Abstract: Disclosed herein are methods and systems for training artificial intelligence (AI) models. A central server may train an AI model by outputting, onto an electronic device operated by a user, results of execution of the AI model; monitoring the electronic device to identify a set of interactions between the user and the electronic device while the electronic device is outputting the results; generating a first training dataset corresponding to the user's interactions with the electronic device, the first training dataset corresponding to a frequency of correction of results; generating a second training dataset corresponding to the user's input to a prompt requesting the user to input a numerical value associated with an accuracy of the results; and training the AI model using the first and second training datasets.

Abstract: A system is provided for a cloud computing environment that is adapted to perform data processing and tracking of agent data between cloud computing tenants. The system includes a processor and a computer readable medium operably coupled thereto, to perform operations which include determining a unique identifier (ID) for an agent of the cloud computing tenants, accumulating, over a time period, agent data for the agent, refining the agent data to curated data views for the agent data based on a plurality of aggregate reports for each of a plurality of KPIs in the agent data, determining a batch processing job for the refined agent data, calculating, using the batch processing job, a base asset value (BAV) score for the agent, and updating a profile for the agent associated with the unique ID based on the calculated BAV score.

Abstract: A digital recruitment system and a method to enable a candidate to create, edit, upload a multimedia comprising a job application comprising video, audio etc. in one or more sections to apply for a job is provided. Further, the system allows the candidate and recruiter(s) to exchange information with each other via videos (or multimedia), video chats, audio chats, etc. The system protects a job application and/or a multimedia response from the recruiter from editing by a third person other than an owner, wherein the candidate is the owner of the job application and the recruiter is the owner of the multimedia response. The system may embed time and location information into the multimedia; therefore, the system allows the users (candidate and recruiters) to generate authentic multimedia. Further, the system may augment more information in the multimedia automatically or based on an input from the owner of the multimedia.

Abstract: Embodiments of the present disclosure related to systems and methods of managing litigation support services. In one embodiment, a method comprises receiving, from a user device, one or more requests related to litigation support services, the one or more requests specifying a litigation-related event and associated scheduling information; receiving an indication of acceptance of one or more of the requests from one or more user devices associated with litigation support service providers; and transmitting, to the user device, the indication of acceptance.

Abstract: An apparatus includes a processor and a memory storing instructions to cause the processor to receive (1) user data associated with a user, (2) target workforce data, (3) target role data, and (4) candidate pool data, randomly select a plurality of candidates from the candidate pool data, execute a machine learning model to generate matching scores for the user and each candidate to the target role data, to produce a matching score distribution, and generate, via a statistical model, a fit score for the user based on a number of candidates in a subset of candidates, where each candidate from the subset of candidates has a matching score lower than the user matching score.

Abstract: A method, apparatus, system, and computer program code for classifying a transaction. A computer system receives an authorization request from a gateway. The authorization request includes data for a transaction that is pending at a web client. A context for accessing a web service is determined from the authorization request, and the computer system accesses web services data according to the context that was determined. The computer system classifies the transaction based on the web services data, and records the transaction in a ledger according to the context.

Abstract: This disclosure is directed to systems and methods for generating and querying an index associated with targeted communications. A method may include receiving candidate identifiers, rates of targeted communication, and traits associated with the candidate identifiers. A method may include generating a candidate index including one or more dimensions associated with candidate traits. A method may include receiving a query associated with desired candidate traits, determining if one or more candidates appear in the dimensions associated with the desired traits, and intersecting the dimensions to determine if one or more candidates appear in all of the dimensions associated with the desired candidate traits. A method may include generating a result set based on the results of an intersecting computation. A method may include removing candidates from the result set and transmitting targeted communications on behalf of or to the candidates remaining on the result set.

Abstract: A system and method for analyzing a response to an interview questions is disclosed, including a speech recognition engine to receive audio information corresponding to a response to create a transcription of the response. A segmentation engine segments the transcription into one or more segments. A segment classification engine classifies the one or more segments into one or more functional units and group the functional units by at least one structure. A presentation skill KPI engine, a structure sequence KPI engine, and a content KPI engine to analyze the response and applying the analysis to a composite model to provide an overall rating of the response.

