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1. 发明申请

US20190188213A1 LANDMARK POINT SELECTION 审中-公开
公开(公告)号：US20190188213A1
公开(公告)日：2019-06-20
申请号：US16012606
申请日：2018-06-19
申请人： Ayasdi, Inc.
发明人： Harlan Sexton , Jennifer Kloke
IPC分类号： G06F16/28 , G06F16/901
CPC分类号： G06F16/285 , G06F16/9024
摘要： An exemplary method comprises receiving data points, selecting a first subset of the data points to generate an initial set of landmarks, each data point of the first subset defining a landmark point and for each non-landmark data point: calculating first data point distances between a respective non-landmark data point and each landmark point of the initial set of landmarks, identifying a first shortest data point distance from among the first data point distances between the respective non-landmark data point and each landmark point of the initial set of landmarks, and storing the first shortest data point distance as a first landmark distance for the respective non-landmark data point. The method further comprising identifying a non-landmark data point with a longest first landmark distance in comparison with other first landmark distances and adding the identified non-landmark data point associated as a first landmark point to the initial set of landmarks.

2. 发明申请

US20160034561A1 LANDMARK POINT SELECTION 有权
公开(公告)号：US20160034561A1
公开(公告)日：2016-02-04
申请号：US14884511
申请日：2015-10-15
申请人： Ayasdi, Inc.
发明人： Harlan Sexton , Jennifer Kloke
IPC分类号： G06F17/30
CPC分类号： G06F17/30598 , G06F17/30958
摘要： An exemplary method comprises receiving data points, selecting a first subset of the data points to generate an initial set of landmarks, each data point of the first subset defining a landmark point and for each non-landmark data point: calculating first data point distances between a respective non-landmark data point and each landmark point of the initial set of landmarks, identifying a first shortest data point distance from among the first data point distances between the respective non-landmark data point and each landmark point of the initial set of landmarks, and storing the first shortest data point distance as a first landmark distance for the respective non-landmark data point. The method further comprising identifying a non-landmark data point with a longest first landmark distance in comparison with other first landmark distances and adding the identified non-landmark data point associated as a first landmark point to the initial set of landmarks.
摘要翻译：一种示例性方法包括接收数据点，选择数据点的第一子集以产生初始的地标集合，第一子集的每个数据点定义地标点，并为每个非标志性数据点计算：计算第一数据点之间的距离相应的非标志性数据点和初始的地标集合的每个地标点，从相应的非地标数据点与初始地标集合的每个地标点之间的第一数据点距离之间确定第一最短数据点距离并且将所述第一最短数据点距离存储为所述相应非标志性数据点的第一标记距离。该方法还包括与其他第一地标距离相比较，识别具有最长的第一地标距离的非地标数据点，并将所标识的非地标数据点作为第一地标点加到初始的地标集合。

3. 发明申请

US20150154281A1 SYSTEMS AND METHODS FOR VISUALIZATION OF DATA ANALYSIS 审中-公开
标题翻译：用于可视化数据分析的系统和方法
公开(公告)号：US20150154281A1
公开(公告)日：2015-06-04
申请号：US14577649
申请日：2014-12-19
申请人： Ayasdi, Inc.
发明人： Gunnar Carlsson , Harlan Sexton , Gurjeet Singh
IPC分类号： G06F17/30
CPC分类号： G06F16/288 , G06F16/287
摘要： Exemplary systems and methods for visualization of data analysis are provided. In various embodiments, a method comprises accessing a database, analyzing the database to identify clusters of data, generating an interactive visualization comprising a plurality of nodes and a plurality of edges wherein a first node of the plurality of nodes represents a cluster and an edge of the plurality of edges represents an intersection of nodes of the plurality of nodes, selecting and dragging the first node in response to a user action, and reorienting the interactive visualization in response to the user action of selecting and dragging the first node.
摘要翻译：提供了用于可视化数据分析的示例性系统和方法。在各种实施例中，一种方法包括访问数据库，分析数据库以识别数据簇，生成包括多个节点和多个边缘的交互式可视化，其中多个节点中的第一节点表示簇，所述多个边缘表示所述多个节点的节点的交集，响应于用户动作选择并拖动所述第一节点，以及响应于所述用户选择和拖动所述第一节点的动作来重新定向所述交互式可视化。

