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1. 发明申请

US20100293184A1 IDENTIFICATION OF RELATED BID PHRASES AND CATEGORIES USING CO-BIDDING INFORMATION 审中-公开
标题翻译：使用共同投标信息识别相关投标单和类别
公开(公告)号：US20100293184A1
公开(公告)日：2010-11-18
申请号：US12465077
申请日：2009-05-13
申请人： Vanja Josifovski , Andrei Broder , Patrick Pantel , Ana-Maria Popescu , Evgeniy Gabrilovich , William Swei Chang
发明人： Vanja Josifovski , Andrei Broder , Patrick Pantel , Ana-Maria Popescu , Evgeniy Gabrilovich , William Swei Chang
IPC分类号： G06F17/30
CPC分类号： G06Q30/08 , G06Q30/02
摘要： The present invention provides a method and system for determining related bid terms. The method and system includes accessing a term database to determine a plurality of term pairs, the term pairs being paired terms bidded together in a term bidding operating environment. In the method and system, for each of the plurality of term pairs, the method and system includes determining similarity values for each of the term pairs. The method and system further includes generating a similarity matrix using the determined similarity values. And, the method and system includes generating an output result based on a co-bidded relationship between at least one of the terms and advertising information.
摘要翻译：本发明提供了一种用于确定相关投标术语的方法和系统。方法和系统包括访问术语数据库以确定多个术语对，术语对是在术语投标操作环境中一起投标的配对术语。在方法和系统中，对于多个术语对中的每一个，该方法和系统包括确定每个术语对的相似度值。所述方法和系统还包括使用所确定的相似度值来生成相似性矩阵。并且，所述方法和系统包括基于所述术语中的至少一个与广告信息之间的共同关系生成输出结果。

2. 发明授权

US09767144B2 Search system with query refinement 有权
公开(公告)号：US09767144B2
公开(公告)日：2017-09-19
申请号：US13452720
申请日：2012-04-20
申请人： Patrick Pantel , Michael Gamon , Hassan Sajjad
发明人： Patrick Pantel , Michael Gamon , Hassan Sajjad
IPC分类号： G06F17/30 , G06F17/00
CPC分类号： G06F17/30395 , G06F17/30867
摘要： A search system that automatically generates questions to refine an underspecified query. The system may generate questions even for queries against a database that contains unstructured textual descriptions of items, allowing the system to operate on a database of items that can be constructed inexpensively. The system extracts from the unstructured text combinations of words that may serve as a set of attribute values. The system uses a classifier to filter out attribute values from the set that would generate unanswerable questions. The remaining attribute values are ranked on their ability to narrow the search results and the highest ranking attribute value is used to generate a question to the user who submitted the query. The response to the question narrows the search results, and the process can be repeated iteratively until the search results are sufficiently narrow.

3. 发明申请

US20130282704A1 SEARCH SYSTEM WITH QUERY REFINEMENT 有权
标题翻译：搜索系统与查询精简
公开(公告)号：US20130282704A1
公开(公告)日：2013-10-24
申请号：US13452720
申请日：2012-04-20
申请人： Patrick Pantel , Michael Gamon , Hassan Sajjad
发明人： Patrick Pantel , Michael Gamon , Hassan Sajjad
IPC分类号： G06F17/30
CPC分类号： G06F17/30395 , G06F17/30867
摘要： A search system that automatically generates questions to refine an underspecified query. The system may generate questions even for queries against a database that contains unstructured textual descriptions of items, allowing the system to operate on a database of items that can be constructed inexpensively. The system extracts from the unstructured text combinations of words that may serve as a set of attribute values. The system uses a classifier to filter out attribute values from the set that would generate unanswerable questions. The remaining attribute values are ranked on their ability to narrow the search results and the highest ranking attribute value is used to generate a question to the user who submitted the query. The response to the question narrows the search results, and the process can be repeated iteratively until the search results are sufficiently narrow.
摘要翻译：搜索系统自动生成问题以优化不合格的查询。即使对于包含项目的非结构化文本描述的数据库的查询，系统也可能产生问题，从而允许系统对可以廉价构建的项目的数据库进行操作。系统从可以用作一组属性值的单词的非结构化文本组合中提取。系统使用分类器从集合中过滤出将产生不可回答问题的属性值。剩余的属性值按其缩小搜索结果的能力进行排名，最高排名属性值用于向提交查询的用户生成问题。对问题的回答缩小了搜索结果，并且可以迭代地重复该过程，直到搜索结果足够窄。

