Abstract: Methods and systems are presented for mining data in association with predicting occurrences of events. Upon detecting an occurrence of an event associated with a transaction, a data mining system accesses data associated with different transactions, and generates a decision tree for predicting occurrences of the event based on the data. Using a classification specification, the data mining system traverses the decision tree and prunes at least a portion of the decision tree that does not satisfy the classification specification. The data mining system then extracts data relevant to predicting occurrences of the event from the pruned decision tree. The extracted data includes attributes and/or criteria that are relevant to predicting occurrences of the event. Based on the extracted data, one or more actions can be performed to improve the event prediction process and/or reduce the frequency of the occurrences of the event.

Abstract: There are provided systems and methods for reducing latency through propensity models that predict data calls. A service provider, such as an electronic transaction processor for digital transactions, may provide computing services to users including those for electronic transaction processing. In order to provide sequence-based forecasting of computing events and processing requests for users, accounts, and/or activities associated with the service provider, the service provider may provide a machine learning model, such as a deep neural network, that predicted potential occurrences and likelihoods of computing events occurring at future times. When predicting the events, the service provider's machine learning predictive framework may further predict data calls required to be executed to retrieve data needed for processing during the events. These predicted calls may then be batched together into a batch processing job, which may be executed to retrieve the data prior to the predicted events.

Abstract: A transaction processing method includes receiving data respective of an electronic transaction, the data including an account involved in the transaction and determining an entity graph according to the account. The entity graph includes a plurality of first-order connections, each including a primary node representative of the account, a secondary node representative of a secondary entity, and an edge from the primary node to the secondary node, and a plurality of second-order connections, each including one of the secondary nodes, a tertiary node representative of a tertiary entity, and an edge from the secondary node to the tertiary node.

Abstract: Techniques for the implantation of time-dependent features (e.g., slope features) in existing data analysis models are disclosed. Time-dependent features are applied in machine learning algorithms to provide deeper analysis of temporally spaced data. Temporally spaced data is time-based or time-dependent data where data is populated at different points in time over some period of time. Implementing the time-dependent features enables application of first derivatives that define slopes over time (e.g., performance) windows within the period of time of the data. Application of the first derivatives provides analysis of the trend of the data over time. Additional features and/or higher order derivatives may also be applied to the first derivatives to provide further refinement to analysis of the temporally spaced data.

Abstract: Methods and systems are presented for mining data in association with predicting occurrences of events. Upon detecting an occurrence of an event associated with a transaction, a data mining system accesses data associated with different transactions, and generates a decision tree for predicting occurrences of the event based on the data. Using a classification specification, the data mining system traverses the decision tree and prunes at least a portion of the decision tree that does not satisfy the classification specification. The data mining system then extracts data relevant to predicting occurrences of the event from the pruned decision tree. The extracted data includes attributes and/or criteria that are relevant to predicting occurrences of the event. Based on the extracted data, one or more actions can be performed to improve the event prediction process and/or reduce the frequency of the occurrences of the event.

Abstract: The disclosure relates to sensor network, machine type communication (MTC), machine-to-machine (M2M) communication, and technology for internet of things (IoT). The disclosure may be applied to intelligent services based on the above technologies, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. The disclosure describes a method and system for routine disruption handling and routine management in a smart environment. A method for operating an apparatus is provided.

Abstract: An apparatus and method for providing one or more protocols for one or more electronic devices are provided. The method includes establishing, by an electronic device configured to provide a framework interface by executing instructions stored in a memory, one or more physical channels with an external electronic device, using one or more communication modules, executing, by the electronic device, two or more application programs to interface with the framework interface, and communicating, via the framework interface, data from the two or more application programs through the one or more physical channels to the external electronic device, using at least one logical channel or session for a respective one of the two or more application programs.

Abstract: The disclosure relates to sensor network, machine type communication (MTC), machine-to-machine (M2M) communication, and technology for internet of things (IoT). The disclosure may be applied to intelligent services based on the above technologies, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. The disclosure describes a method and system for routine disruption handling and routine management in a smart environment. A method for operating an apparatus is provided.

Abstract: An apparatus and method for providing one or more protocols for one or more electronic devices are provided. The method includes establishing, by an electronic device configured to provide a framework interface by executing instructions stored in a memory, one or more physical channels with an external electronic device, using one or more communication modules, executing, by the electronic device, two or more application programs to interface with the framework interface, and communicating, via the framework interface, data from the two or more application programs through the one or more physical channels to the external electronic device, using at least one logical channel or session for a respective one of the two or more application programs.

Abstract: An apparatus and method for providing one or more protocols for one or more electronic devices are provided. The method includes establishing, by an electronic device configured to provide a framework interface by executing instructions stored in a memory, one or more physical channels with an external electronic device, using one or more communication modules, executing, by the electronic device, two or more application programs to interface with the framework interface, and communicating, via the framework interface, data from the two or more application programs through the one or more physical channels to the external electronic device, using at least one logical channel or session for a respective one of the two or more application programs.

Abstract: An apparatus and method for providing one or more protocols for one or more electronic devices are provided. The method includes establishing, by an electronic device configured to provide a framework interface by executing instructions stored in a memory, one or more physical channels with an external electronic device, using one or more communication modules, executing, by the electronic device, two or more application programs to interface with the framework interface, and communicating, via the framework interface, data from the two or more application programs through the one or more physical channels to the external electronic device, using at least one logical channel or session for a respective one of the two or more application programs.