4. 发明授权

US10417262B2 Scalable topological data analysis 有权
公开(公告)号：US10417262B2
公开(公告)日：2019-09-17
申请号：US15640166
申请日：2017-06-30
申请人： Ayasdi, Inc.
发明人： Ryan H. Lewis
IPC分类号： G06F17/30 , G06F17/14 , G06F17/15 , G06F9/46 , G06F16/28 , G06K9/46 , G06K9/62 , G06F16/901 , G06F17/16 , H04L29/08
摘要： An example method comprises receiving first data associated with data points, receiving a lens function selection, a metric function selection, and a resolution function, the metric function identified by the metric function selection being capable of performing functions on data as matrix functions, mapping second data based on the first data to a reference space by utilizing matrix vector multiplication for application of selected lens function on second data based on the first data to map the second data to the reference space, generating cover of reference space including the second data, clustering second data in cover based on the selected metric function to determine each node of a plurality of nodes, each of the nodes of the plurality of nodes comprising members representative of at least one subset of the data points, and generating a visualization comprising the plurality of nodes and a plurality of edges wherein each of the edges of the plurality of edges connects nodes with shared members.

5. 发明申请

US20190005036A1 SYSTEMS AND METHODS FOR METRIC DATA SMOOTHING 审中-公开
公开(公告)号：US20190005036A1
公开(公告)日：2019-01-03
申请号：US16125251
申请日：2018-09-07
申请人： Ayasdi, Inc.
发明人： Gunnar Carlsson , Anthony Bak , Jennifer Kloke , Benjamin Mann , Harlan Sexton
IPC分类号： G06F17/30
摘要： An exemplary method may comprise receiving a matrix for a set of documents, each cell of the matrix including a frequency value indicating a number of instances of a corresponding text segment in a corresponding document, receiving an indication of a relationship between two text segments, each of the two text segments associated with a first column and a second column, respectively, of the matrix, adjusting, for each document, a frequency value of the second column based on the frequency value of the first column, projecting each frequency value into a reference space to generate a set of projection values, identifying a plurality of subsets of the reference space, clustering, for each subset of the plurality of subsets, at least some documents that correspond to projection values, and generating a graph of nodes, each of the nodes identifying one or more of the documents corresponding to each cluster.

6. 发明申请

US20180285685A1 DIMENSION GROUPING AND REDUCTION FOR MODEL GENERATION, TESTING, AND DOCUMENTATION 审中-公开
公开(公告)号：US20180285685A1
公开(公告)日：2018-10-04
申请号：US15806265
申请日：2017-11-07
申请人： Ayasdi, Inc.
发明人： Gurjeet Singh , Noah Horton , Bryce Eakin
IPC分类号： G06K9/62 , G06N7/00 , G06F17/15 , G06F17/30 , G06Q10/06
CPC分类号： G06K9/623 , G06F16/254 , G06F16/9024 , G06F16/9038 , G06F17/153 , G06N7/00 , G06Q10/06375
摘要： An example method includes receiving analysis data and output indicator, mapping data points from a transposition of the analysis data to a reference space, generating a cover of the reference space, clustering the data points mapped to the reference space using the cover and a metric function to determine each node of a plurality of nodes, for each node, identifying data points that are members to identify similar features, grouping features as being similar to each other based on node(s), for each feature, determining correlation with at least some data associated with the output indicator and generate a correlation score, displaying at least groupings of similar features and displaying the correlation scores, receiving a selection of features, generating a set of models based on selection, determining fit of each generated model to output data and generate a model score, and generating a model recommendation report.

7. 发明授权

US10002180B2 Landmark point selection 有权
公开(公告)号：US10002180B2
公开(公告)日：2018-06-19
申请号：US14884511
申请日：2015-10-15
申请人： Ayasdi, Inc.
发明人： Harlan Sexton , Jennifer Kloke
IPC分类号： G06F17/00 , G06F17/30
CPC分类号： G06F16/285 , G06F16/9024
摘要： An exemplary method comprises receiving data points, selecting a first subset of the data points to generate an initial set of landmarks, each data point of the first subset defining a landmark point and for each non-landmark data point: calculating first data point distances between a respective non-landmark data point and each landmark point of the initial set of landmarks, identifying a first shortest data point distance from among the first data point distances between the respective non-landmark data point and each landmark point of the initial set of landmarks, and storing the first shortest data point distance as a first landmark distance for the respective non-landmark data point. The method further comprising identifying a non-landmark data point with a longest first landmark distance in comparison with other first landmark distances and adding the identified non-landmark data point associated as a first landmark point to the initial set of landmarks.