Abstract: A skill-gap analysis and recommender system and method is described that serves as a personalized education and skill (PES) map. It provides a comprehensive presentation of the opportunities afforded by the University along with a detailed analysis of trends for placements and career goals. It conducts a comprehensive analysis of past student data and current market trends to make recommendations that are adapted to each student's profile in line with their individual career goals. This is accomplished using an algorithm for adaptive association pattern mining with a built-in mechanism for creation of meta-categories and drill-down for specifics, so as to meet the needs of every student and not miss infrequent patterns or rare opportunities afforded by the system. For the recommendations generated, the system also provides an assessment of the time-sensitivity of a goal and a mechanism for students to track their progress through prioritizing short and long term goals.

Abstract: Disclosed is a method and system for enabling a job seeker to browse a plurality of job classifieds or a job provider to browse a plurality of job seeker profiles. The method includes generating and storing a job seeker profile for the job seeker based upon job seeker information a location of the job seeker; identifying a plurality of job classifieds stored in the data store which are relevant to the job seeker based upon the job seeker profile; serving the plurality of job classifieds to the mobile device for presentation to the job seeker; receiving job seeker feedback data indicative of whether each job classified was relevant or not relevant; analysing the job seeker feedback data; and updating the job seeker profile stored in the data store in accordance with the analysis of the job seeker feedback data.

Abstract: Systems include reception of a plurality of tags associated with a first job board and, for each of the plurality of tags, one or more values associated with the first job board, input of each of the plurality of tags to a first neural network to determine a field of a job posting system associated with the tag, wherein the first neural network is trained based on a plurality of mappings from fields of the job posting system to tags associated with a plurality of job boards, input of each of the one or more values of each of the plurality of tags to a second neural network to determine an item of the job posting system associated with the value, wherein the second neural network is trained based on a plurality of mappings from items of the job posting system to values associated with the plurality of job boards, creation of first mappings from each of the plurality of tags associated with the first job board to the determined field associated with the tag, creation of second mappings from each of the one or m

Abstract: Techniques are described for automatically generating job descriptions. Training data is used to define job categories, job sections, and selective phrases for each job category and job section. In response to receiving request to generate a job description, a job category or additional information is derived from the request. Such information is used to populate existing templates for a job description based on a skill knowledge graph, which connects skill names based on hypernym trees and enables enhancement of a job description with better or broader coverage.

Abstract: Apparatuses, computer readable medium, and methods are disclosed for determining talent seekers. The apparatus, computer readable medium, and methods may include importing a job posting from an external source into a connection network system. The apparatus, computer readable medium, and methods may include deter mining a company stored in the connection network system that is offering the job, and determining talent seekers associated with the company, where the talent seekers are members of the connection network system. The apparatus, computer readable medium, and methods may include determining a matching score between each of the talent seekers and the job and a job seeker and selecting a talent seeker with a highest matching score. The apparatus, computer readable medium, and methods may include causing to be displayed to the job seeker a user interface screen that enables the job seeker to message the talent seeker with the highest matching score.

Abstract: A system and method reduces or minimizes the number of characteristic values required to evaluate a rule by selecting elements of the rule in an order most likely to allow evaluation of the rule without requiring evaluation of other elements of the rule. The selection may be a function of one or both of the structure of the rule and the probability that an element will resolve to a particular value of true or false.

Abstract: Methods and apparatus for generating feedback, reviewing feedback, and conducting interviews by use of VMocks are provided. A VMock, or Virtual Mock, is a virtual profile of a candidate that includes resume, text, video and a document. VMock profiles may be created that have one or more VMocks. Contacts associated with the VMock profile may be managed. Feedback may be requested from the contacts concerning the one or more VMocks, who may then generate the requested feedback. The feedback may then be reviewed. This feedback process may be performed in the context of interviews for employment opportunities and in other similar situations.

Abstract: In an embodiment, a plurality of ballots (1) for a plurality of candidates, (2) generated by a plurality of search engines, and (3) for a job description are received. Each ballot from the plurality of ballots is generated by a search engine from the plurality of search engines different than remaining search engines from the plurality of search engines. A mathematical representation that indicates, for each candidate from the plurality of candidates, how many other candidates from the plurality of candidates that candidate was ranked higher than in the plurality of ballots is generated. A final ballot ranking the plurality of candidates is generated using a trained statistical model and based on the mathematical representation. A candidate from the plurality of candidates for the job description is identified based on the final ballot.

