Abstract: An illustrative computing device may include a processor and a non-transitory memory device for storing a data structure capable of being compressed, where the data structure includes a plurality of data elements and each of the plurality of data elements includes a date field and a quantity field. The computing device may process instructions to arrange the plurality of data elements in a consecutive series in date order based on a value stored in the date field of each data element, determine whether a gap appears in the consecutive series of data elements based on a value stored in the quantity field of each element, remove the determined gaps in each of the data elements, and repeat the determining and removing steps until a predetermined criterion has been reached.

Abstract: An apparatus to analyze and manipulate biofeedback data is described. The apparatus includes a display that renders a simulated environment. The simulated environment is experienced by a user. The simulated environment is generated by a software program executing on a computer. A biofeedback sensor is coupled to the scalp of the user. The biofeedback sensor measures the electrical activity of the brain of the user when the user experiences the simulated environment. The biofeedback sensor generates electrical signals corresponding to the electrical activity such that the user is able to modify the simulated environment by manipulating the electrical activity in the brain.

Abstract: Configurations herein comprise a multi-layer framework to extract document structural data. The framework extracts structural data from raw, unstructured, electronic documents, for example, .pdf documents. Structural data refers to the semantic elements, for example, paragraphs, lists, tables, titles etc. that may be visible in the displayed document but not described in electronic data.

Abstract: Embodiments of the present disclosure relate to a method that includes receiving customer identification information, verifying a customer identity using the customer identification information, receiving inputs related to customer intent from a predictive intent module, processing the inputs related to the customer intent to select a customer service representative from a plurality of customer service representatives, delivering the inputs related to the customer intent to the customer service representative, and connecting a customer device to the customer service representative to facilitate an interaction.

Abstract: An apparatus to analyze and manipulate biofeedback data is described. The apparatus includes a display that renders a simulated environment. The simulated environment is experienced by a user. The simulated environment is generated by a software program executing on a computer. A biofeedback sensor is coupled to the scalp of the user. The biofeedback sensor measures the electrical activity of the brain of the user when the user experiences the simulated environment. The biofeedback sensor generates electrical signals corresponding to the electrical activity such that the user is able to modify the simulated environment by manipulating the electrical activity in the brain.

Abstract: First indicators may be obtained, each first indicator associated with a respective first web page document. A classification type of each first web page document may be determined, based on the respective first indicators and a respective first content of each first web page document. A set of candidate documents that are included in the first web page documents may be selected, based on the determined classification type. For each one of the candidate documents, a group of first attention geography items and a group of first content geography items associated with the each one of the candidate documents may be determined. A determination may be made whether each of the candidate documents includes a first hyperlocal content page document, based on the group of first attention geography items and the group of first content geography items that are associated with the candidate documents.

Abstract: The present application presents methods for performing topical sentiment analysis on electronically stored communications employing fusion of polarity and topicality. The present application also provides methods for utilizing shallow NLP techniques to determine the polarity of an expression. The present application also provides a method for tuning a domain-specific polarity lexicon for use in the polarity determination. The present application also provides methods for computing a numeric metric of the aggregate opinion about some topic expressed in a set of expressions.