Abstract: This invention allows the semi-automated creation and curation of a knowledge graph based on a query-atom IR ranking engine. This invention cooperates with a domain expert to smoothly and semi-automatically incorporate or restructure textual data in the knowledge graph when a suitable high-confidence response to a query cannot be found. The invention extends the conventional information retrieval approach to consumer interaction by building a structured knowledge graph. Using graph exploration the invention augments the ranking made by the underlying neural model in order to stay in sync with the constantly-changing domain of application. The ultimate goal of this invention is to allow the consistent, cognitive, consumer-driven incorporation and restructuring of relevant unstructured data in a knowledge graph which is generated by mimicking users behaviours.

Abstract: A method and system are disclosed for a novel architecture in which competing suggestions, possibly generated by competing systems, are selected by a Cognitive Unit (CU). The CU observes the user context and learns which contextual circumstances affect the user's cognitive behaviour. Majority of the traditional models trained over multiple users fail to represent the individual because (1) they ignore personal bias toward certain decisions and (2) they don't have complete visibility of all options available to users (i.e. from competitive systems). The invention is ideally suited to interact with several other products as more and more modern products are using AIs to drive the user experience. That shifts traditional HCI towards a novel form of interaction that we call human-AI interaction (HAII). When applied to user experience, predictive models make decisions on users' behalf attempting to minimise user interaction while guiding them toward the completion of predefined funnels.

Abstract: Embodiments of the present invention are directed to computer-implemented methods and systems for representing human or machine-controllable sources, including, but not limited to, cloud services and smart devices, with a Semantic Interface Definition Language (SIDL) so that such resources can be listened to and eventually remote-controlled by discovering and performing Situationally Suitable Actions (SSA). Embodiments of the present invention are further directed to a novel user experience that allows sources to augment each other, removing the need to switch back and forth from different user interfaces (UIs) and overall facilitating or automating the execution of chains of commands.

Abstract: A method and system are disclosed for a novel architecture in which competing suggestions, possibly generated by competing systems, are selected by a Cognitive Unit (CU). The CU observes the user context and learns which contextual circumstances affect the user's cognitive behaviour. Majority of the traditional models trained over multiple users fail to represent the individual because (1) they ignore personal bias toward certain decisions and (2) they don't have complete visibility of all options available to users (i.e. from competitive systems). The invention is ideally suited to interact with several other products as more and more modern products are using AIs to drive the user experience. That shifts traditional HCI towards a novel form of interaction that we call human-AI interaction (HAII). When applied to user experience, predictive models make decisions on users' behalf attempting to minimise user interaction while guiding them toward the completion of predefined funnels.

Abstract: Embodiments of the present invention are directed to computer-implemented methods and systems for representing human or machine-controllable sources, including, but not limited to, cloud services and smart devices, with a Semantic Interface Definition Language (SIDL) so that such resources can be listened to and eventually remote-controlled by discovering and performing Situationally Suitable Actions (SSA). Embodiments of the present invention are further directed to a novel user experience that allows sources to augment each other, removing the need to switch back and forth from different user interfaces (UIs) and overall facilitating or automating the execution of chains of commands.