Abstract: Aspects of the disclosure relate to generating and providing enhanced user interfaces by implementing data, AI, intents and personalization (DAIP) technology. In some embodiments, a computing platform may receive, from enterprise computing infrastructure, first unstructured activity data associated with a first enterprise channel. Subsequently, the computing platform may identify one or more user intents by applying an intent discovery model to the first unstructured activity data associated with the first enterprise channel. Then, the computing platform may generate status tracking information based on identifying the one or more user intents.

Abstract: Real-time prevention of misappropriation and/or exposure assessment posed by a transaction at a POS terminal, especially those transactions in which it is not possible to otherwise definitively determine that a user/transactor is present at the POS terminal. AI is relied on, such as, a neural network implementing sequence modeling, to predict the likelihood that a user/transactor is present at the POS terminal. Location of a user is tracked via a designated mobile communication device and in instances in which a location of the mobile communication cannot be identified at the time of the transaction, the invention performs analysis based at least on the last-in-time location of the mobile communication device, the user's travel route leading up to the last-in-time location of the mobile communication device and other factors to predict a likelihood that the user is located at the POS terminal.

Abstract: Aspects of the disclosure relate to using a natural language processing system to analyze mobile application feedback. A computing platform having at least one processor, a memory, and a communication interface may receive mobile application feedback information comprising text feedback associated with feedback of a mobile application. The computing platform may identify one or more nouns associated with the text feedback. The computing platform may identify one or more text feedback topics. The computing platform may generate one or more commands directing a sentiment analysis server to determine one or more sentiments for the one or more text feedback topics. The computing platform may transmit the one or more commands directing the sentiment analysis server to determine the one or more sentiments. The computing platform may receive the one or more sentiments. The computing platform may transmit the feedback topics and the one or more sentiments.

Abstract: Aspects of the disclosure relate to using a natural language processing system to analyze mobile application feedback. A computing platform having at least one processor, a memory, and a communication interface may receive mobile application feedback information comprising text feedback associated with feedback of a mobile application. The computing platform may identify one or more nouns associated with the text feedback. The computing platform may identify one or more text feedback topics. The computing platform may generate one or more commands directing a sentiment analysis server to determine one or more sentiments for the one or more text feedback topics. The computing platform may transmit the one or more commands directing the sentiment analysis server to determine the one or more sentiments. The computing platform may receive the one or more sentiments. The computing platform may transmit the feedback topics and the one or more sentiments.

Abstract: A method, non-transitory computer readable medium, and device for clustering a network includes obtaining information regarding a network including relationship information for a plurality of nodes of the network. A weight value for each of a plurality of directly connected pairs of the plurality of nodes is determined, wherein the directly connected pair are identified based on the relationship information. At least one topology score is generated for each of the plurality of nodes. A plurality of clusters is generated using the topology scores and one of the plurality of nodes as a seed node for each of the clusters. At least the seed node used to generate at least a subset of the plurality of clusters is output.

Abstract: The disclosed embodiment relates to identifying performance regions in time-series data. An exemplary method comprises identifying, with a computing device, one or more streaks in the time-series data based on at least one streak parameter, ranking, with a computing device, the identified streaks based on at least one characteristic of the identified streaks, and predicting, with a computing device, a future occurrence of at least one streak based on the characteristics of the identified streaks. The steps of identifying and ranking may be carried out using at least one of a linear graph method, a statistical based approach, a curve-line intersection method, and a hypothesis-based method, and the step of predicting the future occurrence of at least one streak may comprise predicting at least one of how long a current streak will continue, when a current streak will end, and when a new streak will begin.

Abstract: The present invention provides a method and system for recommending an optimal shopping path to a user. A shopping layout of a shopping store is downloaded on a handheld device. A shopping list is received from the user, comprising one or more shopping items. A final shopping list is created by appending one or more additional shopping items to the shopping list. The optimal shopping path representing a shortest path on the shopping layout traversing each shopping item of the final shopping list is generated.

Abstract: A method, non-transitory computer readable medium, and device for clustering a network includes obtaining information regarding a network including relationship information for a plurality of nodes of the network. A weight value for each of a plurality of directly connected pairs of the plurality of nodes is determined, wherein the directly connected pair are identified based on the relationship information. At least one topology score is generated for each of the plurality of nodes. A plurality of clusters is generated using the topology scores and one of the plurality of nodes as a seed node for each of the clusters. At least the seed node used to generate at least a subset of the plurality of clusters is output.

Abstract: The disclosed embodiment relates to a computer-implemented method, an apparatus, and computer-readable media for preparing medical treatment service bundles. An exemplary method comprises identifying historical medical treatments based on attributes of a patient's medical condition, the historical medical treatments being associated with existing claim records, deriving a common pattern based on the historical medical treatments, extracting potential medical treatments for the patient from the historical medical treatments based on the common pattern; determining whether the potential medical treatments are appropriate medical treatments for the patient based on the attributes of the patient's medical condition; and preparing a service bundle including the appropriate medical treatments for the patient.

Abstract: A system, method and computer program product for the root cause analysis of the failure of a manufactured product is disclosed. The present invention includes the development of a knowledge model, based on information obtained from historical warranty claim forms and various manufacturing data sources. The invention also includes processing text information in a free-form text that is obtained from warranty claim forms by using text-tagging and annotation techniques. Thereafter, the knowledge model is converted to a Bayesian network. The present invention provides a user interface to select parameters and corresponding instances from current warranty claim forms. The selected parameters and corresponding instances are used as input evidence for the Bayesian network. The present invention facilitates the process of drawing inferences for root cause analysis of the failure of manufactured products and corresponding probabilities.

Abstract: The disclosed embodiment relates to identifying performance regions in time-series data. An exemplary method comprises identifying, with a computing device, one or more streaks in the time-series data based on at least one streak parameter, ranking, with a computing device, the identified streaks based on at least one characteristic of the identified streaks, and predicting, with a computing device, a future occurrence of at least one streak based on the characteristics of the identified streaks. The steps of identifying and ranking may be carried out using at least one of a linear graph method, a statistical based approach, a curve-line intersection method, and a hypothesis-based method, and the step of predicting the future occurrence of at least one streak may comprise predicting at least one of how long a current streak will continue, when a current streak will end, and when a new streak will begin.

Abstract: A system and method for estimation and analysis of operational parameters in workflow processes in order to establish effect of parameters on one or more critical parameters is provided. The method includes creating a Bayesian network including one or more operational nodes representing one or more operational parameters and one or more critical nodes representing one or more critical parameters. The method further includes generating an evidence set based on market events and deducing inferences based on the generated evidence set and Bayesian engine. Inferences are deduced by determining possible discrete states of operational parameters associated with one or more target nodes and their probability distribution values. Deduced inferences are then validated to confirm strength of probability distribution values.

Abstract: A system, method and computer program product for the root cause analysis of the failure of a manufactured product is disclosed. The present invention includes the development of a knowledge model, based on information obtained from historical warranty claim forms and various manufacturing data sources. The invention also includes processing text information in a free-form text that is obtained from warranty claim forms by using text-tagging and annotation techniques. Thereafter, the knowledge model is converted to a Bayesian network. The present invention provides a user interface to select parameters and corresponding instances from current warranty claim forms. The selected parameters and corresponding instances are used as input evidence for the Bayesian network. The present invention facilitates the process of drawing inferences for root cause analysis of the failure of manufactured products and corresponding probabilities.