Abstract: Data security across data residency restriction boundaries is provided by obtaining and profiling a dataset on which a desired analysis is to be performed, with some results of the desired analysis to be transferred from one location to another, the dataset subject to data residency restrictions that restrict transfer of the dataset across a boundary to the another location, and the profiling identifying a profile level for the dataset, then automatically generating a container image based on the profile level and the data residency restrictions that restrict the transfer of the dataset across the boundary, the container image configured for instantiation and execution to process the dataset into a reformatted dataset not restricted by the data residency restrictions for transfer across the boundary, and storing the container image to a container registry.

Abstract: A transitive closure data structure is constructed for a pair of features represented in a vector space corresponding to an input dataset. The data structure includes a set of entries corresponding to a set of all possible paths between a first feature in the pair and a second feature in the pair in a graph of the vector space. The data structure is reduced by removing a subset of the set of entries such that only a single entry corresponding to a single path remains in the transitive closure data structure. A feature cross is formed from a cluster of features remaining in a reduced ontology graph resulting from the reducing the transitive closure data structure. A layer is configured in a neural network to represent the feature cross, which causes the neural network to produce a prediction that is within a defined accuracy relative to the dataset.

Abstract: In an approach for predictive forecasting of food allocation, a first data is received from one or more sensors. The amount and condition of available food is determined from the first data. The number and location of people is determined from the first data. The received data is modified to create a second data. One or more food requirements for the people are predicted based on the number and location of people and the second data. An optimal food allocation for the people is predicted based on the amount and condition of food available and the one or more food requirements. The optimal food allocation is reported.

Abstract: Systems and methods for automated resolution of over-specification and under-specification in a knowledge graph are disclosed. In embodiments, a method includes: determining, by a computing device, that a size of an object cluster of a knowledge graph meets a threshold value indicating under-specification of a knowledge base of the knowledge graph; determining, by the computing device, sub-classes for objects of the knowledge graph; re-initializing, by the computing device, the knowledge graph based on the sub-classes to generate a refined knowledge graph, wherein the size of the object cluster is reduced in the refined knowledge graph; and generating, by the computing device, an output based on information determined from the refined knowledge graph.

Abstract: Data security across data residency restriction boundaries is provided by obtaining and profiling a dataset on which a desired analysis is to be performed, with some results of the desired analysis to be transferred from one location to another, the dataset subject to data residency restrictions that restrict transfer of the dataset across a boundary to the another location, and the profiling identifying a profile level for the dataset, then automatically generating a container image based on the profile level and the data residency restrictions that restrict the transfer of the dataset across the boundary, the container image configured for instantiation and execution to process the dataset into a reformatted dataset not restricted by the data residency restrictions for transfer across the boundary, and storing the container image to a container registry.

Abstract: A transitive closure data structure is constructed for a pair of features represented in a vector space corresponding to an input dataset. The data structure includes a set of entries corresponding to a set of all possible paths between a first feature in the pair and a second feature in the pair in a graph of the vector space. The data structure is reduced by removing a subset of the set of entries such that only a single entry corresponding to a single path remains in the transitive closure data structure. A feature cross is formed from a cluster of features remaining in a reduced ontology graph resulting from the reducing the transitive closure data structure. A layer is configured in a neural network to represent the feature cross, which causes the neural network to produce a prediction that is within a defined accuracy relative to the dataset.

Abstract: Data security across data residency restriction boundaries is provided by obtaining and profiling a dataset on which a desired analysis is to be performed, with some results of the desired analysis to be transferred from one location to another, the dataset subject to data residency restrictions that restrict transfer of the dataset across a boundary to the another location, and the profiling identifying a profile level for the dataset, then automatically generating a container image based on the profile level and the data residency restrictions that restrict the transfer of the dataset across the boundary, the container image configured for instantiation and execution to process the dataset into a reformatted dataset not restricted by the data residency restrictions for transfer across the boundary, and storing the container image to a container registry.

Abstract: Systems and methods for automated resolution of over-specification and under-specification in a knowledge graph are disclosed. In embodiments, a method includes: determining, by a computing device, that a size of an object cluster of a knowledge graph meets a threshold value indicating under-specification of a knowledge base of the knowledge graph; determining, by the computing device, sub-classes for objects of the knowledge graph; re-initializing, by the computing device, the knowledge graph based on the sub-classes to generate a refined knowledge graph, wherein the size of the object cluster is reduced in the refined knowledge graph; and generating, by the computing device, an output based on information determined from the refined knowledge graph.

Abstract: A transitive closure data structure is constructed for a pair of features represented in a vector space corresponding to an input dataset. The data structure includes a set of entries corresponding to a set of all possible paths between a first feature in the pair and a second feature in the pair in a graph of the vector space. The data structure is reduced by removing a subset of the set of entries such that only a single entry corresponding to a single path remains in the transitive closure data structure. A feature cross is formed from a cluster of features remaining in a reduced ontology graph resulting from the reducing the transitive closure data structure. A layer is configured in a neural network to represent the feature cross, which causes the neural network to produce a prediction that is within a defined accuracy relative to the dataset.

