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    • 1. 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。
    • 2. 发明授权
    • Intelligent user assistance facility for a software program
    • 用于软件程序的智能用户辅助功能
    • US06233570B1
    • 2001-05-15
    • US09197160
    • 1998-11-20
    • Eric HorvitzJohn S. BreeseDavid E. HeckermanSamuel D. HobsonDavid O. HovelAdrian C. KleinJacobus A. RommelseGregory L. Shaw
    • Eric HorvitzJohn S. BreeseDavid E. HeckermanSamuel D. HobsonDavid O. HovelAdrian C. KleinJacobus A. RommelseGregory L. Shaw
    • G06F1700
    • G06N5/00G06F9/453Y10S707/99943
    • A general event composing and monitoring system that allows high-level events to be created from combinations of low-level events. An event specification tool allows for rapid development of a general event processor that creates high-level events from combinations of user actions. The event system, in combination with a reasoning system, is able to monitor and perform inference about several classes of events for a variety of purposes. The various classes of events include the current context, the state of key data structures in a program, general sequences of user inputs, including actions with a mouse-controlled cursor while interacting with a graphical user interface, words typed in free-text queries for assistance, visual information about users, such as gaze and gesture information, and speech information. Additionally, a method is provided for building an intelligent user interface system by constructing a reasoning model to compute the probability of alternative user's intentions, goals, or informational needs through analysis of information about a user's actions, program state, and words. The intelligent user interface system monitors user interaction with a software application and applies probabilistic reasoning to sense that the user may need assistance in using a particular feature or to accomplish a specific task. The intelligent user interface also accepts a free-text query from the user asking for help and combines the inference analysis of user actions and program state with an inference analysis of the free-text query. The inference system accesses a rich, updatable user profile system to continually check for competencies and changes assistance that is given based on user competence.
    • 一般的事件编制和监控系统,允许从低级别事件的组合创建高级别事件。 事件规范工具可以快速开发通用事件处理器,从用户操作的组合创建高级事件。 事件系统与推理系统相结合,能够监视和执行关于几类事件的推理,用于各种目的。 各种类型的事件包括当前上下文,程序中关键数据结构的状态,用户输入的一般序列,包括与图形用户界面交互时使用鼠标控制的光标的操作,以自由文本查询形式输入的单词 帮助,关于用户的视觉信息,例如注视和手势信息,以及语音信息。 另外,提供了一种构建智能用户界面系统的方法,通过构建推理模型来通过分析关于用户动作,程序状态和单词的信息来计算替代用户的意图,目标或信息需求的概率。 智能用户界面系统监视用户与软件应用程序的交互,并应用概率推理来感知用户可能需要协助使用特定功能或完成特定任务。 智能用户界面还接受用户请求帮助的自由文本查询,并将用户操作和程序状态的推理分析与自由文本查询的推理分析相结合。 推理系统访问丰富的,可更新的用户配置文件系统,以持续检查基于用户能力给出的能力和更改帮助。
    • 5. 发明授权
    • Intelligent user assistance facility
    • 智能用户帮助设施
    • US6021403A
    • 2000-02-01
    • US684003
    • 1996-07-19
    • Eric HorvitzJohn S. BreeseDavid E. HeckermanSamuel D. HobsonDavid O. HovelAdrian C. KleinJacobus A. RommelseGregory L. Shaw
    • Eric HorvitzJohn S. BreeseDavid E. HeckermanSamuel D. HobsonDavid O. HovelAdrian C. KleinJacobus A. RommelseGregory L. Shaw
    • G06F9/06B82B1/00G06F3/048G06F9/44G06N5/04G06F17/20
    • G06N5/00G06F9/4446Y10S707/99943
    • An event composing and monitoring system that allows high-level events to be created from combinations of low-level events. An event specification tool, contained in the system, allows for rapidly developing a general event processor that creates high-level events from combinations of user actions. An event system, in combination with an inference system, monitors and infers, for various purposes, about several classes of events including: current program context; state of key data structures; user input sequences, including actions with a mouse-controlled cursor while interacting with a graphical user interface; words typed in free-text help queries; visual user information, such as gaze and gesture information; and user speech information. Additionally, an intelligent user interface is provided by constructing a reasoning model that computes probability of alternative user intentions, goals or information needs through analyzing information regarding program state, and that user's actions and free-text query words. Specifically, the interface monitors user interaction with a program and probabilistically reasons to sense that a user may need assistance in using a particular feature or to accomplish a specific task. This interface accepts a free-text help query from the user and combines the inference analysis of user actions and the program state with an inference analysis of the query. The inference system, using an updateable user profile, continually checks for user competencies and, based on such competencies, changes assistance that is offered.