Abstract: An artificial-intelligence-directed social network extender for existing employees and recruiters which increases the pool of available candidates for an employer while also maximizing the effectiveness of candidate selection. In an embodiment, a recruiting manager extends the social networks of employees and recruiters to maximize the available pool of candidates for a given job opening. A first machine learning algorithm provides instructions to a crawler to gather both candidate information from the extended social network, plus corporate structure information from the Internet for privacy and conflict checking purposes. The gathered information is stored in a knowledge graph which is analyzed by a second machine learning algorithm to identify candidates and relationships most likely to produce a good fit for the job opening.

Abstract: Systems, methods, and apparatus, including computer-readable media for managing and adapting monitoring programs. In some implementations, a system accesses data describing a monitoring program that involves collecting data over a period of time from a monitoring group comprising geographically distributed devices. The system classifies the devices in the monitoring group into different groups for the categories based on the attributes associated with the devices. The system monitoring performance of the devices in the different groups and determines a performance score for each group. The system adjusts administration of the monitoring program based on the performance scores, including performing one or more actions to improve diversity in the monitoring group.

Abstract: Methods, apparatus, systems, and computer-readable media are provided for increasing dimensionality of data structures associated with filling positions. In some implementations, a prediction of desired experience for a given position to be filled may be incorporated into a searchable field of the data structure. Among other things, increasing the dimensionality of the data structure may facilitate more granular searching of positions and guided creation of new positions to be filled. In some implementations, a predicted desired experience may be used to notify a user posting a new position whether a specified desired experience corresponds to a predicted desired experience.

Abstract: Techniques are generally described for onboarding optimization for new hires. In various examples, labor order data specifying a target number of new hires may be received. In some examples, a first machine learning model may predict a number of new hire appointments to offer based at least in part on the labor order data. In further examples, an optimization component may allocate the number of new hire appointments to respective time slots based at least in part on candidate preferences. In some additional examples, data may be sent to a first application effective to display a list of available new hire appointment time slots of the respective time slots.

Abstract: One embodiment provides a method, including: receiving a ranked listing of a plurality of candidates; within a first one of a plurality of collaboration rounds: (i) aggregating the ranked listings into an overall listing, (ii) presenting the overall listing to a first one of the job candidate matching agents, and (iii) receiving at least one modification to the overall listing from the agents; (iv) presenting a version of the overall listing to each of the remaining agents; and (v) receiving any modifications from the agents until all of the agents have had a turn; conducting others of the plurality of collaboration rounds: (i) presenting a version of the overall listing and (ii) receiving any modifications from the agents; (iii) presenting a version of the overall listing to each of the remaining agents, and (iv) receiving any modifications from the agents; and providing the final version to a user.

Abstract: An apparatus for creating a video record is disclosed. The apparatus includes a processor communicatively connected to a user device and a memory communicatively connected to the processor. The memory contains instructions configuring the processor to prompt a user with an initial request, receive an initial response from the user, prompt the user with a subsequent request based on the initial response, receive a subsequent response from the user, and create a video record as a function of the initial response and the subsequent response.

Abstract: A system for determining candidate answers during an interview. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include capturing, by an image sensor, a plurality of images comprising a plurality of candidate answers; detecting, based on the captured images, a first bounding box comprising the plurality of the candidate answers; detecting, based on the captured images, a second bounding box comprising a plurality of alphanumeric characters, a first one of the alphanumeric characters being located on a line of software code; calculating a distance from a side of a first bounding box to a side of a second bounding box; and determining, based on the calculated distance, a source code alignment.

Abstract: Aspects relate to apparatuses and methods for using machine learning to classify a user to a posting. An exemplary apparatus includes at least a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to acquire a plurality of user inputs from a user, acquire a plurality of posting inputs from postings, associate each posting input of the plurality of posting inputs to a posting category, compare the plurality of user inputs to the plurality of posting inputs, and classify the user to a posting category as a function of the comparison.

