公开(公告)号：US09218390B2

公开(公告)日：2015-12-22

申请号：US13194887

申请日：2011-07-29

申请人： Donghui Feng ,  Kirk Boydston ,  Nathaniel A. Murray ,  Clarke Retzer ,  James G. Shanahan ,  Remi Zajac

发明人： Donghui Feng ,  Kirk Boydston ,  Nathaniel A. Murray ,  Clarke Retzer ,  James G. Shanahan ,  Remi Zajac

IPC分类号： G06F7/00 ,  G06F17/30

CPC分类号： G06F17/30401 ,  G06F17/3087

摘要： A system and method is provided which may comprise parsing an unstructured geographic web-search query into a field-based format, by utilizing conditional random fields, learned by semi-supervised automated learning, to parse structured information from the unstructured geographic web-search query. The system and method may also comprise establishing semi-supervised conditional random fields utilizing one of a rule-based finite state machine model and a statistics-based conditional random field model. Systematic geographic parsing may be used with the one of the rule-based finite state machine model and the statistics-based conditional random field model. Parsing an unstructured local geographical web-based query in local domain may be done by applying a learned model parser to the query, using at least one class-based query log from a form-based query system. The learned model parser may comprise at least one class-level n-gram language model-based feature harvested from a structured query log.

摘要翻译： 提供了一种系统和方法，其可以包括通过利用通过半监督自动化学习学习的条件随机字段将非结构化地理网络搜索查询解析为基于字段的格式来从非结构化地理网络搜索查询中解析结构化信息 。 系统和方法还可以包括利用基于规则的有限状态机模型和基于统计的条件随机场模型之一建立半监督条件随机场。 系统地理解析可以与基于规则的有限状态机模型和基于统计的条件随机场模型之一一起使用。 在本地域中解析非结构化的本地地理网络查询可以通过使用基于表单的查询系统中至少一个基于类的查询日志将学习的模型解析器应用于查询来完成。 所学习的模型解析器可以包括从结构化查询日志中收集的至少一个基于类级别的基于n-gram语言模型的特征。

公开(公告)号：US20130031113A1

公开(公告)日：2013-01-31

申请号：US13194887

申请日：2011-07-29

申请人： Donghui Feng ,  Kirk Boydston ,  Nathaniel A. Murray ,  Clarke Retzer ,  James G. Shanahan ,  Remi Zajac

发明人： Donghui Feng ,  Kirk Boydston ,  Nathaniel A. Murray ,  Clarke Retzer ,  James G. Shanahan ,  Remi Zajac

IPC分类号： G06F17/30

CPC分类号： G06F17/30401 ,  G06F17/3087

摘要： A system and method is provided which may comprise parsing an unstructured geographic web-search query into a field-based format, by utilizing conditional random fields, learned by semi-supervised automated learning, to parse structured information from the unstructured geographic web-search query. The system and method may also comprise establishing semi-supervised conditional random fields utilizing one of a rule-based finite state machine model and a statistics-based conditional random field model. Systematic geographic parsing may be used with the one of the rule-based finite state machine model and the statistics-based conditional random field model. Parsing an unstructured local geographical web-based query in local domain may be done by applying a learned model parser to the query, using at least one class-based query log from a form-based query system. The learned model parser may comprise at least one class-level n-gram language model-based feature harvested from a structured query log.

摘要翻译： 提供了一种系统和方法，其可以包括通过利用通过半监督自动化学习学习的条件随机字段将非结构化地理网络搜索查询解析为基于字段的格式来从非结构化地理网络搜索查询中解析结构化信息 。 系统和方法还可以包括利用基于规则的有限状态机模型和基于统计的条件随机场模型之一建立半监督条件随机场。 系统地理解析可以与基于规则的有限状态机模型和基于统计的条件随机场模型之一一起使用。 在本地域中解析非结构化的本地地理网络查询可以通过使用基于表单的查询系统中至少一个基于类的查询日志将学习的模型解析器应用于查询来完成。 所学习的模型解析器可以包括从结构化查询日志中收集的至少一个基于类级别的基于n-gram语言模型的特征。