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1. 发明授权

US09535974B1 Systems and methods for identifying key phrase clusters within documents 有权
标题翻译：用于识别文档中关键短语集群的系统和方法
公开(公告)号：US09535974B1
公开(公告)日：2017-01-03
申请号：US14581920
申请日：2014-12-23
申请人： Palantir Technologies, Inc.
发明人： Max Kesin , Hem Wadhar
IPC分类号： G06F17/30
CPC分类号： G06F17/30707 , G06F17/30719
摘要： Systems and methods are disclosed for key phrase clustering of documents. In accordance with one implementation, a method is provided for key phrase clustering of documents. The method includes obtaining a first plurality of documents based at least on a user input, obtaining a statistical model based at least on the user input, and obtaining, from content of the first plurality of documents, a plurality of segments. The method also includes identifying a plurality of clusters of segments from the plurality of segments, determining statistical significance of the plurality of clusters based at least on the statistical model and the content, and providing for display a representative cluster from the plurality of tokens, the representative cluster being determined based at least on the statistical significance. The method further includes determining a label for the representative cluster based at least on the plurality of clusters and the statistical significance.
摘要翻译：披露了关键短语聚类文档的系统和方法。根据一个实现，提供了一种用于文档的密钥短语聚类的方法。该方法包括至少基于用户输入获得第一多个文档，至少基于用户输入获得统计模型，以及从第一多个文档的内容中获取多个片段。该方法还包括从多个片段中识别多个片段群集，至少基于统计模型和内容确定多个群集的统计学显着性，以及提供从多个令牌中显示代表群集，至少根据统计学意义确定代表性群体。所述方法还包括至少基于所述多个聚类确定所述代表性聚类的标签和所述统计学显着性。

2. 发明授权

US11093687B2 Systems and methods for identifying key phrase clusters within documents 有权
公开(公告)号：US11093687B2
公开(公告)日：2021-08-17
申请号：US16211123
申请日：2018-12-05
申请人： Palantir Technologies Inc.
发明人： Max Kesin , Hem Wadhar
IPC分类号： G06F16/20 , G06F40/106 , G06F16/34 , G06F16/35 , G06F40/117 , G06F40/205 , G06F3/0481
摘要： Systems and methods are disclosed for key phrase clustering of documents. In accordance with one implementation, a method is provided for key phrase clustering of documents. The method includes obtaining a first plurality of documents based at least on a user input, obtaining a statistical model based at least on the user input, and obtaining, from content of the first plurality of documents, a plurality of segments. The method also includes identifying a plurality of clusters of segments from the plurality of segments, determining statistical significance of the plurality of clusters based at least on the statistical model and the content, and providing for display a representative cluster from the plurality of tokens, the representative cluster being determined based at least on the statistical significance. The method further includes determining a label for the representative cluster based at least on the plurality of clusters and the statistical significance.

3. 发明授权

US10162887B2 Systems and methods for key phrase characterization of documents 有权
公开(公告)号：US10162887B2
公开(公告)日：2018-12-25
申请号：US15483731
申请日：2017-04-10
申请人： PALANTIR TECHNOLOGIES INC.
发明人： Max Kesin , Hem Wadhar
IPC分类号： G06F17/30
摘要： Systems and methods are disclosed for key phrase characterization of documents. In accordance with one implementation, a method is provided for key phrase characterization of documents. The method includes obtaining a first plurality of documents based at least on a user input, obtaining a statistical model based at least on the user input, and obtaining, from content of the first plurality of documents, a plurality of segments. The method also includes determining statistical significance of the plurality of segments based at least on the statistical model and the content, and providing for display a representative segment from the plurality of segments, the representative segment being determined based at least on the statistical significance.

