公开(公告)号：US20110125732A1

公开(公告)日：2011-05-26

申请号：US12625558

申请日：2009-11-25

Applicant: Yauhen Shnitko ,  Dmitriy Meyerzon ,  Vladimir V. Tankovich

Inventor： Yauhen Shnitko ,  Dmitriy Meyerzon ,  Vladimir V. Tankovich

IPC: G06F17/30 ,  G06N3/02

CPC classification number: G06F17/30675 ,  G06F17/30864

Abstract: A markup language schema utilized to represent internal ranking models. In one implementation, the schema developed utilizes XML (extensible markup language) for internal ranking model representation. Other markups languages can be employed.

Abstract translation: 用于表示内部排名模型的标记语言模式。 在一个实现中，开发的模式利用XML（可扩展标记语言）进行内部排名模型表示。 可以使用其他标记语言。

公开(公告)号：US07853587B2

公开(公告)日：2010-12-14

申请号：US12023678

申请日：2008-01-31

Applicant: Dirk Groeneveld ,  Dmitriy Meyerzon ,  David Mowatt

Inventor： Dirk Groeneveld ,  Dmitriy Meyerzon ,  David Mowatt

IPC: G06F17/30

CPC classification number: G06F17/30867 ,  G06F17/30719

Abstract: Embodiments are configured to provide a summary of information associated with one or more search results. In an embodiment, a system includes a summary generator that can be configured to provide a summary of information including one or more snippets associated with a search term or search terms. The system includes a ranking component that can be used to rank snippets and the ranked snippets can be used when generating a summary that includes one or more ranked snippets. In one embodiment, the system can be configured to include one or more filters that can be used to filter snippets and the filtered snippets can be used when generating a summary. Other embodiments are available.

Abstract translation: 实施例被配置为提供与一个或多个搜索结果相关联的信息的摘要。 在一个实施例中，系统包括摘要生成器，其可以被配置为提供包括与搜索项或搜索项相关联的一个或多个片段的信息的摘要。 该系统包括可用于对片段进行排名的排名组件，并且可以在生成包含一个或多个排名片段的摘要时使用排名片段。 在一个实施例中，系统可被配置为包括一个或多个可用于过滤片段的过滤器，并且可以在生成摘要时使用经过过滤的片段。 其他实施例是可用的。

公开(公告)号：US07840569B2

公开(公告)日：2010-11-23

申请号：US11874844

申请日：2007-10-18

Applicant: Dmitriy Meyerzon ,  Yauhen Shnitko ,  Chris J. C. Burges ,  Michael James Taylor

Inventor： Dmitriy Meyerzon ,  Yauhen Shnitko ,  Chris J. C. Burges ,  Michael James Taylor

IPC: G06F17/30

CPC classification number: G06F17/30864 ,  G06N3/02

Abstract: A neural network is used to process a set of ranking features in order to determine the relevancy ranking for a set of documents or other items. The neural network calculates a predicted relevancy score for each document and the documents can then be ordered by that score. Alternate embodiments apply a set of data transformations to the ranking features before they are input to the neural network. Training can be used to adapt both the neural network and certain of the data transformations to target environments.

Abstract translation: 神经网络用于处理一组排名特征，以便确定一组文档或其他项目的相关性排名。 神经网络计算每个文档的预测相关性分数，然后可以通过该分数排序文档。 替代实施例在排序特征被输入到神经网络之前将一组数据变换应用于排序特征。 训练可以用来适应神经网络和某些数据转换到目标环境。

公开(公告)号：US07792833B2

公开(公告)日：2010-09-07

申请号：US11412723

申请日：2006-04-26

Applicant: Dmitriy Meyerzon ,  Hugo Zaragoza

Inventor： Dmitriy Meyerzon ,  Hugo Zaragoza

IPC: G06F17/30

CPC classification number: G06F17/30867 ,  G06F17/30699

Abstract: Search results of a search query on a network are ranked according to an additional ranking function for the prior probability of relevance of a document based on document property. The ranking function can be adjusted based on a comparison of the language that a document is written in and the language that is associated with a search query. Both query-independent values and query-dependent values can be used to rank the document.