8. 发明申请

US20180025093A1 QUERY CAPABILITIES OF TOPOLOGICAL DATA ANALYSIS GRAPHS 审中-公开
公开(公告)号：US20180025093A1
公开(公告)日：2018-01-25
申请号：US15657074
申请日：2017-07-21
申请人： Ayasdi, Inc.
发明人： Huang Xia , Ronaldo Ama
IPC分类号： G06F17/30
CPC分类号： G06F16/9024 , G06F16/254 , G06F16/26 , G06F16/283 , G06F16/287 , G06F16/9017 , G06F16/90335
摘要： A method comprises receiving a data set, mapping data points from the data set to a reference space utilizing a lens function, generating a cover of the reference space using a resolution function, clustering the data points mapped to the reference space using the cover and a metric function to determine each node of a plurality of nodes of a graph, generating a graph including the plurality of nodes, the graph including an edge between every two nodes that share at least one data point as a member, and generating first and second data structures, the first data structure identifying membership of each node, the second data structure identifying each edge between each of the two nodes, the second data structure further identifying the nodes that are connected by each edge, the first and second data structure being capable of being queryable using a query language.

9. 发明申请

US20170169174A1 DETECTION OF FRAUD OR ABUSE 审中-公开
公开(公告)号：US20170169174A1
公开(公告)日：2017-06-15
申请号：US15376613
申请日：2016-12-12
申请人： Ayasdi, Inc.
发明人： Jean-Ezra Yeung , Anthony Bak
IPC分类号： G06F19/00 , G06F17/30
CPC分类号： G06F19/328 , G06F16/9024 , G06F16/90335 , G06F16/9038 , G16H10/60 , G16H50/20 , G16H50/70
摘要： An example method includes receiving a first set of data identifying entities and performance information for analysis, receiving a second set of data identifying entities and performance information associated with known or suspected past fraud or abuse, receiving metric and lens selections, performing metric and lens functions based on the metric and lens selections on first and second set of data, generating cover of reference space and cluster mapped performance information to identify nodes in a graph, each node including one or more entities as members, each node being connected to another node if they share at least one common entity as members, identifying nodes that include at least one member from the second set of data, determining entities that are members of the identified nodes that are from the first set of data, and generating a first report listing the determined entities as possibly involved in fraud or waste.

10. 发明申请

US20160246863A1 GROUPING OF DATA POINTS IN DATA ANALYSIS FOR GRAPH GENERATION 审中-公开
标题翻译：数据分析在图形生成中的分组
公开(公告)号：US20160246863A1
公开(公告)日：2016-08-25
申请号：US15069797
申请日：2016-03-14
申请人： Ayasdi, Inc.
发明人： Harlan Sexton
IPC分类号： G06F17/30 , G06T11/20
摘要： Autogrouping is described. An example method includes receiving a data set, building a first partition of subsets of the data set, computing a first subset score for each subset using a scoring function, generating a next partition including at least one subset that includes the elements of two or more subsets of the first partition, computing a second subset score for each subset of the next partition using the scoring function, defining a max score for each particular subset using a max score function, each max score being based on maximal subset scores of that particular subset and at least the subsets of the first partition related to that particular subset, selecting output subsets, selection of each of the output subsets being made using a maximum score of previously computed subset scores, and generating a report indicating an output partition, the output subsets being associated with the received data set.
摘要翻译：描述自动分组。一个示例性方法包括接收数据集，构建数据集的子集的第一分区，使用评分函数计算每个子集的第一子集得分，生成包括至少一个子集的下一个分区，所述子集包括两个或更多个元素使用评分函数计算下一分区的每个子集的第二子集，使用最大分数函数定义每个特定子集的最大分数，每个最大分数基于该特定子集的最大子集分数以及至少与该特定子集相关的第一分区的子集，选择输出子集，使用先前计算的子集分数的最大分数来选择每个输出子集，以及生成指示输出分区的报告，输出子集与所接收的数据集相关联。

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