4. 发明申请

US20130159219A1 Predicting the Likelihood of Digital Communication Responses 审中-公开
标题翻译：预测数字通信响应的可能性
公开(公告)号：US20130159219A1
公开(公告)日：2013-06-20
申请号：US13325386
申请日：2011-12-14
申请人： Patrick Pantel , Michael Gamon , Yoav Y. Artzi
发明人： Patrick Pantel , Michael Gamon , Yoav Y. Artzi
IPC分类号： G06F15/18 , G06N5/00
CPC分类号： G06N20/00
摘要： Different advantageous embodiments provide for response prediction. A social element is received by a prediction mechanism. A feature set is generated for the social element. A prediction is generated using the feature set and a prediction model.
摘要翻译：不同的有利实施例提供了响应预测。一个社会因素被预测机制所接受。为社交元素生成一个特征集。使用特征集和预测模型生成预测。

5. 发明申请

US20130144854A1 MODELING ACTIONS FOR ENTITY-CENTRIC SEARCH 有权
标题翻译：建立实体中央搜索行动
公开(公告)号：US20130144854A1
公开(公告)日：2013-06-06
申请号：US13311581
申请日：2011-12-06
申请人： Patrick Pantel , Michael Gamon , Anitha Kannan , Ariel Fuxman , Thomas Lin
发明人： Patrick Pantel , Michael Gamon , Anitha Kannan , Ariel Fuxman , Thomas Lin
IPC分类号： G06F17/30
CPC分类号： G06F17/30867
摘要： In one embodiment, a web service engine server 104 may predict a successive action by a user based on an entity reference 302. The web service engine server 104 may identify an entity reference 302 in a data transmission caused by a user. The web service engine server 104 may determine from the data transmission a user intention towards the entity reference 302 using an intention model based on a transmission log. The web service engine server 104 may predict a related successive web action option 522 for the entity reference 302 based on the user intention.
摘要翻译：在一个实施例中，网络服务引擎服务器104可以基于实体参考302来预测用户的连续动作。网络服务引擎服务器104可以在由用户引起的数据传输中识别实体参考302。 Web服务引擎服务器104可以使用基于传输日志的意图模型从数据传输确定用户对实体参考302的意图。 Web服务引擎服务器104可以基于用户意图预测实体参考302的相关的连续web动作选项522。

6. 发明申请

US20110022550A1 MIXING KNOWLEDGE SOURCES WITH AUTO LEARNING FOR IMPROVED ENTITY EXTRACTION 有权
标题翻译：混合知识来源与自动学习改进实体提取
公开(公告)号：US20110022550A1
公开(公告)日：2011-01-27
申请号：US12509310
申请日：2009-07-24
申请人： Marco Pennacchiotti , Patrick Pantel
发明人： Marco Pennacchiotti , Patrick Pantel
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： The disclosed embodiments of computer systems and techniques utilize an ensemble semantics framework to combine knowledge acquisition systems that yield significantly higher quality resources than each system in isolation. Gains in entity extraction are achieved by combining state-of-the-art distributional and pattern-based systems with a large set of features from, for example, a webcrawl, query logs, and wisdom of the crowd sources. This results in improved query interpretation and greater relevancy in providing search results and advertising, for example.
摘要翻译：所公开的计算机系统和技术的实施例利用集合语义框架来组合知识获取系统，其产生比每个系统孤立地显着更高质量的资源。实体提取的收益通过将最先进的分布式和基于模式的系统与来自例如webcrawl，查询日志和人群智慧的大量功能组合来实现。例如，这可以提高查询解释和提供搜索结果和广告的相关性。

7. 发明授权

US09767201B2 Modeling actions for entity-centric search 有权
公开(公告)号：US09767201B2
公开(公告)日：2017-09-19
申请号：US13311581
申请日：2011-12-06
申请人： Patrick Pantel , Michael Gamon , Anitha Kannan , Ariel Fuxman , Thomas Lin
发明人： Patrick Pantel , Michael Gamon , Anitha Kannan , Ariel Fuxman , Thomas Lin
IPC分类号： G06F17/30
CPC分类号： G06F17/30867
摘要： In one embodiment, a web service engine server 104 may predict a successive action by a user based on an entity reference 302. The web service engine server 104 identifies an entity reference 302 in a data transmission caused by a user. The web service engine server 104 determines from the data transmission a user intention towards the entity reference 302 using an intention model based on a transmission log. The web service engine server 104 predicts a related successive web action option 522 for the entity reference 302 based on the user intention.

