公开(公告)号：US08572074B2

公开(公告)日：2013-10-29

申请号：US13454637

申请日：2012-04-24

申请人： Sanaz Ahari ,  Xiaoxin Yin ,  Farid Hosseini ,  Sarthak Shah ,  Adam Troy ,  Dan Fain ,  Brian MacDonald ,  Nikhil Dandekar ,  Michael Cameron

发明人： Sanaz Ahari ,  Xiaoxin Yin ,  Farid Hosseini ,  Sarthak Shah ,  Adam Troy ,  Dan Fain ,  Brian MacDonald ,  Nikhil Dandekar ,  Michael Cameron

IPC分类号： G06F7/00 ,  G06F17/30

CPC分类号： G06F17/30864 ,  G06F7/00 ,  G06F17/30 ,  G06F17/30702 ,  G06F17/30867

摘要： Computer-readable media and computerized methods for automatically organizing search results according to task groups are provided. The methods involve aggregating a gallery of entities (e.g., search queries that share a common categorization) into a query class and assigning a dictionary (e.g., list of terms that are drawn from various sources) to the query class. The task groups are identified from the list of terms within the dictionary. The process of identification includes analyzing patterns of user search behavior to select terms from the list of terms, which reflect popular user search intents, and ranking the selected terms based on predetermined parameters to produce an ordering. Based on the ordering, a set of the selected terms that are highest ranked are declared the task groups. The task groups are employed to arrange the search results on a UI display and to provide a consistent and intuitive format for refining a search.

摘要翻译： 提供了根据任务组自动组织搜索结果的计算机可读介质和计算机化方法。 这些方法包括将实体库（例如，共享公共分类的搜索查询）聚合到查询类中并将查询类别的字典（例如，从各种来源绘制的术语列表）分配。 任务组从字典中的术语列表中识别。 识别过程包括分析用户搜索行为的模式以从反映流行用户搜索意图的术语列表中选择术语，并且基于预定参数对所选项进行排序以产生排序。 根据排序，将排列最高的选定术语集合声明为任务组。 任务组用于在UI显示器上排列搜索结果，并提供一致和直观的格式来完善搜索。

公开(公告)号：US20120209835A1

公开(公告)日：2012-08-16

申请号：US13454637

申请日：2012-04-24

申请人： Sanaz Ahari ,  Xiaoxin Yin ,  Farid Hosseini ,  Sarthak Shah ,  Adam Troy ,  Dan Fain ,  Brian MacDonald ,  Nikhil Dandekar ,  Michael Cameron

发明人： Sanaz Ahari ,  Xiaoxin Yin ,  Farid Hosseini ,  Sarthak Shah ,  Adam Troy ,  Dan Fain ,  Brian MacDonald ,  Nikhil Dandekar ,  Michael Cameron

IPC分类号： G06F17/30

CPC分类号： G06F17/30864 ,  G06F7/00 ,  G06F17/30 ,  G06F17/30702 ,  G06F17/30867

摘要： Computer-readable media and computerized methods for automatically organizing search results according to task groups are provided. The methods involve aggregating a gallery of entities (e.g., search queries that share a common categorization) into a query class and assigning a dictionary (e.g., list of terms that are drawn from various sources) to the query class. The task groups are identified from the list of terms within the dictionary. The process of identification includes analyzing patterns of user search behavior to select terms from the list of terms, which reflect popular user search intents, and ranking the selected terms based on predetermined parameters to produce an ordering. Based on the ordering, a set of the selected terms that are highest ranked are declared the task groups. The task groups are employed to arrange the search results on a UI display and to provide a consistent and intuitive format for refining a search.

摘要翻译： 提供了根据任务组自动组织搜索结果的计算机可读介质和计算机化方法。 这些方法包括将实体库（例如，共享公共分类的搜索查询）聚合到查询类中并将查询类别的字典（例如，从各种来源绘制的术语列表）分配。 任务组从字典中的术语列表中识别。 识别过程包括分析用户搜索行为的模式以从反映流行用户搜索意图的术语列表中选择术语，并且基于预定参数对所选项进行排序以产生排序。 根据排序，将排列最高的选定术语集合声明为任务组。 任务组用于在UI显示器上排列搜索结果，并提供一致和直观的格式来完善搜索。

