Abstract: Disclosed are a method and system for propagating data changes in a hierarchy of dataset models in which each dataset model comprises an analytic and one or more parent datasets, including a primordial dataset. The analytic is executed to instantiate a first instance of the data model. After a change in a primordial dataset, each instance of a dataset model that descends from the primordial dataset is invalidated, and the analytic is re-executed to create a second instance of the data model. Analytical results may be displayed. The first dataset model may include a metric in which the definition of the metric comprises metadata of the dataset model. Metric values may be stored in a first cache, re-computed on a new instance of the dataset model, and stored in a second cache.

Abstract: Observable data points are collected and organized into a link-oriented data set comprising nodes and links. Information is abstracted for use in link analysis by generating links between the collected data points, including deriving links and inducing links. A link can be induced by linking together a pair of nodes that satisfy a distance function. Exemplary distance functions that can be used to induce links include geospatial proximity, attribute nearness, and name similarity. Paths can be identified between selected nodes of interest through a dataset operation, and nodes and/or links can be selectively included or excluded from the data set operation. The dataset can be augmented with pedigree information or one or more association nodes. Link information, including a trajectory and a connected path that selectively produces or excludes one or more intermediate nodes, can be displayed and/or produced in a specified format.

Abstract: Observable data points are collected and organized into a link-oriented data set comprising nodes and links. Information is abstracted for use in link analysis by generating links between the collected data points, including deriving links and inducing links. A link can be induced by linking together a pair of nodes that satisfy a distance function. Exemplary distance functions that can be used to induce links include geospatial proximity, attribute nearness, and name similarity. Paths can be identified between selected nodes of interest through a dataset operation, and nodes and/or links can be selectively included or excluded from the data set operation. The dataset can be augmented with pedigree information or one or more association nodes. Link information, including a trajectory and a connected path that selectively produces or excludes one or more intermediate nodes, can be displayed and/or produced in a specified format.

Abstract: A method for generating synthetic training records for use in training a model to predict low-incidence events. A synthetic training record is generated from a minority-class training record by substituting a different value for a feature in the minority-class training record, where the probability of the different value occurring in the minority-class training record exceeds a probability threshold. Also disclosed are a non-transitory storage medium comprising minority-class training records and synthetic training records and a method of training a machine-leaning model using training records augmented with synthetic training records. An exemplary synthetic training records is a synthetic medical record for use in training a model to predict drug overdoses.

Abstract: A recurrent neural network (RNN) method implemented on a computer system is used to produce summaries of unstructured text generated by multiple networks of individuals interacting over time by encoding the unstructured text into intermediate representations and decoding the intermediate representations into summaries of each network. Parameter data for the RNN is obtained by using multiple different versions of the same source texts to train the computer system. The method and computer system can be used to identify which of the networks match a query by determining which network generates the query with low or lowest cost.

Abstract: Disclosed are a method and system for propagating data changes in a hierarchy of dataset models in which each dataset model comprises an analytic and one or more parent datasets, including a primordial dataset. The analytic is executed to instantiate a first instance of the data model. After a change in a primordial dataset, each instance of a dataset model that descends from the primordial dataset is invalidated, and the analytic is re-executed to create a second instance of the data model. Analytical results may be displayed. The first dataset model may include a metric in which the definition of the metric comprises metadata of the dataset model. Metric values may be stored in a first cache, re-computed on a new instance of the dataset model, and stored in a second cache.

Abstract: A recurrent neural network (RNN) method implemented on a computer system is used to produce summaries of unstructured text generated by multiple networks of individuals interacting over time by encoding the unstructured text into intermediate representations and decoding the intermediate representations into summaries of each network. Parameter data for the RNN is obtained by using multiple different versions of the same source texts to train the computer system. The method and computer system can be used to identify which of the networks match a query by determining which network generates the query with low or lowest cost.

Abstract: A computer-implemented method of creating synthetic training data records for machine learning, comprising a source computer system operatively connected to a separate target computer system, where the target system comprises real data records, the contents of which are not known to the source computer system. The source computer system comprises the generator component of a generative adversarial network (GAN) and the target computer system comprises a discriminator component of the GAN. The source computer system generates one or more synthetic training records using a computational process that does not reveal contents of the real data records. Also disclosed is a method of training a machine-learning model using the one or more synthetic training records.

Abstract: Disclosed are a method and system for propagating data changes in a hierarchy of dataset models in which each dataset model comprises an analytic and one or more parent datasets, including a primordial dataset. The analytic is executed to instantiate a first instance of the data model. After a change in a primordial dataset, each instance of a dataset model that descends from the primordial dataset is invalidated, and the analytic is re-executed to create a second instance of the data model. Analytical results may be displayed. The first dataset model may include a metric in which the definition of the metric comprises metadata of the dataset model. Metric values may be stored in a first cache, re-computed on a new instance of the dataset model, and stored in a second cache.

Abstract: Observable data points are collected and organized into a link-oriented data set comprising nodes and links. Information is abstracted for use in link analysis by generating links between the collected data points, including deriving links and inducing links. A link can be induced by linking together a pair of nodes that satisfy a distance function. Exemplary distance functions that can be used to induce links include geospatial proximity, attribute nearness, and name similarity. Paths can be identified between selected nodes of interest through a dataset operation, and nodes and/or links can be selectively included or excluded from the data set operation. The dataset can be augmented with pedigree information or one or more association nodes. Link information, including a trajectory and a connected path that selectively produces or excludes one or more intermediate nodes, can be displayed and/or produced in a specified format.

Abstract: Observable data points are collected and organized into a link-oriented data set including nodes and links. Information is abstracted for use in link analysis by generating links between the collected data points, including deriving links and inducing links. A link can be induced by linking together a pair of nodes that satisfy a distance function. Exemplary distance functions that can be used to induce links include geospatial proximity, attribute nearness, and name similarity. Paths can be identified between selected nodes of interest through a dataset operation, and nodes and/or links can be selectively included or excluded from the data set operation. The dataset can be augmented with pedigree information or one or more association nodes. Link information, including a trajectory and a connected path that selectively produces or excludes one or more intermediate nodes, can be displayed and/or produced in a specified format.

Abstract: A recurrent neural network (RNN) method implemented on a computer system is used to produce summaries of unstructured text generated by multiple networks of individuals interacting over time by encoding the unstructured text into intermediate representations and decoding the intermediate representations into summaries of each network. Parameter data for the RNN is obtained by using multiple different versions of the same source texts to train the computer system. The method and computer system can be used to identify which of the networks match a query by determining which network generates the query with low or lowest cost.

Abstract: Observable data points are collected and organized into a link-oriented data set comprising nodes and links. Information is abstracted for use in link analysis by generating links between the collected data points, including deriving links and inducing links. A link can be induced by linking together a pair of nodes that satisfy a distance function. Exemplary distance functions that can be used to induce links include geospatial proximity, attribute nearness, and name similarity. Paths can be identified between selected nodes of interest through a dataset operation, and nodes and/or links can be selectively included or excluded from the data set operation. The dataset can be augmented with pedigree information or one or more association nodes. Link information, including a trajectory and a connected path that selectively produces or excludes one or more intermediate nodes, can be displayed and/or produced in a specified format.