Abstract: An apparatus for dynamically debiasing an online job application system includes a processor and a memory that stores code executable by the processor to receive a plurality of job listings and corresponding job descriptions in response to a search query on an online job listing system and to dynamically modify bias terms of the job description for each of the job listings based on profile information for a user such that each of the job descriptions conforms to the user's profile information. The apparatus includes code executable by the processor to dynamically rank each of the job listings based on the modified job descriptions and with respect to the user's profile information and the search query and to present the job listings and their corresponding modified job descriptions in order of the rank for each of the job listings.

Abstract: A post-processing method, system, and computer program product for post-hoc improvement of instance-level and group-level prediction metrics, including training a bias detector that learns to detect a sample that has an individual bias greater than a predetermined individual bias threshold value with constraints on a group bias, applying the bias detector on a run-time sample to select a biased sample in the run-time sample having a bias greater than the predetermined individual bias threshold bias value, and suggesting a de-biased prediction for the biased sample.

Abstract: A method to automatically delete an image stored on a computing device is provided. The method may include, in response to a trigger event, scanning a plurality of images stored on the computing device. The method may also include determining if at least one image within the scanned plurality of images matches a plurality of predetermined criteria or a predetermined threshold. The method may further include marking the at least one image for deletion based on the determination that the at least one image matches the plurality of predetermined criteria or the predetermined threshold. The method may include adding the marked at least one image to an auto delete list. The method may also include displaying the auto delete list to a user.

Abstract: Systems and methods for detecting indirect bias in machine learning models are provided. A computer-implemented method includes: receiving, by a computer device, a user request to detect transitive bias in a machine learning model; determining, by the computer device, correlations of attributes of neighboring data not included in a dataset of the machine learning model; ranking, by the computer device, the attributes based on the determined correlations; and returning, by the computer device, a list of the ranked attributes to a user that generated the user request.

Abstract: Embodiments generally relate an intelligent automated trolley system. In some embodiments, a method includes receiving a trolley request. The method further includes determining one or more luggage characteristics of one or more luggage items. The method further includes determining one or more trolleys to send based on the luggage characteristics of the one or more luggage items. The method further includes assigning the one or more trolleys to assist the user based on the one or more characteristics of the one or more luggage items. The method further includes sending the one or more trolleys to a meeting location.

Abstract: Asset recommendation for a particular input dataset is provided. Candidate data analysis assets having a corresponding relatedness score associated with the particular input dataset greater than a defined relatedness score threshold value are selected. Those candidate data analysis assets having a corresponding relatedness score greater than the defined relatedness score threshold value are ranked by score. Those candidate data analysis assets having a corresponding relatedness score greater than the defined relatedness score threshold value are listed by rank from highest to lowest. A justification for each candidate data analysis asset is inserted in the ranked list of candidate data analysis assets. The ranked list of candidate data analysis assets along with each respective justification is outputted on a display device.

Abstract: A discussion thread is associated with a master recipients list that is maintained at an author's computer or a server computer. The recipients list is revised as participants in the discussion are added to and/or removed from the discussion. An author is notified when target recipients do not match the master recipients list. When a participant is added to the discussion from an old discussion instance, a thread manager provides for the added participant to receive a more current discussion instance.

Abstract: A discussion thread is associated with a master recipients list that is maintained at an author's computer or a server computer. The recipients list is revised as participants in the discussion are added to and/or removed from the discussion. An author is notified when target recipients do not match the master recipients list. When a participant is added to the discussion from an old discussion instance, a thread manager provides for the added participant to receive a more current discussion instance.

Abstract: A method to automatically delete an image stored on a computing device is provided. The method may include, in response to a trigger event, scanning a plurality of images stored on the computing device. The method may also include determining if at least one image within the scanned plurality of images matches a plurality of predetermined criteria or a predetermined threshold. The method may further include marking the at least one image for deletion based on the determination that the at least one image matches the plurality of predetermined criteria or the predetermined threshold. The method may include adding the marked at least one image to an auto delete list. The method may also include displaying the auto delete list to a user.