公开(公告)号：US20100299343A1

公开(公告)日：2010-11-25

申请号：US12471116

申请日：2009-05-22

申请人： Sanaz Ahari ,  Xiaoxin Yin ,  Farid Hosseini ,  Sarthak Shah ,  Adam Troy ,  Daniel C. Fain ,  Brian MacDonald ,  Nikhil Dandekar ,  Michael Cameron

发明人： Sanaz Ahari ,  Xiaoxin Yin ,  Farid Hosseini ,  Sarthak Shah ,  Adam Troy ,  Daniel C. Fain ,  Brian MacDonald ,  Nikhil Dandekar ,  Michael Cameron

IPC分类号： G06F17/30

CPC分类号： G06F17/30864 ,  G06F7/00 ,  G06F17/30 ,  G06F17/30702 ,  G06F17/30867

摘要： Computer-readable media and computerized methods for automatically organizing search results according to task groups are provided. The methods involve aggregating a gallery of entities (e.g., search queries that share a common categorization) into a query class and assigning a dictionary (e.g., list of terms that are drawn from various sources) to the query class. The task groups are identified from the list of terms within the dictionary. The process of identification includes analyzing patterns of user search behavior to select terms from the list of terms, which reflect popular user search intents, and ranking the selected terms based on predetermined parameters to produce an ordering. Based on the ordering, a set of the selected terms that are highest ranked are declared the task groups. The task groups are employed to arrange the search results on a UI display and to provide a consistent and intuitive format for refining a search.

摘要翻译： 提供了根据任务组自动组织搜索结果的计算机可读介质和计算机化方法。 这些方法包括将实体库（例如，共享公共分类的搜索查询）聚合到查询类中并将查询类别的字典（例如，从各种来源绘制的术语列表）分配。 任务组从字典中的术语列表中识别。 识别过程包括分析用户搜索行为的模式以从反映流行用户搜索意图的术语列表中选择术语，并且基于预定参数对所选项进行排序以产生排序。 根据排序，将排列最高的选定术语集合声明为任务组。 任务组被用于在UI显示器上排列搜索结果，并提供一致和直观的格式来完善搜索。

公开(公告)号：US08190601B2

公开(公告)日：2012-05-29

申请号：US12471116

申请日：2009-05-22

申请人： Sanaz Ahari ,  Xiaoxin Yin ,  Farid Hosseini ,  Sarthak Shah ,  Adam Troy ,  Daniel C. Fain ,  Brian MacDonald ,  Nikhil Dandekar ,  Michael Cameron

发明人： Sanaz Ahari ,  Xiaoxin Yin ,  Farid Hosseini ,  Sarthak Shah ,  Adam Troy ,  Daniel C. Fain ,  Brian MacDonald ,  Nikhil Dandekar ,  Michael Cameron

IPC分类号： G06F7/00 ,  G06F17/30

CPC分类号： G06F17/30864 ,  G06F7/00 ,  G06F17/30 ,  G06F17/30702 ,  G06F17/30867

摘要： Computer-readable media and computerized methods for automatically organizing search results according to task groups are provided. The methods involve aggregating a gallery of entities (e.g., search queries that share a common categorization) into a query class and assigning a dictionary (e.g., list of terms that are drawn from various sources) to the query class. The task groups are identified from the list of terms within the dictionary. The process of identification includes analyzing patterns of user search behavior to select terms from the list of terms, which reflect popular user search intents, and ranking the selected terms based on predetermined parameters to produce an ordering. Based on the ordering, a set of the selected terms that are highest ranked are declared the task groups. The task groups are employed to arrange the search results on a UI display and to provide a consistent and intuitive format for refining a search.

摘要翻译： 提供了根据任务组自动组织搜索结果的计算机可读介质和计算机化方法。 这些方法包括将实体库（例如，共享公共分类的搜索查询）聚合到查询类中并将查询类别的字典（例如，从各种来源绘制的术语列表）分配。 任务组从字典中的术语列表中识别。 识别过程包括分析用户搜索行为的模式以从反映流行用户搜索意图的术语列表中选择术语，并且基于预定参数对所选项进行排序以产生排序。 根据排序，将排列最高的选定术语集合声明为任务组。 任务组用于在UI显示器上排列搜索结果，并提供一致和直观的格式来完善搜索。

公开(公告)号：US20120150838A1

公开(公告)日：2012-06-14

申请号：US12962677

申请日：2010-12-08

申请人： Xiaoxin Yin ,  Wenzhao Tan ,  Chao Liu

发明人： Xiaoxin Yin ,  Wenzhao Tan ,  Chao Liu

IPC分类号： G06F17/30

CPC分类号： G06F17/30864

摘要： Technologies pertaining to fact lookup queries are described herein. A relational database is automatically built by extracting attribute identities and attribute values from a one dimensional table, wherein the one dimensional table does not include an entity identity that corresponds to the attribute identity and the attribute value. The entity identity is inferred, and the attribute value is indexed in a relational database by the entity identity and the attribute identity. When a query is issued by a user that includes the entity identity and the attribute identity, the corresponding attribute value in the relational database is returned to the user.

