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
    • 1. 发明授权
    • Widget searching utilizing task framework
    • 小部件搜索利用任务框架
    • US07996783B2
    • 2011-08-09
    • US11367292
    • 2006-03-02
    • William D. RamseySanjeev Katariya
    • William D. RamseySanjeev Katariya
    • G06F3/048
    • G06F17/30893
    • A task framework and a semantic reasoning engine are combined to provide a scalable mechanism for dealing with extremely large numbers of widgets, allowing users to both find a widget and automatically fill-in whatever functionality is available on the widget. Calling applications are employed to obtain task information from each widget. The calling application also receives user queries that can be resolved by a widget. A task reasoning process based on an adaptive semantic reasoning engine utilizes the task information to select a widget best suited to respond to a user's query. The task reasoning process can also be employed to determine “best-guess” slot filling of the selected widget. The calling application can then invoke the selected widget and, if available, fill appropriate slots with information to facilitate user interaction with the selected widget. Instances can be client- and/or server-side based.
    • 组合任务框架和语义推理引擎以提供可扩展的机制来处理极大数量的小部件,从而允许用户找到小部件,并自动填充小部件上可用的任何功能。 采用呼叫应用程序从每个小部件获取任务信息。 呼叫应用程序还接收可由窗口小部件解析的用户查询。 基于自适应语义推理引擎的任务推理过程利用任务信息来选择最适合于响应用户查询的小部件。 任务推理过程也可以用于确定所选小部件的“最佳猜测”插槽填充。 呼叫应用程序然后可以调用所选择的窗口小部件,并且如果可用,则填充具有信息的适当插槽以便于用户与所选择的窗口小部件交互。 实例可以是客户端和/或服务器端。
    • 4. 发明申请
    • Adaptive semantic platform architecture
    • 自适应语义平台架构
    • US20070203869A1
    • 2007-08-30
    • US11363747
    • 2006-02-28
    • William D. RamseySanjeev KatariyaJun LiuJianfeng GaoQi YaoZhanliang Chen
    • William D. RamseySanjeev KatariyaJun LiuJianfeng GaoQi YaoZhanliang Chen
    • G06N7/02
    • G06F17/279
    • An adaptive shared infrastructure that can be easily utilized to enable natural interaction between user(s) and machine system(s) is provided. Additionally, the novel innovation can provide interactive techniques that produce accurate intent-to-action mapping based upon a user input. Further, the innovation can provide novel mechanism by which assets (e.g., documents, actions) can be authored. The authoring mechanisms can enable the generation of learning models such that the system can infer a user intent based at least in part upon an analysis of a user input. In response thereto, the system can discover an asset, or group of assets based upon the inference. Moreover, the innovation can provide a natural language interface that learns and/or adapts based upon one or more user input(s), action(s), and/or state(s).
    • 提供了可以容易地利用以实现用户和机器系统之间的自然交互的自适应共享基础设施。 此外,新颖的创新可以提供基于用户输入产生准确的意图 - 动作映射的交互技术。 此外,创新可以提供可以创作资产(例如,文档,动作)的新颖机制。 创作机制可以实现学习模型的产生,使得系统至少部分地基于对用户输入的分析来推断用户意图。 作为响应,系统可以基于推论发现资产或资产组。 此外,创新可以提供基于一个或多个用户输入,动作和/或状态来学习和/或适应的自然语言界面。
    • 8. 发明授权
    • Adaptive semantic reasoning engine
    • 自适应语义推理引擎
    • US07822699B2
    • 2010-10-26
    • US11290076
    • 2005-11-30
    • Sanjeev KatariyaQi Steven YaoJun LiuWilliam D. RamseyJianfeng Gao
    • Sanjeev KatariyaQi Steven YaoJun LiuWilliam D. RamseyJianfeng Gao
    • G06N5/00G06F17/00
    • G06F17/30663
    • Provided is an adaptive semantic reasoning engine that receives a natural language query, which may contain one or more contexts. The query can be broken down into tokens or a set of tokens. A task search can be performed on the token or token set(s) to classify a particular query and/or context and retrieve one or more tasks. The token or token set(s) can be mapped into slots to retrieve one or more task result. A slot filling goodness may be determined that can include scoring each task search result and/or ranking the results in a different order than the order in which the tasks were retrieved. The token or token set(s), retrieved tasks, slot filling goodness, natural language query, context, search result score and/or result ranking can be feedback to the reasoning engine for further processing and/or machine learning.
    • 提供了一种自适应语义推理引擎,其接收可以包含一个或多个上下文的自然语言查询。 该查询可以分为令牌或一组令牌。 可以对令牌或令牌集执行任务搜索以对特定查询和/或上下文进行分类并检索一个或多个任务。 令牌或令牌集可被映射到插槽中以检索一个或多个任务结果。 可以确定插槽填充质量,其可以包括对每个任务搜索结果进行评分和/或以与检索任务的顺序不同的顺序对结果进行排序。 令牌或令牌集,检索任务,插槽填充良品,自然语言查询,上下文,搜索结果分数和/或结果排名可以反馈到推理引擎用于进一步处理和/或机器学习。
    • 9. 发明授权
    • Distributed named entity recognition architecture
    • 分布式命名实体识别架构
    • US07814092B2
    • 2010-10-12
    • US11249982
    • 2005-10-13
    • William D. RamseySanjeev Katariya
    • William D. RamseySanjeev Katariya
    • G06F7/00G06F17/30
    • G06F17/278
    • A computer-implemented method of performing named entity recognition in a client-server environment includes providing a first named entity recognition module operable with a client machine in the client-server environment and a second named entity recognition module operable with a server in the client-server environment. The method also includes performing named entity recognition on the client machine to identify one or more domain dependent named entities in a set of tokens and data assessable to the client machine and performing named entity recognition on the server to identify one or more domain independent named entities in the set of tokens and data assessable to the server. A task is completed using at least information related to the identified named entities from the client machine and the server.
    • 在客户机 - 服务器环境中执行命名实体识别的计算机实现的方法包括提供可与客户机 - 服务器环境中的客户端机器一起操作的第一命名实体识别模块和可与客户端 - 服务器环境中的服务器一起操作的第二命名实体识别模块, 服务器环境。 该方法还包括在客户端计算机上执行命名实体识别以识别一组令牌中的一个或多个依赖域名的命名实体和可评估给客户机的数据,并在服务器上执行命名实体识别以识别一个或多个域独立的命名实体 在一组令牌和数据可评估到服务器。 使用至少与来自客户机和服务器的所识别的命名实体相关的信息完成任务。