Abstract: Data-deduplicating includes comparing a first record of a data-store with a second record of the data-store but instead of using a static weight for a field, the present data-deduplicating dynamically assigns a first weight for the first score to generate a first weighted score, wherein the first weight is based on one or both of the first value or the second value; and assigns a second weight for the second score to generate a second weighted score. A composite score is calculated based on the first weighted score and the second weighted score; and it is determined whether or not the first record and the second record are duplicate records, based on the composite score.

Abstract: A discussion thread is associated with a master recipients list that is maintained at an author's computer or a server computer. The recipients list is revised as participants in the discussion are added to and/or removed from the discussion. An author is notified when target recipients do not match the master recipients list. When a participant is added to the discussion from an old discussion instance, a thread manager provides for the added participant to receive a more current discussion instance.

Abstract: The present application describes embodiments for reducing noise emanated by a device. An example computer implemented method includes receiving, by a supervisor device of a wireless system, a notification that an activity is being initiated. The method further includes, reducing the noise emanated by the device in response by determining, by the supervisor device a location of the device; in response to the location of the device being is within a predetermined vicinity of a location of the activity, sending, by the supervisor device a mute signal to the device.

Abstract: An approach for outage avoidance. The approach receives a scheduled task, wherein the scheduled task is completed at a scheduled time by a device. The approach receives an outage time of a service disruption, wherein the service disruption occurs at the outage time. The approach determines whether the service disruption conflicts with the scheduled task, based on the outage time and the scheduled time. Responsive to a determination that the service disruption conflicts with the scheduled task, the approach modifies the scheduled task to be completed at a modified time, wherein the outage time does not conflict with the modified time.

Abstract: A method controls execution of an intended application. One or more processors receive a first formatted character string that is in a first format. The processor(s) determine which application from multiple applications is an intended application that is to use the first formatted character string as a basis of an input to the intended application. The processor(s) convert the first formatted character string into a second formatted character string by applying a second format that is used by the intended application, and then execute the intended application by using the second formatted character string as an input to the intended application.

Abstract: An approach using one or more computer processors to send a request from a user for a mobile payment to a payment gateway and to determine that an event has occurred on a mobile computing device of a user. The approach includes sending a request for additional transaction time for the mobile payment.

Abstract: Aspects of the invention perform an operation comprising receiving a plurality of rules associated with a first seat in a mass-transit vehicle, determining a plurality of physical attributes for a first passenger, of a plurality of passengers, based on data describing the first passenger received from a plurality of data sources, determining a plurality of non-physical attributes for the first passenger based on the received data describing the first passenger, determining that at least one of the plurality of physical attributes and the plurality of non-physical attributes of the first passenger satisfy each rule in the set of rules associated with the first seat, computing, based on a machine learning (ML) model a score for the first passenger, determining that the score exceeds a threshold score associated with the first seat, and allocating the first passenger to the first seat in the mass-transit vehicle.

Abstract: Aspects of the invention include receiving a plurality of assets from a data catalog and a respective plurality of classifications applied to each asset in the data catalog, extracting, for a plurality of features, feature data from the plurality of assets and the plurality of asset classifications, generating a feature vector based on the extracted feature data; and generating, by a machine learning (ML) algorithm and based on the feature vector, a first classification rule specifying a condition for applying a first classification of the plurality of classifications to a first asset of the plurality of assets.

Abstract: Embodiments generally relate an intelligent automated trolley system. In some embodiments, a method includes receiving a trolley request. The method further includes determining one or more luggage characteristics of one or more luggage items. The method further includes determining one or more trolleys to send based on the luggage characteristics of the one or more luggage items. The method further includes assigning the one or more trolleys to assist the user based on the one or more characteristics of the one or more luggage items. The method further includes sending the one or more trolleys to a meeting location.

Abstract: A unit test case framework system writes unit test case(s) by passing only module input parameter value(s) that need to be tested, instead of passing all the input parameter value(s).

Abstract: A conference management application for a remote conferencing system stores information on a plurality of users and a plurality of client devices though which the plurality of users communicate with the remote conferencing system. The conference management application transmits information for a remote conference to a user, wherein the information that is transmitted is generated by a cognitive engine via learning mechanisms that iteratively incorporate information on previously completed remote conferences, information on the user, and information on the client device used by the user to communicate with the conference management application.