Abstract: According to one embodiment, a method, computer system, and computer program product for adaptive surrogate modeling is provided. The embodiment may include capturing a plurality of system information for a smart Internet of Things (IoT) device. The embodiment may also include calculating a lifespan value of the smart IoT device based on the plurality of captured system information. The embodiment may further include, in response to the calculated lifespan value being below a threshold and a surrogate model fitting one or more parameters of the smart IoT device not existing, creating the surrogate model for the smart IoT device. The embodiment may also include deploying the created surrogate model to the smart IoT device through an update transmission.

Abstract: A system may include a memory and a processor in communication therewith. The processor may be configured to perform operations including obtaining an egocentric network with a center node for an entity and receiving data about the entity. The operations may include predicting, with the data, a node array of the egocentric network including a first node to remain, a second node to disappear, and a third node to join the network. The operations may include prognosticating, with the data, a connection array of the egocentric network including a first link connecting the first node to the center node, a second link disappearing from the egocentric network, and a third link connecting the third node to the center node. The operations may include updating the egocentric network to reflect the node and connection arrays, generating an output based on the egocentric network, and displaying the output to a user.

Abstract: Embodiments of the invention are directed to a computer-implemented method of generating a pathway recommendation. The computer-implemented method includes using a processor system to generate an intermediate three-dimensional (3D) virtual reality (VR) environment of a target environment. A machine learning algorithm is used to perform a machine learning task on the intermediate 3D VR environment to generate machine learning task results including predicted features of interest (FOI) and FOI annotations for the intermediate 3D VR environment. The processor system is used to generate, based at least in part on the machine learning task results, the pathway recommendation configured to assist a user with navigating and interpreting a 3D VR environment including the intermediate 3D VR environment having the pathway recommendation.

Abstract: A method and system of generating a documentation includes monitoring user actions regarding a model development, wherein the user actions are captured in a source code development environment. Semantic meaning is provided for each user action captured in the source code development environment. A degree of impact of each user action is determined in connection with the model. Actions having a degree of impact in the development of the model that is above a predetermined threshold are identified as impactful actions. An interactive knowledge graph is identified based on the user actions, semantic meaning of each action, and the determined degree of impact of each user action. The interactive knowledge graph is provided to be displayed in a navigable way.

Abstract: A seismic dataset and a task to be performed with the seismic dataset may be received. A representative seismic line representative of the seismic dataset may be generated. The representative seismic line may include pixel data representative of the seismic dataset. Based on the representative seismic line, the task may be performed. The task may include at least finding an analogous geological region by searching for an analogous seismic dataset existing in a seismic database by comparing the representative seismic line with the analogous seismic dataset's representative seismic line.

Abstract: A metadata-based scientific data characterization method, system, and computer program product include requesting a user input for a task to specify a rule for the task to determine a quality and a relationship of a data file in a data file database based on metadata associated with the data file, processing a user feedback of results using the rule run on the data file database and tracking the user feedback on the results in order to learn from the user feedback, and based on the learning, creating a modified rule to determine a quality and a relationship of a second data file.

Abstract: Storing and retrieving subsurface rock physical property models for well drilling by generating estimated subsurface rock physical property models based on a respective set of seismic data, determining a stratigraphic classification for each model based on seismic interpretation data; storing the models associated classification in a database, determining characteristics of the seismic data used to generate the models, selecting from the database a subset of the models based on a similarity of the stratigraphic classification, determining measures of similarity between the characteristics of the seismic data used to generate each of subset of the models and a new set of seismic data and retrieving an estimated subsurface rock physical property model from the subset models based on the similarity measures.

Abstract: Machine teaching in an embodiment can include receiving a user annotated concept for a given image in given context. The given image can be broken into parts and classified. Relationships can be determined associated with the parts. The created relationships can be stored along with the user annotated concept in a knowledge base. One or more similar images can be annotated using the parts and relationships. A second image associated the given context can be retrieved, decomposed into parts. The parts can be classified. Relationships can be determined associated with the second image's parts. Classifications and relationships associated with the second image's parts can be compared with classifications and relationships associated with the given image's parts. Based on comparing, the second image can be annotated with the user annotated concept for the given image.