摘要翻译： 本文描述了与事实查找查询有关的技术。 通过从一维表中提取属性标识和属性值来自动构建关系数据库，其中一维表不包括对应于属性标识和属性值的实体标识。 推断出实体身份，并通过实体身份和属性身份在属性数据库中对属性值进行索引。 当由包含实体标识和属性标识的用户发出查询时，将关系数据库中的对应属性值返回给用户。

公开(公告)号：US08041710B2

公开(公告)日：2011-10-18

申请号：US12270201

申请日：2008-11-13

申请人： Li-wei He ,  Wenzhao Tan ,  Jinliang Fan ,  Yi-Min Wang ,  Xiaoxin Yin

发明人： Li-wei He ,  Wenzhao Tan ,  Jinliang Fan ,  Yi-Min Wang ,  Xiaoxin Yin

IPC分类号： G06F17/30

CPC分类号： G06F17/30867

摘要： Search relevance failures are diagnosed automatically. Users presented with unsatisfactory search results can report their dissatisfaction through various mechanisms. Dissatisfaction reports can trigger automatic investigation into the root cause of such dissatisfaction. Based on the identified root cause, a search engine can be modified to resolve the issue creating dissatisfaction thereby improving search engine quality.

摘要翻译： 搜索相关性故障自动诊断。 用户不满意的搜索结果可以通过各种机制报告他们的不满。 不满意的报告可能引发自动调查，造成这种不满的根本原因。 基于确定的根本原因，可以修改搜索引擎来解决创建不满意的问题，从而提高搜索引擎的质量。

公开(公告)号：US20120158668A1

公开(公告)日：2012-06-21

申请号：US12971976

申请日：2010-12-17

申请人： Yi-Chin Tu ,  Aleksey Sinyagin ,  Xiaoxin Yin ,  Wenzhao Tan ,  Li-wei He ,  Yi-Min Wang ,  Emre Kiciman ,  Chun-Kai Wang

发明人： Yi-Chin Tu ,  Aleksey Sinyagin ,  Xiaoxin Yin ,  Wenzhao Tan ,  Li-wei He ,  Yi-Min Wang ,  Emre Kiciman ,  Chun-Kai Wang

IPC分类号： G06F17/30

CPC分类号： G06Q10/101 ,  G06F17/30882

摘要： A crowdsourcing data structuring system and method for capturing unstructured data from the Web and adding structure by placing the data in a document that is accessible by others in a cloud computing environment. Using crowdsourcing, the unstructured data is annotated, amended, and verified to add structure to the unstructured data. An anchor and update module convert the data to a pointer that links the document to the data at an information source and stores the pointer in the document rather than the data itself. The data displayed in the document is updated whenever the information source is updated. A contribution module allows users to add data to the document, a validation module allows users to determine the validity of the data linked to in the document, and an expert ranking module allows users to rank the expert or contributor of the data in the document.

摘要翻译： 用于从Web获取非结构化数据并通过将数据放置在可由其他人在云计算环境中访问的文档中来添加结构的众包数据结构化系统和方法。 使用众包，非结构化数据进行注释，修改和验证，以向非结构化数据添加结构。 锚和更新模块将数据转换为将文档链接到信息源上的数据的指针，并将指针存储在文档中而不是数据本身。 每当更新信息源时，文档中显示的数据都会更新。 贡献模块允许用户向文档添加数据，验证模块允许用户确定文档中链接的数据的有效性，专家排名模块允许用户对文档中的数据的专家或贡献者进行排名。

公开(公告)号：US09460207B2

公开(公告)日：2016-10-04

申请号：US12962677

申请日：2010-12-08

申请人： Xiaoxin Yin ,  Wenzhao Tan ,  Chao Liu

发明人： Xiaoxin Yin ,  Wenzhao Tan ,  Chao Liu

IPC分类号： G06F17/30

CPC分类号： G06F17/30864

摘要： Technologies pertaining to fact lookup queries are described herein. A relational database is automatically built by extracting attribute identities and attribute values from a one dimensional table, wherein the one dimensional table does not include an entity identity that corresponds to the attribute identity and the attribute value. The entity identity is inferred, and the attribute value is indexed in a relational database by the entity identity and the attribute identity. When a query is issued by a user that includes the entity identity and the attribute identity, the corresponding attribute value in the relational database is returned to the user.