8. 发明授权

US09754585B2 Crowdsourced, grounded language for intent modeling in conversational interfaces 有权
公开(公告)号：US09754585B2
公开(公告)日：2017-09-05
申请号：US13438751
申请日：2012-04-03
申请人： Christopher John Brockett , Piali Choudhury , William Brennan Dolan , Yun-Cheng Ju , Patrick Pantel , Noelle Mallory Sophy , Svitlana Volkova
发明人： Christopher John Brockett , Piali Choudhury , William Brennan Dolan , Yun-Cheng Ju , Patrick Pantel , Noelle Mallory Sophy , Svitlana Volkova
IPC分类号： G10L15/00 , G10L15/18 , G10L15/22
CPC分类号： G10L15/18 , G10L15/22
摘要： Different advantageous embodiments provide a crowdsourcing method for modeling user intent in conversational interfaces. One or more stimuli are presented to a plurality of describers. One or more sets of describer data are captured from the plurality of describers using a data collection mechanism. The one or more sets of describer data are processed to generate one or more models. Each of the one or more models is associated with a specific stimulus from the one or more stimuli.

9. 发明申请

US20110022598A1 MIXING KNOWLEDGE SOURCES FOR IMPROVED ENTITY EXTRACTION 审中-公开
标题翻译：混合知识来源改进实体提取
公开(公告)号：US20110022598A1
公开(公告)日：2011-01-27
申请号：US12509278
申请日：2009-07-24
申请人： Marco Pennacchiotti , Patrick Pantel
发明人： Marco Pennacchiotti , Patrick Pantel
IPC分类号： G06F17/30
CPC分类号： G06F16/951
摘要： The disclosed embodiments of computer systems and techniques utilize an ensemble semantics framework to combine knowledge acquisition systems that yield significantly higher quality resources than each system in isolation. Gains in entity extraction are achieved by combining state-of-the-art distributional and pattern-based systems with a large set of features from, for example, a webcrawl, query logs, and wisdom of the crowd sources. This results in improved query interpretation and greater relevancy in providing search results and advertising, for example.
摘要翻译：所公开的计算机系统和技术的实施例利用集合语义框架来组合知识获取系统，其产生比每个系统孤立地显着更高质量的资源。实体提取的收益通过将最先进的分布式和基于模式的系统与来自例如webcrawl，查询日志和人群智慧的大量功能组合来实现。例如，这可以提高查询解释和提供搜索结果和广告的相关性。

10. 发明申请

US20130262114A1 Crowdsourced, Grounded Language for Intent Modeling in Conversational Interfaces 有权
标题翻译：众所周知的语言对话接口中的意图建模
公开(公告)号：US20130262114A1
公开(公告)日：2013-10-03
申请号：US13438751
申请日：2012-04-03
申请人： Christopher John Brockett , Piali Choudhury , William Brennan Dolan , Yun-Cheng Ju , Patrick Pantel , Noelle Mallory Sophy , Svitlana Volkova
发明人： Christopher John Brockett , Piali Choudhury , William Brennan Dolan , Yun-Cheng Ju , Patrick Pantel , Noelle Mallory Sophy , Svitlana Volkova
IPC分类号： G10L15/06 , G10L15/18 , G10L15/04
CPC分类号： G10L15/18 , G10L15/22
摘要： Different advantageous embodiments provide a crowdsourcing method for modeling user intent in conversational interfaces. One or more stimuli are presented to a plurality of describers. One or more sets of describer data are captured from the plurality of describers using a data collection mechanism. The one or more sets of describer data are processed to generate one or more models. Each of the one or more models is associated with a specific stimulus from the one or more stimuli.
摘要翻译：不同的有利实施例提供了用于在会话界面中建模用户意图的众包方法。一个或多个刺激被呈现给多个描述者。使用数据收集机构从多个描述者捕获一组或多组描述数据。一组或多组描述者数据被处理以产生一个或多个模型。一个或多个模型中的每一个与来自一个或多个刺激的特定刺激相关联。

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