Abstract translation: 根据基于文档属性的文档相关先前概率的附加排序函数对网络上的搜索查询的搜索结果进行排序。 可以基于写入文档的语言与与搜索查询相关联的语言的比较来调整排名功能。 可以使用查询无关值和与查询相关的值来对文档进行排名。

公开(公告)号：US20100121838A1

公开(公告)日：2010-05-13

申请号：US12690100

申请日：2010-01-19

Applicant: Vladimir Tankovich ,  Dmitriy Meyerzon ,  Mihai Petriuc

Inventor： Vladimir Tankovich ,  Dmitriy Meyerzon ,  Mihai Petriuc

IPC: G06F17/30

CPC classification number: G06F17/30864

Abstract: Technologies are described herein for providing a more efficient approach to ranking search results. An illustrative technology reduces an amount of ranking data analyzed at query time. In the technology, a term is selected, at index time, from a master index. The term corresponds to a number of documents greater than a threshold. A set of documents that includes the term is selected based on the master index. A rank is determined for each document in the set of documents that contains the term. Each document in the set of documents that contains the term is assigned to a top document list or a bottom document list based on the rank. Predefined values of at least part of the rank are stored in the top document list for documents in the top document list and are not stored in the bottom document list for documents in the bottom document list.

Abstract translation: 本文描述了技术，以提供用于对搜索结果进行排名的更有效的方法。 说明性技术减少了在查询时间分析的排名数据量。 在技​​术中，在索引时间，从主索引中选择一个术语。 该术语对应于大于阈值的多个文档。 根据主索引选择一组包含该术语的文档。 在包含该术语的文档集中的每个文档确定排名。 包含该术语的文档集中的每个文档都会根据排名分配给顶级文档列表或底部文档列表。 至少部分等级的预定义值存储在顶部文档列表中的文档的顶部文档列表中，并且不存储在底部文档列表中的文档的底部文档列表中。

公开(公告)号：US20100017403A1

公开(公告)日：2010-01-21

申请号：US12569028

申请日：2009-09-29

Applicant: Chadd Creighton Merrigan ,  Kyle G. Peltonen ,  Dmitriy Meyerzon ,  David J. Lee

Inventor： Chadd Creighton Merrigan ,  Kyle G. Peltonen ,  Dmitriy Meyerzon ,  David J. Lee

IPC: G06F17/30

CPC classification number: G06F17/30864 ,  G06F17/30967 ,  Y10S707/99931 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99936 ,  Y10S707/99943

Abstract: A set of index keys is included in an index search system that are associated with the scope of the search rather than the content of the documents that are the target of the search. These scope related index keys, or scope keys allows the scope of the search to be selected, reducing the number of documents that a search is required to sift through to obtain results. Furthermore, compound scopes are recognized and stored such that an index of complex search scopes is provided to eliminate rehashing of the searches based on these complex search scopes.

Abstract translation: 一组索引关键字被包括在与搜索范围相关联的索引搜索系统中，而不是作为搜索目标的文档的内容。 这些范围相关的索引键或范围键允许选择搜索的范围，减少搜索需要筛选以获得结果的文档数量。 此外，识别和存储复合范围，使得提供复杂搜索范围的索引以消除基于这些复杂搜索范围的搜索的重新排列。

公开(公告)号：US07606793B2

公开(公告)日：2009-10-20

申请号：US10951123

申请日：2004-09-27

Applicant: Chadd Creighton Merrigan ,  Kyle G. Peltonen ,  Dmitriy Meyerzon ,  David J. Lee

Inventor： Chadd Creighton Merrigan ,  Kyle G. Peltonen ,  Dmitriy Meyerzon ,  David J. Lee

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30864 ,  G06F17/30967 ,  Y10S707/99931 ,  Y10S707/99932 ,  Y10S707/99933 ,  Y10S707/99936 ,  Y10S707/99943

Abstract: A set of index keys is included in an index search system that are associated with the scope of the search rather than the content of the documents that are the target of the search. These scope related index keys, or scope keys allows the scope of the search to be selected, reducing the number of documents that a search is required to sift through to obtain results. Furthermore, compound scopes are recognized and stored such that an index of complex search scopes is provided to eliminate rehashing of the searches based on these complex search scopes.

Abstract translation: 一组索引关键字被包括在与搜索范围相关联的索引搜索系统中，而不是作为搜索目标的文档的内容。 这些范围相关的索引键或范围键允许选择搜索的范围，减少搜索需要筛选以获得结果的文档数量。 此外，识别和存储复合范围，使得提供复杂搜索范围的索引以消除基于这些复杂搜索范围的搜索的重新排列。

公开(公告)号：US20090259651A1

公开(公告)日：2009-10-15

申请号：US12101951

申请日：2008-04-11

Applicant: Vladimir Tankovich ,  Hang Li ,  Dmitriy Meyerzon ,  Jun Xu

Inventor： Vladimir Tankovich ,  Hang Li ,  Dmitriy Meyerzon ,  Jun Xu

IPC: G06F17/30

CPC classification number: G06F17/2211 ,  G06F17/30864

Abstract: Architecture for extracting document information from documents received as search results based on a query string, and computing an edit distance between the data string and the query string. The edit distance is employed in determining relevance of the document as part of result ranking by detecting near-matches of a whole query or part of the query. The edit distance evaluates how close the query string is to a given data stream that includes document information such as TAUC (title, anchor text, URL, clicks) information, etc. The architecture includes the index-time splitting of compound terms in the URL to allow the more effective discovery of query terms. Additionally, index-time filtering of anchor text is utilized to find the top N anchors of one or more of the document results. The TAUC information can be input to a neural network (e.g., 2-layer) to improve relevance metrics for ranking the search results.

