Abstract: Systems and methods for privacy-preserving summarization of digital activity are disclosed. According to one embodiment in an information processing apparatus comprising at least one computer processor and at least one display, a privacy-preserving digital activity computer program performing the following: (1) capturing a blurred or pixelated screenshot of the at least one display; (2) identifying a plurality of computer application visible in the blurred or pixelated screenshot; (3) identifying a foreground or actively-used application out of the plurality computer applications in the blurred or pixelated screenshot; and (4) logging the visible computer applications and the foreground or actively-used application.

Abstract: A method for using images that represent time-series data to forecast future images depicting future values as pixelated information is provided. The method includes: receiving a first set of time-series data; converting the received first set of time-series data into a first image; and using the first image to forecast a future image depicting future values as pixelated information that corresponds to a future time interval Training sets of time-series data are used to generate historical data that provides input to a machine learning algorithm, which provides, as an output, a composite image that depicts the future values as pixelated information that reflects associated uncertainties in the value predictions.

Abstract: A method for detecting abnormal transactional behavior in a financial account is provided. The method includes: accessing first information that includes a textual description of a first transaction of a plurality of transactions associated with a first account; analyzing the text by applying tags thereto; assigning, based on a result of the analyzing, the first transaction to a respective cluster of the plurality of transactions; and designating each respective cluster as corresponding to one from among a normal transactional behavior group, an abnormal transactional behavior group, and an anomalous transactional behavior group. When a proportion of abnormal and anomalous transactions exceeds a threshold, the account may be flagged for further investigation.

Abstract: Systems and methods for extracting information from a resume of an applicant are provided. The method includes: receiving a resume that relates to an applicant; extracting information that relates to applicant attributes from the resume; comparing the extracted information with a predetermined list of job-specific skills and with a predetermined list of characteristics that relate to soft skills; using the extracted information to determine applicant achievements; and determining at least one skill that corresponds to the applicant. The method may be implemented by using a deep learning technique and/or a natural language processing technique.

Abstract: Systems and methods for extracting information from a resume of an applicant and matching the applicant with a suitable position within an organization are provided. The method includes: receiving a resume that relates to an applicant; extracting, from the received resume, information that relates to applicant attributes; and generating a score that indicates a suitability level of the applicant for an available job that is associated with a team of employees within the organization. The score is generated by applying an algorithm to the applicant attributes, the job requirements, and team goals. For a set of resumes and a corresponding set of scores, an optimal assignment of resumes to jobs that maximizes the joint score is determined.

Abstract: Systems and methods for privacy-preserving summarization of digital activity are disclosed. According to one embodiment in an information processing apparatus comprising at least one computer processor and at least one display, a privacy-preserving digital activity computer program performing the following: (1) capturing a blurred or pixelated screenshot of the at least one display; (2) identifying a plurality of computer application visible in the blurred or pixelated screenshot; (3) identifying a foreground or actively-used application out of the plurality computer applications in the blurred or pixelated screenshot; and (4) logging the visible computer applications and the foreground or actively-used application.

Abstract: A method for using images that represent time-series data to forecast future images depicting future values as pixelated information is provided. The method includes: receiving a first set of time-series data; converting the received first set of time-series data into a first image; and using the first image to forecast a future image depicting future values as pixelated information that corresponds to a future time interval Training sets of time-series data are used to generate historical data that provides input to a machine learning algorithm, which provides, as an output, a composite image that depicts the future values as pixelated information that reflects associated uncertainties in the value predictions.