会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 12. 发明申请
    • NOTIFICATION PLATFORM ARCHITECTURE
    • 通知平台架构
    • US20070011314A1
    • 2007-01-11
    • US11469058
    • 2006-08-31
    • Eric HorvitzDavid HovelAndrew JacobsCarl Kadie
    • Eric HorvitzDavid HovelAndrew JacobsCarl Kadie
    • G06F15/173
    • G06Q10/107G06F17/18
    • An architecture for a notification platform is disclosed. In one embodiment, the architecture includes a user mechanism, one or more notification sources and sinks, and a notification manager. The user mechanism stores information regarding notification parameters of a user, such as the user's default notification preferences, and may also contain, access, and/or infer contextual information. Each notification source generates notifications intended for the user, while each notification sink can provide the notifications to the user. Notification sources and sinks provide information via standardized notification schema. The notification manager is designed to appropriately convey the notifications generated by the sources to the sinks, based on information provided by the user mechanism, and by the sources and sinks. As disclosed, the architecture is applicable to entities other users as well.
    • 公开了一种通知平台架构。 在一个实施例中,该架构包括用户机制,一个或多个通知源和汇点以及通知管理器。 用户机构存储关于用户的通知参数的信息,诸如用户的默认通知偏好,并且还可以包含,访问和/或推断上下文信息。 每个通知源产生针对用户的通知,而每个通知接收器可以向用户提供通知。 通知源和汇通过标准化通知模式提供信息。 通知管理器被设计为基于由用户机制提供的信息以及源和汇来适当地传送由源产生的通知给汇。 如所公开的,该架构也适用于其他用户的实体。
    • 14. 发明申请
    • Methods for and applications of learning and inferring the periods of time until people are available or unavailable for different forms of communication, collaboration, and information access
    • 学习方法和应用,并推断出人们可用或不可用于不同形式的沟通,协作和信息访问的时间
    • US20050132006A1
    • 2005-06-16
    • US11047527
    • 2005-01-31
    • Eric HorvitzCarl KadieAndrew Jacobs
    • Eric HorvitzCarl KadieAndrew Jacobs
    • G06Q10/10G06F12/14
    • G06Q10/109
    • A system and method are provided to learn and infer the time until a user will be available for communications, collaboration, or information access, given evidence about such observations as time of day, calendar, location, presence, and activity. The methods can be harnessed to coordinate communications between parties via particular modalities of interaction. The system includes a user state identifier that determines a user's state from background knowledge, the flow of time, or one or more context information sources. A data log can be employed to store information about user state changes and observational evidence to accumulate statistics and build inferential models of the availability and unavailability of users for different kinds of communication, collaboration, and information access. A forecaster is constructed from the accumulated statistics and/or learned models to enable a determination of a user's likely return, or, more generally, the probability distribution over a user's likely return to particular states of availability. The forecaster can be employed to cache information for offline access, drive displays of availability and unavailability, to send messages that include availability forecasts, and to automatically perform scheduling or rescheduling of communications.
    • 提供了一种系统和方法,用于了解和推断直到用户可用于通信,协作或信息访问的时间,给出有关诸如时间,日历,位置,存在和活动之类的观察的证据。 可以利用这些方法通过特定的交互方式协调各方之间的通信。 该系统包括从背景知识,时间流或者一个或多个上下文信息源确定用户状态的用户状态标识符。 可以使用数据日志来存储关于用户状态变化和观察证据的信息,以累积统计信息,并构建用于不同种类的通信,协作和信息访问的可用性和不可用性的推理模型。 预测者是由累积的统计学和/或学习模型构成的,以便确定用户的可能回报,或者更一般地说,用户可能返回特定可用状态的概率分布。 可以使用预测器缓存信息以进行离线访问,驱动显示可用性和不可用性,以发送包括可用性预测的消息,并自动执行调度或重新安排通信。
    • 17. 发明申请
    • Training, inference and user interface for guiding the caching of media content on local stores
    • 培训,推理和用户界面,用于指导本地商店的媒体内容缓存
    • US20050193414A1
    • 2005-09-01
    • US11121219
    • 2005-05-03
    • Eric HorvitzCarl KadieStuart OzerCurtis Wong
    • Eric HorvitzCarl KadieStuart OzerCurtis Wong
    • G06F3/00G06F13/00G06F17/30H04N5/445H04N5/76H04N5/765H04N5/775H04N7/16H04N7/173
    • H04N5/44543H04N5/76H04N5/765H04N5/775H04N7/163H04N21/4147H04N21/4331H04N21/4335H04N21/44008H04N21/4532H04N21/466H04N21/4667H04N21/4755H04N21/482Y10S707/99931Y10S707/99932Y10S707/99937Y10S707/99945
    • The present invention is related to a system and method of caching data employing probabilistic predictive techniques. The system and method has particular application to multimedia systems for providing local storage of a subset of available viewing selections by assigning a value to a selection and retaining selections in the cache depending on the value and size of the selection. The value assigned to an item can represent the time-dependent likelihood that a user will review an item at some time in the future. An initial value of an item can be based on the user's viewing habits, the user's viewing habit over particular time segment (e.g., early morning, late morning, early afternoon, late afternoon, primetime, late night) and/or viewing habits of a group of user's during a particular time segment. A value assigned to a selection dynamically changes according to a set of cache retention policies, where the value can be time-dependent functions that decay based on the class of the item, as determined by inference about the class or via a label associated with the item. A selections value may be reduced as the selection ages because a user is less likely to view the selection over time. Additionally, a value of a selection may change based on changes on a user's viewing habits, changes in time segments or a user's modification of the cache retention policies.