Abstract: A system and method for matching students to tutors is disclosed. In particular, a user submits a query and in response a plurality of tutors are identified responsive to the search query. The identified tutors are then ranked based on relevance to the search query. The identified tutors are then presented to the user in an order based on the relevance score assigned to each tutor.

Abstract: An apparatus is configured to identify a plurality of temporal ranges, associated with a plurality of first identifiers and a plurality of sets of descriptive data, generate a plurality of temporal sections, wherein generating further includes dividing each temporal range into at least a temporal section of the plurality of temporal sections, receive at least a second identifier, wherein the at least a second identifier is associated with at least a temporal constraint and a set of second identifier data, classify, as a function of the inputs, the at least a first identifier to a particular temporal section of the plurality of temporal sections as a function of the plurality of sets of descriptive data and the at least a set of second identifier data and output the particular temporal section.

Abstract: Methods, computer-readable media, software, and apparatuses may calculate and inform a consumer of company privacy scores corresponding to companies with which the consumer has a corresponding account, or for a company associated with a website that a consumer may visit. A consumer privacy score may also be determined, based on the company privacy scores. The company privacy scores may be based on a calculation including elements of a privacy practice of the corresponding company and elements of a privacy policy of the corresponding company.

Abstract: A method for controlling a cooking device includes the following steps: recording an image of food; implementing a recognition of the recorded image of the food to determine the likelihood that the food corresponds to known foods. If a probability value exceeds a default threshold value, a cooking program associated with the known food is selected and specified to the cooking device. The probability value for the recorded image and the associated food is increased in response to a user subsequently starting the selected cooking program, and reduced in response to the user discarding the selected cooking program. A cooking device includes a primary control unit for controlling the cooking functions; a network interface with a second control unit, and a camera for recording images of the cooking space. The second control unit processes recorded images independently of the primary control unit and transmits them over the network interface.

Abstract: Apparatus and methods for classifying applications to posts using immutable sequential listings. Apparatus includes a processor configured to receive application data, browse postings, select a posting entry, and forward posting to a remote device. Apparatus utilizes a comparison method to compare postings to application data in order to forward application data to the posting.

Abstract: An apparatus for classifying and neutralizing bias, wherein the apparatus includes a computing device configured to receive candidate data items as a function of a candidate application, identify a potential bias of the candidate data items, and block the potential bias by removing the candidate data item associated with the potential bias from the candidate application.

Abstract: A method includes retrieving information regarding a candidate from a plurality of sources, and analyzing the information regarding the candidate using one or more machine learning techniques. A plurality of questions for the candidate are generated based on the analysis. The method further includes receiving and analyzing a plurality of natural language responses to the plurality of questions from the candidate, and computing a plurality of confidence scores for the plurality of natural language responses using the one or more machine learning techniques. The plurality of questions and the plurality of confidence scores are provided to a user via a user interface.

Abstract: A system and method are presented for combining visual recordings from a camera, audio recordings from a microphone, and behavioral data recordings from behavioral sensors, during a panel discussion. Cameras and other sensors can be assigned to specific individuals or can be used to create recordings from multiple individuals simultaneously. Separate recordings are combined and time synchronized, and portions of the synchronized data are then associated with the specific individuals in the panel discussion. Interactions between participants are determined by examining the individually assigned portions of the time synchronized recordings. Events are identified in the interactions and then recorded as separate event data associated with individuals.

Abstract: A method and system are provided to combine best practices with a new discovery method, incentive structure and tracking system for better results in the referral process, particularly in the domain of employment. Crowdsourcing using a tiered peer-to-peer referral incentive system that encourages higher quality inbound leads combined with data analytics and machine learning techniques of identifying high quality referrers and candidates improve success rates, and leveraging online and offline Social and Professional networks creates a frictionless user experience. Tracking technologies and methods inspired by the online advertising industry across a variety of platforms (desktop/handheld/wearable devices) enable improved crowdsourcing and reward strategies.