摘要翻译： 本文描述了与事实查找查询有关的技术。 通过从一维表中提取属性标识和属性值来自动构建关系数据库，其中一维表不包括对应于属性标识和属性值的实体标识。 推断出实体身份，并通过实体身份和属性身份在属性数据库中对属性值进行索引。 当由包含实体标识和属性标识的用户发出查询时，将关系数据库中的对应属性值返回给用户。

公开(公告)号：US08145622B2

公开(公告)日：2012-03-27

申请号：US12351013

申请日：2009-01-09

申请人： Xiaoxin Yin ,  Vijay Ravindran Nair ,  Ryan Frederick Stewart ,  Fang Liu ,  Junhua Wang ,  Tiffany Kumi Dohzen ,  Yi-Min Wang

发明人： Xiaoxin Yin ,  Vijay Ravindran Nair ,  Ryan Frederick Stewart ,  Fang Liu ,  Junhua Wang ,  Tiffany Kumi Dohzen ,  Yi-Min Wang

IPC分类号： G06F7/00

CPC分类号： G06F17/30864

摘要： Systems and methodologies for improved query classification and processing are provided herein. As described herein, a query prediction model can be constructed from a set of training data (e.g., diagnostic data obtained from an automatic diagnostic system and/or other suitable data) using a machine learning-based technique. Subsequently upon receiving a query, a set of features corresponding to the query, such as the length and/or frequency of the query, unigram probabilities of respective words and/or groups of words in the query, presence of pre-designated words or phrases in the query, or the like, can be generated. The generated features can then be analyzed in combination with the query prediction model to classify the query by predicting whether the query is aimed at a head Uniform Resource Locator (URL) or a tail URL. Based on this prediction, an appropriate index or combination of indexes can be assigned to answer the query.

摘要翻译： 本文提供了改进的查询分类和处理的系统和方法。 如本文所述，可以使用基于机器学习的技术从一组训练数据（例如，从自动诊断系统获得的诊断数据和/或其他合适的数据）来构建查询预测模型。 随后在接收到查询后，查询对应的一组特征，诸如查询的长度和/或频率，查询中各个单词和/或单词组的单位概率，预先指定的单词或短语的存在 在查询等中可以生成。 然后可以结合查询预测模型分析生成的特征，以通过预测查询是针对头统一资源定位符（URL）还是尾URL来对查询进行分类。 基于该预测，可以分配适当的索引或索引组合来回答查询。

公开(公告)号：US07970773B1

公开(公告)日：2011-06-28

申请号：US11863020

申请日：2007-09-27

申请人： Srikanth Thirumalai ,  Aswath Manoharan ,  Xiaoxin Yin ,  Mark J. Tomko ,  Grant M. Emery ,  Vijai Mohan ,  Egidio Terra

发明人： Srikanth Thirumalai ,  Aswath Manoharan ,  Xiaoxin Yin ,  Mark J. Tomko ,  Grant M. Emery ,  Vijai Mohan ,  Egidio Terra

IPC分类号： G06F7/00

CPC分类号： G06F17/2211 ,  Y10S707/917

摘要： Systems and methods for determining a set of variation-phrases from a collection of documents in a document corpus is presented. Potential variation-phrase pairs among the various documents in the document corpus are identified. The identified potential variation-phrase pairs are then added to a variation-phrase set. The potential variation-phrase pairs in the variation-phrase set are filtered to remove those potential variation-phrase pairs that do not satisfy a predetermined criteria. After filtering the variation-phrase set, the resulting variation-phrase set is stored in a data store.

摘要翻译： 提出了用于从文档语料库中的文档集合确定一组变体词组的系统和方法。 识别文档语料库中的各种文档之间的潜在的变化 - 短语对。 然后将所识别的潜在变异短语对添加到变化短语集合中。 对变化短语组中的潜在的变体 - 短语对进行过滤以去除不满足预定标准的那些潜在的变体 - 短语对。 在对变化短语组进行过滤之后，将所得到的变化短语组存储在数据存储器中。