    • 本发明涉及采用概率预测技术来缓存数据的系统和方法。 该系统和方法特别适用于多媒体系统,用于通过根据选择的值和大小向选择分配值并保留高速缓存中的选择来提供可用观看选择子集的本地存储。 分配给项目的值可以表示用户将来某个时间审查项目的时间依赖性的可能性。 项目的初始值可以基于用户的观看习惯,用户在特定时间段(例如,清晨,凌晨,下午,下午,黄金时段,深夜)和/或观看习惯的观看习惯 特定时段内的用户组。 分配给选择的值根据一组高速缓存保留策略动态地改变,其中该值可以是基于项目类别而衰减的时间依赖函数,这通过关于该类别的推断或通过与该类别相关联的标签来确定 项目。 由于用户不太可能随着时间的推移来查看选择,所以选择值可能会减少。 此外,选择的值可以基于用户的观看习惯的变化,时间段的变化或用户对缓存保留策略的修改而改变。
    • 18. 发明授权
    • Methods and apparatus for retrieving and/or processing retrieved
information as a function of a user's estimated knowledge
    • 用于根据用户的估计知识检索和/或处理检索到的信息的方法和装置
    • US6006218A
    • 1999-12-21
    • US807566
    • 1997-02-28
    • John S. BreeseDavid E. HeckermanEric HorvitzCarl KadieKeiji Kanazawa
    • John S. BreeseDavid E. HeckermanEric HorvitzCarl KadieKeiji Kanazawa
    • G06F17/30
    • G06F17/30864Y10S707/99933Y10S707/99935
    • Information retrieval methods and apparatus which involve: 1) the generation of estimates regarding the probability that items included in search results are already known to the user and 2) the use of such knowledge probability estimates to influence the ranking of search results, are described. By discounting the ranking, or adjusting ranking values generated by a known search engine as a function of the knowledge probability estimates, the present invention reduces or eliminates the risk of locating known information near the top of a list of search results. This is advantageous since known information is generally of little interest to a user. In various embodiments the popularity of an item is used to estimate the probability that the item is already known to a user. In addition, in various embodiments one or more user controllable parameters are used in the generation of the knowledge probability estimates and/or the ranking of the search results to give the user an opportunity to have the ranking of the search results accurately reflect the user's knowledge. The present invention is particularly well suited to collaborative filtering based search systems. This is because collaborative filters make recommendations to a user based on historical information relating to, e.g., the popularity of items being considered for recommendation. This same popularity information can be used to estimate a users knowledge of a database item. Such items may include television shows, music, Internet sites, etc.
    • 信息检索方法和装置,其涉及:1)生成关于搜索结果中包含的项目对于用户已知的概率的估计,以及2)使用这种知识概率估计来影响搜索结果的排名。 通过对排名进行折扣或者根据知识概率估计来调整由已知搜索引擎产生的排名值,本发明减少或消除了在搜索结果列表顶部附近定位已知信息的风险。 这是有利的,因为已知的信息通常对用户没有兴趣。 在各种实施例中,使用项目的流行度来估计项目已经被用户知道的概率。 此外,在各种实施例中,一个或多个用户可控参数用于产生知识概率估计和/或搜索结果的排名以给予用户机会使搜索结果的排名准确地反映用户的知识 。 本发明特别适合于基于协作过滤的搜索系统。 这是因为协作过滤器基于与例如被考虑用于推荐的项目的受欢迎程度有关的历史信息向用户提出建议。 可以使用相同的流行度信息来估计用户对数据库项目的了解。 这些物品可能包括电视节目,音乐,互联网站点等。
    • 19. 发明申请
    • METHODS AND ARCHITECTURE FOR CROSS-DEVICE ACTIVITY MONITORING, REASONING, AND VISUALIZATION FOR PROVIDING STATUS AND FORECASTS OF A USERS' PRESENCE AND AVAILABILITY
    • 跨设备活动监测,理论和可视化的方法和架构,用于提供用户状态和可用性的状态和预测
    • US20070071209A1
    • 2007-03-29
    • US11469148
    • 2006-08-31
    • Eric HorvitzPaul KochJohnson ApacibleCarl Kadie
    • Eric HorvitzPaul KochJohnson ApacibleCarl Kadie
    • H04M3/42
    • G06Q10/109
    • The present invention relates to a system and methodology to facilitate collaboration and communications between entities such as between automated applications, parties to a communication and/or combinations thereof. The systems and methods of the present invention include a service that supports collaboration and communication by learning predictive models that provide forecasts of one or more aspects of a users' presence and availability. Presence forecasts include a user's current or future locations at different levels of location precision and usage of different devices or applications. Availability assessments include inferences about the cost of interrupting a user in different ways and a user's current or future access to one or more communication channels. The predictive models are constructed from data collected by considering user activity and proximity from multiple devices, in addition to analysis of the content of users' calendars, the time of day, and day of week, for example. Various applications are provided that employ the presence and availability information supplied by the models in order to facilitate collaboration and communications between entities.
    • 本发明涉及促进实体之间的协作和通信的系统和方法,例如在自动应用,通信方和/或其组合之间。 本发明的系统和方法包括通过学习提供用户的存在和可用性的一个或多个方面的预测的预测模型来支持协作和通信的服务。 存在预测包括用户在不同级别的位置精度和不同设备或应用的使用的当前或将来的位置。 可用性评估包括关于以不同方式中断用户的成本以及用户当前或未来访问一个或多个通信信道的推论。 除了分析用户日历的内容,一天中的一天和一周中的一天之外,还通过考虑用户活动和多个设备的邻近度来收集的数据构建预测模型。 提供了各种应用,其使用由模型提供的存在和可用性信息,以便于实体之间的协作和通信。