    • 一个事件组合和监控系统,允许从低级别事件的组合创建高级别事件。 包含在系统中的事件规范工具允许快速开发通用事件处理器,它通过用户操作的组合创建高级事件。 事件系统与推理系统相结合,针对各种目的监视和推测几类事件,包括:当前程序环境; 关键数据结构状态; 用户输入序列,包括与图形用户界面交互时具有鼠标控制的光标的动作; 输入自由文本帮助查询的单词; 视觉用户信息,如凝视和姿态信息; 和用户语音信息。 另外,通过构建推理模型来提供智能用户界面,该推理模型通过分析关于程序状态的信息以及该用户的动作和自由文本查询词来计算替代用户意图,目标或信息需求的概率。 具体来说,接口监视用户与程序的交互,并且概率地认为用户可能需要协助使用特定特征或完成特定任务。 该接口接受来自用户的自由文本帮助查询,并将用户操作的推理分析和程序状态与查询的推断分析相结合。 推理系统使用可更新的用户配置文件,不断检查用户能力,并根据这些能力来更改提供的帮助。
    • 6. 发明授权
    • Collaborative filtering utilizing a belief network
    • 利用信念网络进行协同过滤
    • US5704017A
    • 1997-12-30
    • US602238
    • 1996-02-16
    • David E. HeckermanJohn S. BreeseEric HorvitzDavid Maxwell Chickering
    • David E. HeckermanJohn S. BreeseEric HorvitzDavid Maxwell Chickering
    • G06Q30/02G06F17/00
    • H04N21/252G06Q30/02
    • The disclosed system provides an improved collaborative filtering system by utilizing a belief network, which is sometimes known as a Bayesian network. The disclosed system learns a belief network using both prior knowledge obtained from an expert in a given field of decision making and a database containing empirical data obtained from many people. The empirical data contains attributes of users as well as their preferences in the field of decision making. After initially learning the belief network, the belief network is relearned at various intervals when additional attributes are identified as having a causal effect on the preferences and data for these additional attributes can be gathered. This relearning allows the belief network to improve its accuracy at predicting preferences of a user. Upon each iteration of relearning, a cluster model is automatically generated that best predicts the data in the database. After relearning the belief network a number of times, the belief network is used to predict the preferences of a user using probabilistic inference. In performing probabilistic inference, the known attributes of a user are received and the belief network is accessed to determine the probability of the unknown preferences of the user given the known attributes. Based on these probabilities, the preference most likely to be desired by the user can be predicted.
    • 所公开的系统通过利用有时被称为贝叶斯网络的置信网络来提供改进的协同过滤系统。 所公开的系统使用从给定的决策领域的专家获得的现有知识和包含从许多人获得的经验数据的数据库来学习信念网络。 实证数据包含用户的属性以及决策领域的偏好。 在最初学习信念网络之后,当附加属性被识别为对偏好具有因果影响并且可以收集这些附加属性的数据时,信念网络以不同的间隔被重新学习。 这种再学习允许信念网络在预测用户的偏好时提高其准确性。 在重新学习的每次迭代之后,自动生成最能预测数据库中的数据的集群模型。 在重新学习信念网络多次之后,信念网络用于使用概率推理来预测用户的偏好。 在执行概率推理时,接收用户的已知属性,并且访问置信网络以确定给定已知属性的用户的未知偏好的概率。 基于这些概率,可以预测用户最可能希望的偏好。