Abstract: A generation device according to the present application includes: an acquisition unit which acquires content targeted for disclosure (for example, an image which a user desires to disclose) and policy information which indicates a disclosure policy of the content (for example, a text which the user inputs as a caption of the image); and a generation unit which generates modified content in which a predetermined part of the content is modified based on the disclosure policy indicated by the policy information (for example, content in which an object identified based on the disclosure policy is emphasized).

Abstract: A method and apparatus for scheduling agents in a call center to meet predefined service levels, wherein communications are associated with queues representing categories of communications, the queues including at least one concurrent queue of concurrent communications, wherein multiple concurrent communications can be handled concurrently by a single agent. The method includes executing a simulation to determine an effectiveness of plural agents. The simulation includes computing a skill group weighting (SGW) for each agent for at least one concurrent queue and at least one interval based on: tc, the time spent by the agent on queue C communications tall, the time spent by the agent on all concurrent communications te, the elapsed concurrent time for the agent tn, the non-idle time of the agent; and Agents are scheduled based on the SGW and max capacity of concurrent communications for each agent.

Abstract: A machine learning (ML) process can include teaching, with a teaching set, a first ML algorithm to generate one or more machine-predicted results. One or more weights can be generated based on the one or more machine-predicted results and the teaching set. A second ML algorithm can be generated based on the one or more weights. Via the second ML algorithm, one or more machine-learned results can be generated. A description of one or more candidates can be received. Based on the one or more machine-learned results, a respective likelihood of interest in a CCG class of positions for each of the one or more candidates can be generated. A respective communication can be transmitted to each of a subset of the one or more candidates open to the respective likelihood of interest in the CCG class of positions for the subset above a threshold.

Abstract: Providing access to content is disclosed. An indication of a context is received. Access is provided to a context-relevant subset of a body of managed content. In some cases, the context-relevant subset includes a document relevant to the content.

Abstract: Various embodiments provide a method of connecting an employer with a candidate, comprising: receiving criteria data from the employer regarding a job opening; receiving background data from the candidate; recording data of the candidate in a video interview; analyzing the data of the candidate with speech-to-text analysis to identify candidate data, comparing real-time connection attributes to the candidate data; if a threshold amount of real-time connection attributes are satisfied by the candidate data, then sending, a first offer to the employer for a real-time connection with the candidate; receiving an employer acceptance of the first offer for a real-time connection with the candidate; sending a second offer to the candidate for a real-time connection with the employer; receiving a candidate acceptance; and connecting the candidate and the employer in real time by establishing a live audio connection or a live audio and video connection.

Abstract: According to various aspects, systems and methods are provided for automatically matching recruiters to job openings. The system may train one or more models that determine a measure of compatibility between a recruiter and a job opening. The system may train the model(s) using stored records of activity tracked by the system. The measure of compatibility may be used to determine whether a recruiter is likely to place a candidate for a job opening. Some embodiments provide a system that can collect objective data about recruiters and hiring parties, and use the objective data to train the model(s).

Abstract: A method includes receiving uncompilable code from a candidate. The method further includes extracting features from the uncompilable code. The method further includes outputting, with a coding machine-learning model, compilable code based on the uncompilable code and the extracted features. The method further includes generating a coding score based on the uncompilable code and the compilable code. The method further includes receiving first media of one or more answers to questions provided by the candidate during an interview. The method further includes outputting, with a media machine-learning model, one or more corresponding ratings for the one or more answers. The method further includes generating a media score based on the one or more corresponding ratings. The method further includes generating a total score based on the coding score and the media score.

Abstract: In an example embodiment, a screening question-based online screening mechanism is provided to assess job applicants automatically. More specifically, job-specific questions are automatically generated and asked to applicants to assess the applicants using the answers they provide. Answers to these questions are more recent than facts contained in a user profile and thus are more reliable measures of an appropriateness of an applicant's skills for a particular job.

Abstract: A system providing for user-initiated, account-type limiting, association-limiting, and duration-dependent public access file disclosures over a semi-private network.

Abstract: Disclosed herein are methods and systems to generate and communicate interactive digital proofs of transaction. In one implementation, the method may include receiving an indication of a payment transaction between a merchant and a user and processing payment for the payment transaction. The payment processing system generates one or more interactive digital proofs of transaction including at least details of the payment transaction and availability of a vacancy or resource at the payee location. The user may respond via the interactive receipt.

