Abstract: Disclosed herein is method and system for providing context based adaptive response to user interactions. A primary context of the user interactions is determined based on intents and associated named entities extracted from the user interactions. Further, secondary context of the user interactions is determined by detecting enquiry intent in user responses for queries provided for the primary context of the user interactions. Information related to primary and the secondary contexts are stored as Key Context Information (KCI) and is dynamically updated during the user interactions. Finally, context based adaptive responses are generated based on the updated KCI upon determining non-enquiry intent in subsequent user responses. The method of present disclosure maintains track of the user interactions and automatically detects changes in the context of the user interactions.

Abstract: Disclosed herein is method and system for providing context based adaptive response to user interactions. A primary context of the user interactions is determined based on intents and associated named entities extracted from the user interactions. Further, secondary context of the user interactions is determined by detecting enquiry intent in user responses for queries provided for the primary context of the user interactions. Information related to primary and the secondary contexts are stored as Key Context Information (KCI) and is dynamically updated during the user interactions. Finally, context based adaptive responses are generated based on the updated KCI upon determining non-enquiry intent in subsequent user responses. The method of present disclosure maintains track of the user interactions and automatically detects changes in the context of the user interactions.

Abstract: Systems and methods are provided for transforming historical data collected in response to one or more triggering events, in order to analyze resource utilization, inflow and outflow. Embodiments access inflow and outflow information corresponding to a primary node from historical data; analyze the inflow and outflow information corresponding to the primary node in order to identify one or more channels of flow out of a plurality of channels of flow, each channel connecting the primary node and a secondary node, the one or more channels of flow identified when they exhibit one or more predetermined characteristics; determine that the one or more channels of flow, based on the exhibited predetermined characteristics should be categorized into one or more categories out of a plurality of categories.

Abstract: Aspects of the present disclosure are directed to methods and systems for macroeconomic indication, including electronically selectively mapping a plurality of merchant classification data to sub-sector economic data for payment card transactions classification. The method may electronically receive a plurality of retail sales data based on the payment card transactions classification over a predetermined period of time to define an economic time series dataset; electronically adjust the economic time series dataset based on an autoregressive integrated moving average; and electronically transform the economic time series dataset after the adjusting step by using linear regression to define a predefined time period percentage change in the periodic data.