Abstract translation: 用于基于查询字符串从作为搜索结果接收的文档提取文档信息的结构，以及计算数据串和查询字符串之间的编辑距离。 编辑距离用于通过检测整个查询或部分查询的近似匹配来确定文档作为结果排名的一部分的相关性。 编辑距离评估查询字符串与包含诸如TAUC（标题，锚文本，URL，点击）信息等文档信息的给定数据流的距离。该体系结构包括索引时间分割URL中的复合术语 以便更有效地发现查询条款。 另外，使用锚文本的索引时间过滤来查找一个或多个文档结果的前N个锚点。 可以将TAUC信息输入到神经网络（例如，2层），以改进用于对搜索结果排序的相关性度量。

公开(公告)号：US07603616B2

公开(公告)日：2009-10-13

申请号：US10981962

申请日：2004-11-05

Applicant: Kenji Obata ,  Dmitriy Meyerzon

Inventor： Kenji Obata ,  Dmitriy Meyerzon

IPC: G06F17/30

CPC classification number: G06F17/30864 ,  Y10S707/99931 ,  Y10S707/99933

Abstract: A computer based system and method of determining whether to re-fetch a previously retrieved document across a computer network is disclosed. The method utilizes a statistical model to determine whether the previously retrieved document likely changed since last accessed. The statistical model is continuously improving its accuracy by training internal probability distributions to reflect the actual experience with change rate patterns of the documents accessed. The decision of whether to access the document is based on the probability of change compared against a desired synchronization level, random selections, maximum limits on the amount of time since the document was last accessed, and other criterion. Once the decision to access is made, the document is checked for changes and this information is used to train the statistical model.

Abstract translation: 公开了一种基于计算机的系统和方法，用于确定是否通过计算机网络重新获取先前检索的文档。 该方法利用统计模型来确定先前检索的文档自上次访问以来是否可能改变。 统计模型通过训练内部概率分布来不断提高其准确性，以反映所访问文件的变化率模式的实际经验。 是否访问文档的决定是基于与期望的同步级别进行比较的更改概率，随机选择，自上次访问文档以来的时间量的最大限制以及其他标准。 一旦作出决定，将对文件进行更改检查，并将此信息用于训练统计模型。

公开(公告)号：US20090240680A1

公开(公告)日：2009-09-24

申请号：US12051847

申请日：2008-03-20

Applicant: Vladimir Tankovich ,  Dmitriy Meyerzon ,  Michael Taylor ,  Stephen Robertson

Inventor： Vladimir Tankovich ,  Dmitriy Meyerzon ,  Michael Taylor ,  Stephen Robertson

IPC: G06F17/30

CPC classification number: G06F17/3053

Abstract: Techniques to perform relative ranking for search results are described. An apparatus may include an enhanced search component operative to receive a search query and provide ranked search results responsive to the search query. The enhanced search component may comprise a resource search module operative to search for resources using multiple search terms from the search query, and output a set of resources having some or all of the search terms. The enhanced search component may also comprise a proximity generation module communicatively coupled to the resource search module, the proximity generation module operative to receive the set of resources, retrieve search term position information for each resource, and generate a proximity feature value based on the search term position information. The enhanced search component may further comprise a resource ranking module communicatively coupled to the resource search module and the proximity generation module, the resource ranking module to receive the proximity feature values, and rank the resources based in part on the proximity feature values. Other embodiments are described and claimed.

Abstract translation: 描述了对搜索结果执行相对排名的技术。 装置可以包括增强的搜索组件，其操作以接收搜索查询并且响应于搜索查询提供排名的搜索结果。 增强搜索组件可以包括资源搜索模块，其可操作以使用来自搜索查询的多个搜索项来搜索资源，并且输出具有部分或全部搜索项的一组资源。 增强搜索组件还可以包括通信地耦合到资源搜索模块的邻近生成模块，用于接收资源集合的邻近生成模块，检索每个资源的搜索项位置信息，以及基于搜索生成接近特征值 期限位置信息。 增强搜索组件还可以包括资源排序模块，其通信地耦合到资源搜索模块和邻近生成模块，用于接收邻近特征值的资源排名模块，以及部分地基于邻近特征值对资源进行排名。 描述和要求保护其他实施例。