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    Promoting strategic documents by bias ranking of search results on a web browser
    1.
    发明授权
    Promoting strategic documents by bias ranking of search results on a web browser 有权
    通过网页浏览器的搜索结果偏好排序来提升战略文件

    公开(公告)号：US08117072B2

    公开(公告)日：2012-02-14

    申请号：US10120071

    申请日：2002-04-10

    申请人： Moon Ju Kim ,  Juan-Leon Rodriguez ,  Yurdaer Nezihi Doganata ,  Youssef Drissi ,  Lev Kozakov

    发明人： Moon Ju Kim ,  Juan-Leon Rodriguez ,  Yurdaer Nezihi Doganata ,  Youssef Drissi ,  Lev Kozakov

    IPC分类号： G06Q30/00

    CPC分类号： G06Q30/02 ,  G06Q30/0241 ,  G06Q30/0601 ,  G06Q30/0633

    摘要： A method, software and apparatus are provided which enable a user to obtain products and services in a manner which counteracts conflicting actions modifying raw ranking data based on merchants interests. For this purpose, an information a user's web browser is provided with modules that modify search results obtained from one or more sources including directly from merchants. When the user enters a set of key words in an entry field in an on-screen form for a web server to obtain a list of items (products and/or services) of interest to the user, the search terms are modified in the users or his agents browser to reflect the interest of the user, his management or his parents. The user or his agent receives ranking information taking the highest ranked products and obtains the product information for the most highly ranked products. The browser then reranks the products using a ranking algorithm preferred by the user that offsets information sources biases in the ranking of the product information. The algorithm adds weighting factors reflecting the modified search terms. The weighting factors are combined with the mentioned ranking mechanisms to the documents to increase the probability that certain items come to the top when the search results are presented to the shopper.

    摘要翻译： 提供了一种方法，软件和装置，其使得用户能够以抵消基于商家兴趣修改原始排名数据的冲突动作的方式获得产品和服务。 为此，用户的Web浏览器的信息被提供有模块，其修改从直接来自商家的一个或多个来源获得的搜索结果。 当用户在用于web服务器的屏幕上的输入字段中输入一组关键词以获得用户感兴趣的项目（产品和/或服务）的列表时，在用户中修改搜索项 或他的代理浏览器来反映用户，他的管理层或他的父母的兴趣。 用户或其代理人收到排名最高的产品的排名信息，并获得最高排名的产品的产品信息。 然后，浏览器使用用户偏好的排序算法来重新排列产品，以抵消信息源在产品信息的排名中的偏差。 该算法添加了反映修改的搜索项的加权因子。 加权因子与提到的文件排序机制结合起来，以便在将搜索结果呈现给购物者时增加某些项目到达顶部的可能性。

    Dynamic comparison of search systems in a controlled environment
    2.
    发明授权
    Dynamic comparison of search systems in a controlled environment 失效
    在受控环境中搜索系统的动态比较

    公开(公告)号：US07483877B2

    公开(公告)日：2009-01-27

    申请号：US10412808

    申请日：2003-04-11

    申请人： Moon Ju Kim ,  Yurdaer Nezihi Doganata ,  Youssef Drissi ,  Lev Kozakov

    发明人： Moon Ju Kim ,  Yurdaer Nezihi Doganata ,  Youssef Drissi ,  Lev Kozakov

    IPC分类号： G06F17/30

    CPC分类号： G06F17/3069 ,  G06F17/30864 ,  Y10S707/99933 ,  Y10S707/99943 ,  Y10S707/99945

    摘要： A random document is stripped of the relevant search terms to generate a non-relevant document. The relevant search terms are formed into grammatically correct but not necessarily technically correct sentences. The grammatically correct sentences are placed at the beginning of the random document in one pass through the system in the middle of a document in a second pass through the system and at the end of the document in a third pass through the system. A relevancy vector chart is computed using the references documents and a known relevancy algorithm relating to position of search terms. The results obtained from search engines are compared to the relevancy vector chart to determine the relative relevancy of the returned search results from the search engines.

