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: A computer-implemented method, a computer system and a computer program product coordinates knowledge from visual elements in a collaboration session. The method includes obtaining collaboration session data. The collaboration session data includes a plurality of visual elements and a plurality of participant interactions. The method also includes identifying a subject and a link in the plurality of visual elements using a text recognition algorithm. In addition, the method includes applying a weight to the link based on the plurality of participant interactions and a distinct characteristic in the plurality of visual elements. Lastly, the method includes generating a knowledge graph. The nodes of the graph comprise the subjects and the edges of the graph comprise weighted links.

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: 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: A document may be received. An ontology associated with a domain may be identified or retrieved. A set of concepts in the document may be extracted, the set represented in the ontology. A set of concepts selected from the ontology may be received. A search may be performed based on the set of selected concepts.

Abstract: A computer-implemented method for constructing an ontology includes using a chatbot program to elicit an utterance from a user. An utterance is received from the user. The received utterance is parsed to detect a concept/property/relationship therein. It is determined whether the identified concept/property/relationship is represented within an ontology and the identified concept/property/relationship is added to the ontology when it is determined that the it is not present therein. A response to the received utterance is generated using the ontology. The generated response is presented to the user using the chatbot.

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 document may be received. An ontology associated with a domain may be identified or retrieved. A set of concepts in the document may be extracted, the set represented in the ontology. A set of concepts selected from the ontology may be received. A search may be performed based on the set of selected concepts.

Abstract: A computer-implemented method for constructing an ontology includes using a chatbot program to elicit an utterance from a user. An utterance is received from the user. The received utterance is parsed to detect a concept/property/relationship therein. It is determined whether the identified concept/property/relationship is represented within an ontology and the identified concept/property/relationship is added to the ontology when it is determined that the it is not present therein. A response to the received utterance is generated using the ontology. The generated response is presented to the user using the chatbot.

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.