Abstract: An information processing apparatus managed by an administrator and used by plural users includes a reception unit and a request unit. The reception unit receives a disclosure request from the administrator related to secret information in a job processed by the information processing apparatus. The request unit requests a disclosure of the secret information with respect to a user of a target job that is a target of the disclosure request.

Abstract: In some embodiments, a method can include receiving a set of job descriptions and a set of candidate profiles. Each job description is associated with a first subset of candidate profiles from the set of candidate profiles. The method can further include executing a model to identify, from the first subset of candidate profiles, a second subset of candidate profiles that satisfy a fit metric and a third subset of candidate profiles that does not satisfy the fit metric. The method can further include calculating a bias metric based on a true positive value, a false positive value, a true negative value, and a false negative value that were calculated based on auditing the second subset of candidate profiles and the third subset of candidate profiles. The method can further include updating the set of job descriptions based on the bias metric.

Abstract: A method and a multi-directional attribute matching system (MAMS) determining a degree of match between item profiles with respective attributes possessed (AP) and respective attributes needed (AN) of varying credibility and varying importance are provided. The MAMS receives an attributes possessed list including the AP and an attributes needed list including the AN, from a predefined attribute list database. The AP and the AN have parent attributes or hierarchical sub-attributes. The MAMS merges multiple occurrences of AP and inputs to the attributes possessed list. The MAMS generates a matched attribute list for a side by matching the AP in an item profile with the AN in an item profile of another item by matching the AP with the AN. The MAMS computes a raw score and an attribute match score for each side using match formulae and computes a final score of the multi-directional match between the item profiles.

Abstract: Apparatuses, computer readable medium, and methods are disclosed for verifying skills of members of an online connection network. The apparatus, computer readable medium, and methods may include a method including responding to a first member of the online connection network indicating a skill possessed by the first member by selecting a skill verification user interface (UI) to present to a second member of the online connection network where the first member and the second member are connected via the online connection network. The method may further include presenting the skill verification UI to the second member, where the skill verification UI presents an indication of the first member, an indication of the skill, and a query regarding a competence level of the skill possessed by the first member. The method may further include receiving a response to the query and determining a skill validation value of the skill for the first member based on the response and a machine learning model.

Abstract: A platform for providing employment assistance services to enterprises and candidates is disclosed. For example, the platform trains, based on personal attributes of employees of multiple enterprise and work culture attributes associated with each employer of the multiple enterprises, a machine learning model that defines associations between the personal attributes and the work culture attributes. Further, the platform extracts information associated with a person from one or more sources on the Web where the person is represented, generates, based on the information associated with the person, a user profile associating personal attributes with the person, applies the user profile to the machine learning model; and receives an indication, from the machine learning model, of an employer profile that is compatible with the user profile, the employer profile including work culture attributes associated with an employer.

Abstract: The present disclosure provides a method for identifying and representing potential next positions based on current position of user of an opportunity network system, the method including: (a) collecting and pre-analysing a comprehensive database of resumes or profiles of users, (b) extracting normalized entity information from resumes or profiles about backgrounds of users, (c) normalizing of the entity information of the users using at least one of machine learning techniques or statistical techniques to obtain normalized entity information, (d) identifying a comprehensive set of possible subsequent positions for the user based on the current position, (e) generating a position-detail profile for one or more of possible subsequent positions based on the profiles of people who are currently in that position or who may have previously worked at the position, and (f) determining a degree of match between resume or profile information of the user and at least one the position-detail profile of the target positi

Abstract: The present disclosure provides a method for identifying, ordering, and contacting candidates for a target position based on a position detail profile for the target position. The method includes determining a position detail profile for the target position based on background details of users currently in a role corresponding to the target position, automatically determining a set of position-detail keywords for a search query to find one or more candidates for the target position, automatically prioritizing the set of position-detail keywords based on at least one of a frequency of occurrence of the keywords in the background details of the users currently to obtain a prioritized set of keywords, executing a search query based on the prioritized set of keywords to obtain a candidate list, determining a compatibility score between candidates in the candidate list, ordering the candidate list based on the compatibility scores of candidates.