Abstract: Method, apparatus, and computer program product are provided for retrieving analogues using topological knowledge representation (TKR). In some embodiments, a TKR input query is built and/or validated using a domain-specific knowledge base (KB). A search database containing candidate analogues and corresponding pre-built TKRs is then searched to retrieve at least one analogue of the TKR input query using statistical analysis. In some embodiments, a system may build the TKR input query based on a seismic dataset. For example, the system may receive a seismic dataset, segment the seismic dataset and classify each region using a computer vision (CV) database and the KB, and build the TKR input query based on the segmented and classified seismic dataset. In some embodiments, the TKR input query may be input and/or edited by a user. For example, the TKR input query may be input and/or edited by the user and validated using the KB.

Abstract: Embodiments of the invention are directed to a computer-implemented method of generating a pathway recommendation. The computer-implemented method includes using a processor system to generate an intermediate three-dimensional (3D) virtual reality (VR) environment of a target environment. A machine learning algorithm is used to perform a machine learning task on the intermediate 3D VR environment to generate machine learning task results including predicted features of interest (FOI) and FOI annotations for the intermediate 3D VR environment. The processor system is used to generate, based at least in part on the machine learning task results, the pathway recommendation configured to assist a user with navigating and interpreting a 3D VR environment including the intermediate 3D VR environment having the pathway recommendation.

Abstract: Method, apparatus, and computer program product are provided for retrieving analogues using topological knowledge representation (TKR). In some embodiments, a TKR input query is built and/or validated using a domain-specific knowledge base (KB). A search database containing candidate analogues and corresponding pre-built TKRs is then searched to retrieve at least one analogue of the TKR input query using statistical analysis. In some embodiments, a system may build the TKR input query based on a seismic dataset. For example, the system may receive a seismic dataset, segment the seismic dataset and classify each region using a computer vision (CV) database and the KB, and build the TKR input query based on the segmented and classified seismic dataset. In some embodiments, the TKR input query may be input and/or edited by a user. For example, the TKR input query may be input and/or edited by the user and validated using the KB.

Abstract: A metadata-based scientific data characterization method, system, and computer program product include requesting a user input for a task to specify a rule for the task to determine a quality and a relationship of a data file in a data file database based on metadata associated with the data file, processing a user feedback of results using the rule run on the data file database and tracking the user feedback on the results in order to learn from the user feedback, and based on the learning, creating a modified rule to determine a quality and a relationship of a second data

Abstract: A seismic dataset and a task to be performed with the seismic dataset may be received. A representative seismic line representative of the seismic dataset may be generated. The representative seismic line may include pixel data representative of the seismic dataset. Based on the representative seismic line, the task may be performed. The task may include at least finding an analogous geological region by searching for an analogous seismic dataset existing in a seismic database by comparing the representative seismic line with the analogous seismic dataset's representative seismic line.

Abstract: A system, method and program product for implementing a sketch-based retrieval system. A system is disclosed that includes: an interface having a canvas for entering inputs including user generated strokes, and extracting features associated with the inputs; a hierarchy system for assigning an importance to the inputs; a matching system for retrieving matches from a database based on extracted features and importance associated with the extracted features; a feedback system that provides real-time feedback on the canvas to suggest improved inputs for the user; and a ranking system that ranks retrieved matches for output in the interface by incorporating user interaction history.

Abstract: A system, method and program product for implementing a sketch-based retrieval system. A system is disclosed that includes: an interface having a canvas for entering inputs including user generated strokes, and extracting features associated with the inputs; a hierarchy system for assigning an importance to the inputs; a matching system for retrieving matches from a database based on extracted features and importance associated with the extracted features; a feedback system that provides real-time feedback on the canvas to suggest improved inputs for the user; and a ranking system that ranks retrieved matches for output in the interface by incorporating user interaction history.

Abstract: A system, method and program product for implementing a sketch-based retrieval system. A system is disclosed that includes: an interface having a canvas for entering inputs including user generated strokes, and extracting features associated with the inputs; a hierarchy system for assigning an importance to the inputs; a matching system for retrieving matches from a database based on extracted features and importance associated with the extracted features; a feedback system that provides real-time feedback on the canvas to suggest improved inputs for the user; and a ranking system that ranks retrieved matches for output in the interface by incorporating user interaction history.

Abstract: A method is provided, the method including: displaying an image on a display; detect a user input corresponding to one or more portions of the image; analyzing the user input to determine at least one feature vector corresponding to the user input; and determining a classification for the one or more portions of the image based at least on the at least one feature vector.

Abstract: A method is provided, the method including: displaying an image on a display; detect a user input corresponding to one or more portions of the image; analyzing the user input to determine at least one feature vector corresponding to the user input; and determining a classification for the one or more portions of the image based at least on the at least one feature vector.