4. 发明申请

US20190114309A1 SYSTEMS AND METHODS FOR IDENTIFYING KEY PHRASE CLUSTERS WITHIN DOCUMENTS 审中-公开
公开(公告)号：US20190114309A1
公开(公告)日：2019-04-18
申请号：US16211123
申请日：2018-12-05
申请人： Palantir Technologies Inc.
发明人： Max Kesin , Hem Wadhar
IPC分类号： G06F17/21 , G06F3/0481 , G06F17/27
摘要： Systems and methods are disclosed for key phrase clustering of documents. In accordance with one implementation, a method is provided for key phrase clustering of documents. The method includes obtaining a first plurality of documents based at least on a user input, obtaining a statistical model based at least on the user input, and obtaining, from content of the first plurality of documents, a plurality of segments. The method also includes identifying a plurality of clusters of segments from the plurality of segments, determining statistical significance of the plurality of clusters based at least on the statistical model and the content, and providing for display a representative cluster from the plurality of tokens, the representative cluster being determined based at least on the statistical significance. The method further includes determining a label for the representative cluster based at least on the plurality of clusters and the statistical significance.

5. 发明申请

US20180173792A1 CONCEPT INDEXING AMONG DATABASE OF DOCUMENTS USING MACHINE LEARNING TECHNIQUES 审中-公开
公开(公告)号：US20180173792A1
公开(公告)日：2018-06-21
申请号：US15898066
申请日：2018-02-15
申请人： Palantir Technologies Inc.
发明人： Max Kesin
IPC分类号： G06F17/30 , G06N99/00
摘要： Systems and techniques for indexing and/or querying a database are described herein. Discrete sections and/or segments from documents may be determined by a concept indexing system. The segments may be indexed by concept and/or higher-level category of interest to a user. A user may query the segments by one or more concepts. The segments may be analyzed to rank the segments by statistical accuracy and/or relatedness to one or more particular concepts. The rankings may be used for presentation of search results in a user interface. Furthermore, segments and/or documents may be ranked based on recency decay functions that distinguish between segments that maintain their relevance over time in contrast with temporal segments whose relevance decays quicker over time, for example.

6. 发明授权

US10942957B2 Concept indexing among database of documents using machine learning techniques 有权
公开(公告)号：US10942957B2
公开(公告)日：2021-03-09
申请号：US15898066
申请日：2018-02-15
申请人： Palantir Technologies Inc.
发明人： Max Kesin
IPC分类号： G06F16/33 , G06F16/31 , G06F16/338 , G06F16/93 , G06F16/248 , G06F16/951 , G06F16/9535 , G06N20/00 , G06F16/40 , G06F16/28 , G06F16/35 , G06F16/36
摘要： Systems and techniques for indexing and/or querying a database are described herein. Discrete sections and/or segments from documents may be determined by a concept indexing system. The segments may be indexed by concept and/or higher-level category of interest to a user. A user may query the segments by one or more concepts. The segments may be analyzed to rank the segments by statistical accuracy and/or relatedness to one or more particular concepts. The rankings may be used for presentation of search results in a user interface. Furthermore, segments and/or documents may be ranked based on recency decay functions that distinguish between segments that maintain their relevance over time in contrast with temporal segments whose relevance decays quicker over time, for example.

7. 发明授权

US09898528B2 Concept indexing among database of documents using machine learning techniques 有权
公开(公告)号：US09898528B2
公开(公告)日：2018-02-20
申请号：US15159622
申请日：2016-05-19
申请人： Palantir Technologies Inc.
发明人： Max Kesin
IPC分类号： G06F17/30 , G06N99/00
CPC分类号： G06F17/30675 , G06F17/30011 , G06F17/30017 , G06F17/30554 , G06F17/30589 , G06F17/30613 , G06F17/30696 , G06F17/30707 , G06F17/30734 , G06F17/30864 , G06F17/30867 , G06N99/005
摘要： Systems and techniques for indexing and/or querying a database are described herein. Discrete sections and/or segments from documents may be determined by a concept indexing system. The segments may be indexed by concept and/or higher-level category of interest to a user. A user may query the segments by one or more concepts. The segments may be analyzed to rank the segments by statistical accuracy and/or relatedness to one or more particular concepts. The rankings may be used for presentation of search results in a user interface. Furthermore, segments and/or documents may be ranked based on recency decay functions that distinguish between segments that maintain their relevance over time in contrast with temporal segments whose relevance decays quicker over time, for example.