Abstract: Systems and methods for automated resolution of over-specification and under-specification in a knowledge graph are disclosed. In embodiments, a method includes: determining, by a computing device, that a size of an object cluster of a knowledge graph meets a threshold value indicating under-specification of a knowledge base of the knowledge graph; determining, by the computing device, sub-classes for objects of the knowledge graph; re-initializing, by the computing device, the knowledge graph based on the sub-classes to generate a refined knowledge graph, wherein the size of the object cluster is reduced in the refined knowledge graph; and generating, by the computing device, an output based on information determined from the refined knowledge graph.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises generating a context-based query through based on a received input; finding a result of the generated query using link prediction algorithm coupled with link prefetching algorithm; and generating a specific link that illustrates and matches the generated context-based query.

Abstract: Identifying private information and preventing privacy violations is provided by a process that evaluates digital information obtained by an organization as part of a digital information stream from a user. The evaluating identifies a user utterance, including keyword(s), entity/ies, and intent(s), and applies natural language understanding to the digital information to ascertain a contextual understanding for the user utterance. The process selects training set(s) of historical information from available training sets that includes vocabulary used in varying contexts. The process compares the identified user utterance to an ontology based on the selected training set(s), and determines a confidence level that the digital information includes digital private information. The process also flags for the organization an action to take with respect to handling of the digital information. The flagging is based on the determined confidence level that the digital information includes digital private information.

Abstract: Systems and methods for dynamic camouflaging are disclosed. A computer-implemented method can be used with the system including determining, by a computing device, if current environment image data is available for a location of one or more users, and instructing, by the computing device, at least one image-enabled clothing system of the one or more users to display a camouflage image based on the determining. The camouflage image is based on the current environment image data when the current environment image data is available, and the camouflage image is based on historic image data associated with the location of the one or more users when the current environment image data is not available.

Abstract: A computer-implemented method includes: receiving, by a computing device, a container from a data requester server for processing data as part of an inference analysis; attaching, by the computing device, an input data volume and an output data volume associated with the container; processing, by the computing device, input data stored in the input data volume to produce output data; attaching, by the computing device, the output data in the output data volume; detaching, by the computing device, the input data volume based on attaching the output data to the output data volume; determining, by the computing device, whether sensitive data exists in the output data volume; and providing, by the computing device, the output data volume to the data requester server based on the determining that sensitive data does not exist in the output data volume.

Abstract: Data security across data residency restriction boundaries is provided by obtaining and profiling a dataset on which a desired analysis is to be performed, with some results of the desired analysis to be transferred from one location to another, the dataset subject to data residency restrictions that restrict transfer of the dataset across a boundary to the another location, and the profiling identifying a profile level for the dataset, then automatically generating a container image based on the profile level and the data residency restrictions that restrict the transfer of the dataset across the boundary, the container image configured for instantiation and execution to process the dataset into a reformatted dataset not restricted by the data residency restrictions for transfer across the boundary, and storing the container image to a container registry.

Abstract: An approach is provided for detecting a malicious activity on a computer system. First process trees are identified for computer processes that have been executed on a computer system. Each of the first process trees are vectorized. The vectorized first process trees are associated with respective labels. Each label represents an amount by which a respective vectorized process tree reflects the malicious activity. An artificial neural network is trained by using the vectorized first process trees and the associated labels as training input. After the training of the artificial neural network is completed, second process trees for currently executing computer processes are vectorized and provided as input vectors to the artificial neural network. Responsive to the artificial neural network providing an output indicating that a combination of the input vectors indicates the malicious activity, a remedial action is performed.

Abstract: Data security across data residency restriction boundaries is provided by profiling a dataset on which a desired analysis is to be performed, with some results of the desired analysis to be transferred from one location to another, the dataset subject to data residency restrictions that restrict transfer of the dataset across a boundary to the another location, and the profiling identifying a profile level for the dataset, automatically generating, based on the profile level and the data residency restrictions that restrict the transfer of the dataset across the boundary, a container for processing the dataset into a reformatted dataset not restricted by the data residency restrictions for transfer across the boundary, instantiating the generated container on a data processing system at the one location, and processing the dataset into the reformatted dataset using the instantiated generated container, and transferring the reformatted dataset to the another location.

Abstract: A method and system for managing queries in business intelligence platforms. It is determined that at least one requirement to complete a first query exceeds a threshold and in response, a redacted report failing to exceed the threshold is generated. The first query requests data from at least one business intelligence content from a first geographical region. In response to detecting a rejection, by a user, of the redacted report after the user had been prompted, to accept or reject the redacted report: (i) the first query is converted to a second query configured to be used by an Extract, Transform, and Load (ETL) program from a second geographical region; and (ii) a report responsive to the first query is generated.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises generating a context-based query through based on a received input; finding a result of the generated query using link prediction algorithm coupled with link prefetching algorithm; and generating a specific link that illustrates and matches the generated context-based query.

Abstract: An approach is provided for granting a security permission to a payment account. A relationship between an owner of an account and a user is determined by using a knowledge graph. A pattern of purchases made by the user is determined by using a machine learning module. Based on (i) the relationship between the owner of the account and the user and (ii) the pattern of the purchases, a security permission is dynamically granted to the user for a usage of the account.