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1.发明申请Machine Learning Model for Level-Based Categorization of Natural Language Parameters 审中-公开自然语言参数基于级别分类的机器学习模型公开(公告)号：US20160071022A1
公开(公告)日：2016-03-10
申请号：US14476912
申请日：2014-09-04
CPC分类号： G06N99/005 , G06F16/3349 , G06F17/30312 , G06F17/30693 , G06N7/005
摘要： A mechanism is provided in a data processing system for categorizing a user providing a text input. The mechanism receives an input text written by a user and determines a set of features associated with the input text. The mechanism processes the input text and the set of features by a detection model. The detection model comprises a plurality of detectors corresponding to a plurality of categories. Each of the plurality of detectors determines whether the user fits a respective category based on the input text and the set of features. The mechanism categorizes the user into one or more of the plurality of categories based on a result of processing the input text and the set of features by the detection model.
摘要翻译： 在用于对提供文本输入的用户进行分类的数据处理系统中提供一种机制。 该机制接收用户写入的输入文本并确定与输入文本相关联的一组特征。 该机制通过检测模型处理输入文本和特征集。 检测模型包括对应于多个类别的多个检测器。 多个检测器中的每个检测器基于输入文本和特征集来确定用户是否适合相应的类别。 该机构基于通过检测模型处理输入文本和特征集合的结果，将用户分类为多个类别中的一个或多个。
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公开(公告)号：US10528878B2
公开(公告)日：2020-01-07
申请号：US16524432
申请日：2019-07-29
摘要： A mechanism is provided in a data processing system for tailoring question answering system output based on user expertise. The mechanism receives an input question from a questioning user and determines a set of features associated with text of the input question. The mechanism determines an expertise level of the questioning user based on the set of features associated with the text of the input question using a trained expertise model. The mechanism generates one or more candidate answers for the input question and tailors output of the one or more candidate answers based on the expertise level of the questioning user.
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公开(公告)号：US10366332B2
公开(公告)日：2019-07-30
申请号：US14460066
申请日：2014-08-14
摘要： A mechanism is provided in a data processing system for tailoring question answering system output based on user expertise. The mechanism receives an input question from a questioning user and determines a set of features associated with text of the input question. The mechanism determines an expertise level of the questioning user based on the set of features associated with the text of the input question using a trained expertise model. The mechanism generates one or more candidate answers for the input question and tailors output of the one or more candidate answers based on the expertise level of the questioning user.
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公开(公告)号：US09658991B2
公开(公告)日：2017-05-23
申请号：US14640987
申请日：2015-03-06
发明人： Nicholas V. Bruno , Jared M. Smythe
CPC分类号： G06F17/2235 , G06F17/2264
摘要： An approach is provided in which a number of sections from a sequence of characters included in a Portable Document Format (PDF) file are identified. Each of the identified sections includes a unique set of coordinate positions. The approach builds links between the sections based on a relative position of each of the sections in relation to the other sections along an axis. The approach repeatedly merges sections based on the links that were built to form increasingly larger sections until a final larger section is generated with the characters appearing in a manner consistent with human reading of the rendered PDF document rather than the placement of the characters found within the original PDF file.
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公开(公告)号：US09904668B2
公开(公告)日：2018-02-27
申请号：US15641904
申请日：2017-07-05
CPC分类号： G06F17/2705
摘要： Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of the natural language content is generated by identifying latent logical terms within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value associated with at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. The propagating of the at least one knowledge value generates transaction records in a transaction knowledgebase data structure. A reasoning operation is executed based on the transaction knowledgebase data structure.
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公开(公告)号：US20170109651A1
公开(公告)日：2017-04-20
申请号：US14887501
申请日：2015-10-20
IPC分类号： G06N99/00 , G06F17/27 , G06F3/0484 , G06F17/24
CPC分类号： G06N20/00 , G06F3/0487 , G06F17/211 , G06F17/241 , G06F17/273 , G06F17/276 , G06F17/2785 , G06F17/279
摘要： A natural language text is received from a user. The natural language text includes typing characteristics metadata. An emotive content of the natural language text is determined using a machine learning model. The natural language text is modified based on the emotive content.
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公开(公告)号：US20160085731A1
公开(公告)日：2016-03-24
申请号：US14640987
申请日：2015-03-06
发明人： Nicholas V. Bruno , Jared M. Smythe
IPC分类号： G06F17/22
CPC分类号： G06F17/2235 , G06F17/2264
摘要： An approach is provided in which a number of sections from a sequence of characters included in a Portable Document Format (PDF) file are identified. Each of the identified sections includes a unique set of coordinate positions. The approach builds links between the sections based on a relative position of each of the sections in relation to the other sections along an axis. The approach repeatedly merges sections based on the links that were built to form increasingly larger sections until a final larger section is generated with the characters appearing in a manner consistent with human reading of the rendered PDF document rather than the placement of the characters found within the original PDF file.
摘要翻译： 提供了一种方法，其中识别包括在便携式文档格式（PDF）文件中的字符序列的多个部分。 每个识别的部分包括一组唯一的坐标位置。 该方法基于相对于沿着轴的其它部分的每个部分的相对位置来建立部分之间的连接。 该方法基于构建越来越大的部分的链接重复合并部分，直到生成最终较大的部分，其中以与人造阅读所渲染的PDF文档一致的方式出现的角色，而不是在 原始PDF文件。
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公开(公告)号：US20170308521A1
公开(公告)日：2017-10-26
申请号：US15641904
申请日：2017-07-05
发明人： Nicholas V. Bruno , Jared M.D. Smythe , Eric Woods
IPC分类号： G06F17/27
CPC分类号： G06F17/2705
摘要： Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of the natural language content is generated by identifying latent logical terms within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value associated with at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. The propagating of the at least one knowledge value generates transaction records in a transaction knowledgebase data structure. A reasoning operation is executed based on the transaction knowledgebase data structure.
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公开(公告)号：US09715488B2
公开(公告)日：2017-07-25
申请号：US14506898
申请日：2014-10-06
CPC分类号： G06F17/2705
摘要： Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of the natural language content is generated by identifying latent logical terms within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value associated with at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. The propagating of the at least one knowledge value generates transaction records in a transaction knowledgebase data structure. A reasoning operation is executed based on the transaction knowledgebase data structure.
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公开(公告)号：US09658990B2
公开(公告)日：2017-05-23
申请号：US14490076
申请日：2014-09-18
发明人： Nicholas V. Bruno , Jared M. Smythe
IPC分类号： G06F17/22
CPC分类号： G06F17/2235 , G06F17/2264
摘要： An approach is provided in which a number of sections from a sequence of characters included in a Portable Document Format (PDF) file are identified. Each of the identified sections includes a unique set of coordinate positions. The approach builds links between the sections based on a relative position of each of the sections in relation to the other sections along an axis. The approach repeatedly merges sections based on the links that were built to form increasingly larger sections until a final larger section is generated with the characters appearing in a manner consistent with human reading of the rendered PDF document rather than the placement of the characters found within the original PDF file.
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