8. 发明授权

US09348920B1 Concept indexing among database of documents using machine learning techniques 有权
标题翻译：使用机器学习技术的文档数据库中的概念索引
公开(公告)号：US09348920B1
公开(公告)日：2016-05-24
申请号：US14746671
申请日：2015-06-22
申请人： Palantir Technologies Inc.
发明人： Max Kesin
IPC分类号： G06F17/30
CPC分类号： G06F17/30675 , G06F17/30011 , G06F17/30017 , G06F17/30554 , G06F17/30589 , G06F17/30613 , G06F17/30696 , G06F17/30707 , G06F17/30734 , G06F17/30864 , G06F17/30867 , G06N99/005
摘要： Systems and techniques for indexing and/or querying a database are described herein. Discrete sections and/or segments from documents may be determined by a concept indexing system. The segments may be indexed by concept and/or higher-level category of interest to a user. A user may query the segments by one or more concepts. The segments may be analyzed to rank the segments by statistical accuracy and/or relatedness to one or more particular concepts. The rankings may be used for presentation of search results in a user interface. Furthermore, segments and/or documents may be ranked based on recency decay functions that distinguish between segments that maintain their relevance over time in contrast with temporal segments whose relevance decays quicker over time, for example.
摘要翻译：本文描述了用于索引和/或查询数据库的系统和技术。来自文档的离散区段和/或段可以由概念索引系统确定。段可以由用户的兴趣的概念和/或更高级别的类别来索引。用户可以通过一个或多个概念查询段。可以通过统计精度和/或与一个或多个特定概念的相关性来对片段进行分析以对片段进行排序。排名可以用于在用户界面中呈现搜索结果。此外，例如，区段和/或文档可以基于新近度衰减函数进行排名，所述新近度衰减函数区分保持其随时间变化的相关性的区段，与其相关性随时间变化更快的时间段相反。

9. 发明授权

US11341178B2 Systems and methods for key phrase characterization of documents 有权
公开(公告)号：US11341178B2
公开(公告)日：2022-05-24
申请号：US16209617
申请日：2018-12-04
申请人： Palantir Technologies Inc.
发明人： Max Kesin , Hem Wadhar
IPC分类号： G06F16/20 , G06F16/34
摘要： Systems and methods are disclosed for key phrase characterization of documents. In accordance with one implementation, a method is provided for key phrase characterization of documents. The method includes obtaining a first plurality of documents based at least on a user input, obtaining a statistical model based at least on the user input, and obtaining, from content of the first plurality of documents, a plurality of segments. The method also includes determining statistical significance of the plurality of segments based at least on the statistical model and the content, and providing for display a representative segment from the plurality of segments, the representative segment being determined based at least on the statistical significance.

10. 发明授权

US10180929B1 Systems and methods for identifying key phrase clusters within documents 有权
公开(公告)号：US10180929B1
公开(公告)日：2019-01-15
申请号：US15293140
申请日：2016-10-13
申请人： Palantir Technologies Inc.
发明人： Max Kesin , Hem Wadhar
IPC分类号： G06F17/30 , G06F17/21 , G06F17/27 , G06F3/0481
摘要： Systems and methods are disclosed for key phrase clustering of documents. In accordance with one implementation, a method is provided for key phrase clustering of documents. The method includes obtaining a first plurality of documents based at least on a user input, obtaining a statistical model based at least on the user input, and obtaining, from content of the first plurality of documents, a plurality of segments. The method also includes identifying a plurality of clusters of segments from the plurality of segments, determining statistical significance of the plurality of clusters based at least on the statistical model and the content, and providing for display a representative cluster from the plurality of tokens, the representative cluster being determined based at least on the statistical significance. The method further includes determining a label for the representative cluster based at least on the plurality of clusters and the statistical significance.

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