12490449
    • 2009-06-24
    • Ashish KapoorEric Horvitz
    • Ashish KapoorEric Horvitz
    • G06N5/04G06N7/02
    • G06N5/045
    • Active learning is extended to decisions on information acquisition of both missing labels and missing features within one or more cases. In one example, desired (e.g., optimal) information to acquire about a case at hand and about cases in a training library during diagnostic sessions can be computed concurrently. A joint distribution of variables, comprising observed and unobserved labels and features for one or more cases, is modeled and probability distributions are determined for unobserved variables. An unobserved variable is selected from the joint distribution that has a return on information (ROI) metric having a combination of a desired uncertainty metric for a value of the unobserved variable and a desired cost for observing the value of the unobserved variable. The value of the variable is observed, and the probability distributions for the respective unobserved variables in the joint distribution are updated using the value of the identified variable.
    • 主动学习扩展到在一个或多个情况下丢失标签和缺失功能的信息获取的决策。 在一个示例中,可以同时计算期望的(例如,最佳)信息来获取有关病例的情况以及在诊断期间关于训练库中的情况。 对一个或多个情况的包含观察到和未观察到的标签和特征的变量的联合分布进行建模,并为未观察到的变量确定概率分布。 从具有返回信息(ROI)度量的联合分布中选择未观察到的变量,其具有对于未观察到的变量的值的期望不确定性度量的组合和用于观察未观察到的变量的值的期望成本。 观察变量的值,并使用识别的变量的值来更新关联分布中各个不可观察变量的概率分布。