    摘要翻译： 随机文件被剥离相关的搜索条件，以生成不相关的文档。 相关搜索词形成为语法正确但不一定是技术上正确的句子。 语法上正确的句子被放置在随机文档的开头，在通过系统的第二遍中的文档中间的一次通过系统中，并且在文档的最后通过系统的第三遍。 使用参考文献和与搜索词的位置相关的已知相关性算法计算相关性矢量图。 将搜索引擎获得的结果与相关矢量图进行比较，以确定搜索引擎返回的搜索结果的相对关系。

    Optimization of server selection using euclidean analysis of search terms
    5.
    发明授权
    Optimization of server selection using euclidean analysis of search terms 失效
    优化服务器选择使用欧几里得分析搜索词

    公开(公告)号：US07143085B2

    公开(公告)日：2006-11-28

    申请号：US10209619

    申请日：2002-07-31

    申请人： Gregory T. Brown ,  Youssef Drissi ,  Moon Ju Kim ,  Lev Kozakov ,  Juan Leon-Rodriquez ,  Ricardo Vilalta

    发明人： Gregory T. Brown ,  Youssef Drissi ,  Moon Ju Kim ,  Lev Kozakov ,  Juan Leon-Rodriquez ,  Ricardo Vilalta

    IPC分类号： G06F7/00

    CPC分类号： G06F17/30864 ,  G06F17/30657 ,  Y10S707/99931 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99936 ,  Y10S707/99937

    摘要： Euclidean analysis is used to define queries in terms of a multi-axis query space where each of the keywords T1, T2, . . . Ti, . . . Tn is assigned an axis in that space. Sets of test queries St for each one from one of a plurality of server sources, are plotted in the query space. Clusters of the search terms are identified based on the proximity of the plotted query vectors to one another. Predominant servers are identified for each of the clusters. When a search query Ss is received, the location of its vector is determined and the servers accessed by the search query Ss are those that are predominant in the cluster which its vector may fall or is in closest proximity to.

    摘要翻译： 欧几里德分析用于根据多轴查询空间来定义查询，其中每个关键字T 1，T 2，...。 。 。 。。。。。。。。。。。。 。 。 在该空间中分配了一个轴。 在多个服务器源中的一个服务器源中的每​​一个的测试查询集合被绘制在查询空间中。 基于绘制的查询向量彼此的邻近度来识别搜索项的群集。 为每个集群标识主要服务器。 当接收到搜索查询S 时，确定其向量的位置，并且由搜索查询S 访问的服务器是在群集中占主导地位的那些 矢量可能会下降或最接近。

    Method, system and program product for detecting deviation from software development best practice resource in a code sharing system
    6.
    发明授权
    Method, system and program product for detecting deviation from software development best practice resource in a code sharing system 失效
    用于在代码共享系统中检测与软件开发最佳实践资源的偏差的方法，系统和程序产品

    公开(公告)号：US07647579B2

    公开(公告)日：2010-01-12

    申请号：US10814925

    申请日：2004-03-31

    申请人： Youssef Drissi ,  Tong-Haing Fin ,  Moon Ju Kim ,  Lev Kozakov ,  Juan Leon Rodriguez

    发明人： Youssef Drissi ,  Tong-Haing Fin ,  Moon Ju Kim ,  Lev Kozakov ,  Juan Leon Rodriguez

    IPC分类号： G06F9/44

    CPC分类号： G06F8/36

    摘要： Under the present invention, a best practice violation (BPV) engine resource is first built. This typically occurs by: receiving sets of source code from a plurality of sources; detecting a programming language of each of the sets of source code; extracting code patterns from the sets of source code; defining meta data for each code pattern that indicates a quality; classifying each code pattern; and assigning a rank to each of the code pattern based on its corresponding meta data as well as a skill level and an experience level of the developer. Once the BPV engine resource is built, it will be used to detect best practice violations in other sets of source code.

    摘要翻译： 根据本发明，首先构建最佳实践违规（BPV）引擎资源。 这通常发生在：从多个源接收源代码集合; 检测每个源代码集的编程语言; 从源代码集中提取代码模式; 为指示质量的每个代码模式定义元数据; 对每个代码模式进行分类; 并且基于其对应的元数据以及开发者的技能水平和经验水平为每个代码模式分配等级。 一旦构建了BPV引擎资源，它将被用于检测其他源代码集中的最佳实践违规。