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    • 1. 发明申请
    • SELF-TUNING ALTERATIONS FRAMEWORK
    • 自调整框架
    • US20130346400A1
    • 2013-12-26
    • US13528411
    • 2012-06-20
    • WILLIAM D. RAMSEYBENOIT DUMOULINNICHOLAS ERIC CRASWELL
    • WILLIAM D. RAMSEYBENOIT DUMOULINNICHOLAS ERIC CRASWELL
    • G06F17/30
    • G06F17/30864
    • Embodiment described herein are directed to an enhanced search engine with multiple feedback loops for providing optimal search results that are responsive a user's search query. The user's search query is parsed, and based on the underlying terms, different linguistic models and refinement techniques generate alternative candidate search queries that may yield better results. Searches are performed for the original search query and the candidate search queries, and different scores are used to select the best search results to present to the user. Results making it onto the list, as well as the underlying candidate search query, linguistic model, or refinement technique for generating that search query, will have their corresponding scores updated to reflect their success of generating a search result. Scores are stored and used by future searches to come up with better results.
    • 本文描述的实施例涉及具有多个反馈回路的增强搜索引擎,用于提供响应用户搜索查询的最佳搜索结果。 用户的搜索查询被解析,并且基于基础术语,不同的语言模型和细化技术产生可能产生更好结果的替代候选搜索查询。 对原始搜索查询和候选搜索查询执行搜索,并且使用不同的分数来选择要呈现给用户的最佳搜索结果。 将其列入列表的结果以及用于生成该搜索查询的底层候选搜索查询,语言模型或细化技术将更新其相应的分数,以反映其生成搜索结果的成功。 未来的搜索记录和使用得分可以获得更好的结果。
    • 2. 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。
    • 6. 发明授权
    • Method and apparatus for identifying semantic structures from text
    • 从文本中识别语义结构的方法和装置
    • US07593845B2
    • 2009-09-22
    • US10679556
    • 2003-10-06
    • William D. Ramsey
    • William D. Ramsey
    • G06F17/27
    • G06F17/2785G06F17/2715Y10S707/99933Y10S707/99936
    • A method and apparatus for identifying a semantic structure from an input text forms at least two candidate semantic structures. A semantic score is determined for each candidate semantic structure based on the likelihood of the semantic structure. A syntactic score is also determined for each semantic structure based on the position of a word in the text and the position in the semantic structure of a semantic entity formed from the word. The syntactic score and the semantic score are combined to select a semantic structure for at least a portion of the text. In many embodiments, the semantic structure is built incrementally by building and scoring candidate structures for a portion of the text, pruning low scoring candidates, and adding additional semantic elements to the retained candidates.
    • 用于从输入文本识别语义结构的方法和装置形成至少两个候选语义结构。 基于语义结构的可能性,为每个候选语义结构确定语义分数。 还根据单词在文本中的位置以及从单词形成的语义实体的语义结构中的位置,为每个语义结构确定句法分数。 组合语法分数和语义分数以选择文本的至少一部分的语义结构。 在许多实施例中,通过为文本的一部分建立和评分候选结构,修剪低得分的候选以及向保留的候选者添加附加的语义元素来逐渐构建语义结构。
    • 7. 发明申请
    • GRAPHICAL APPLICATION FOR BUILDING DISTRIBUTED APPLICATIONS
    • 用于建筑分布式应用的图形应用
    • US20090119640A1
    • 2009-05-07
    • US11936105
    • 2007-11-07
    • William D. RamseyRonnie I. Chaiken
    • William D. RamseyRonnie I. Chaiken
    • G06F9/44
    • G06F8/34
    • A graphical application development tool for developing parallel computation applications. The tool facilitates insertion of computational elements by a drag-and-drop operation onto a canvas area for creating a computational graph. The graphical application tool reduces the barriers to the development of parallel computation applications by entry-level developers, for example, by allowing these users to write applications by using a graphical tool, thereby avoiding complexities of having to write well-formed code and learning a new language. The tool includes built-in functionality that allows the developer to write arbitrary code (e.g., C#) to perform various functions on massive amounts of data.
    • 用于开发并行计算应用程序的图形应用程序开发工具。 该工具便于通过拖放操作将计算元素插入到画布区域上,用于创建计算图。 图形应用程序工具减少了入门级开发人员开发并行计算应用程序的障碍,例如,允许这些用户使用图形工具编写应用程序,从而避免复杂的编写格式良好的代码和学习 新语言 该工具包括内置的功能,允许开发人员编写任意代码(例如C#)来执行大量数据的各种功能。