Abstract: The present disclosure provides a method and an apparatus of matching data, a device and a computer-readable storage medium, which are related to the field of artificial intelligence technology, and in particularly to the field of intelligent search and deep learning. The specific implementation solution includes: obtaining a first instance of a resume and a second instance of a job profile; determining, for a meta path, a resume feature data of the first instance and a profile feature data of the second instance, the meta path is a knowledge graph path from the resume to the job profile; and applying a classification model to the resume feature data of the first instance and the profile feature data of the second instance to determine a matching result between the first instance and the second instance.

Abstract: The method and system of the present disclosure facilitate automatic, and in an objective manner, selection of an optimal set of technical questions, from a question bank, personalized for a candidate. This ensures consistent, standardized, efficient and objective interviews that result in high quality recruitment, given the diversity of candidates, complexity of job requirements and interviews are inherently subjective. The state-of-the-art depends on responses so far, to generate on-the-fly questions causing a cognitive load on the interviewer. Also, there is no guarantee on the breadth and depth of concepts assessed in each interview. In the present disclosure, skill graphs are employed to create a semantically rich and detailed characterization of questions in terms of concepts. Optimization formulation uses the skill graph to generate constraints, content balancing and objective functions for selection of questions.

Abstract: Advanced infrastructure management. In an embodiment, infrastructure domain(s) are imported. Each domain comprises representations of infrastructure asset type(s), activity type(s) related to the asset type(s), and standards and compliance parameters related to the asset type(s). A plurality of representations of infrastructure assets of the asset type(s) are stored. Each of the representations of infrastructure assets comprises location information representing a geolocation of the asset, and updated location information is continually received for infrastructure asset(s), such that the location information for those infrastructure asset(s) is continually updated. In addition, at least one rating is generated for each of the infrastructure assets based on the standards and compliance parameters, and workplan(s) comprising activity(ies) to be performed on infrastructure asset(s) may be generated.

Abstract: Disclosed embodiments provide a framework for processing sets of credentials in real-time using machine learning models to identify requisitions that can be recommended to users. In response to receiving a set of credentials from a user, a system assigns a classification to the set of credentials based on a set of characteristics associated with the set of credentials. A machine learning model is used to assign tags to the text of the set of credentials. These tags correspond to the set of characteristics. Using these tags, a set of open requisitions are identified and provided to the user.

Abstract: A method implements influencer segmentation detection. The method includes selecting transaction data for a time window and processing the transaction data for the time window to generate a graph for the time window. The method further includes extracting, from the graph, a feature set for a node of the graph for the time window and processing the feature set to generate a predicted rank for the node for a subsequent time window using a machine learning model. The method further includes selecting, using the predicted rank, an entity identifier corresponding to the node and presenting the entity identifier.

Abstract: Disclosed are various embodiments for a predictive communication system. In one embodiment, a communication is received from a user, and a profile associated with the user is identified. Real-time activity data associated with the profile and obtained from one or more internal channels via a messaging bus is accessed. A redeemable value accumulation in the activity data is determined to have reached a specified threshold. An intent prediction alert associated with the communication is determined according to one or more of a plurality of intent prediction rules based at least in part on the redeemable value accumulation reaching the threshold, where the intent prediction alert includes a predicted reason for the communication.

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: An apparatus and method for classifying a multi-channel user data set to a program category configuring the processor to receive user data by displaying a graphical user interface, the graphical user interface having at least a user input field, receiving, at the user input field, a first element of user data and capture, using a sensor, a second element of user data, wherein the second element of user data indicates a current user state, determine a user compatibility with a plurality of program category admission requirements as a function of user data utilizing a machine-learning model, wherein generating the machine-learning model comprises receiving training data, wherein the training data comprises user data inputs correlated to user compatibility outputs and determining, using the machine-learning model, as a function of the user data, the user compatibility with program category admission requirements, generate program category data for a user as a function of user data and user compatibility and gene

Abstract: Described is a system for social interaction regarding features based on geolocation. The system includes a server having a memory storing geo-grouped feature data and a user computing device coupled to the server. The server may be programmed to receive location information from the user computing device to automatically determine a feature or features near a location of the user computing device The server automatically finds and retrieves geo-grouped feature data corresponding to the feature and automatically delivers the geo-grouped data to the user computing device for access as bubbles of data floating above the feature. The server can then receive and store a post from the user computing device as part of the geo-grouped feature data. The system allows users to interact with each other without preestablished connections of users.

Abstract: Provided are systems and methods for determining behaviors of a user that are associated with earning secondary income. In one example, a method may include receiving a request from a user device, identifying productivity attributes and consumption attributes of a user associated with the user device based on behavior of the user captured over time, determining a recommended value-generating behavior for the user via execution of a collaborative filtering model, where the collaborative filtering model receives the productivity and consumption attributes of the user and determines the recommended value-generating behavior based on historical value-generating behavior of other users having similar productivity attributes and consumption attributes, and transmitting the recommended value-generating behavior to the user device via a content channel between the server and the user device.

Abstract: An embodiment for dynamic categorization of information technology (IT) service tickets is provided. The embodiment may include logging an IT service ticket when text is entered into a description field. The embodiment may also include creating a filtered description field by processing the text entered into the description field. The embodiment may further include computing a set of exponential weights and assigning the set of exponential weights to each word in the filtered description field. The embodiment may also include multiplying the set of exponential weights by the word's TF-IDF score to determine an IT service ticket category for placement of the IT service ticket into the IT service ticket category. The embodiment may further include generating features for machine learning, utilizing the generated features to build a supervised machine learning model, and evaluating the supervised machine learning model through analyzation of data from historical IT service tickets.

Abstract: Various embodiments are provided for intelligent application of operational rules to operational data in a computing environment by a processor. One or more operational rules may be extracted and formalized from a knowledge graph, a domain knowledge, or a combination thereof describing one or more operational policies and conditions. The one or more operational rules may be applied to operational data to identify and filter non-compliant operational data.

Abstract: A method, computer system, and computer program product are provided for managing reports. A subset of data fields is identified for inclusion in a new report. An intent of the new report is determined based on the subset of data fields. The intent is determined using a set of machine learning models trained from a set of existing reports and a taxonomy of human capital management (HCM) information. Based on the intent determined by the artificial intelligence system, a set of additional fields is predicted for the new report. The set of the additional fields is displayed in a graphical user interface on a display system.

Abstract: A system and method for enrolling new carwash customer account profiles can or automatic access to carwash equipment. Baseline information is collected along with vehicle images for quick enrollment. The new customer can enter the carwash right away. As long as the account remains unclaimed the system periodically sends reminder messages. The unclaimed account can still wash, and the registration can be completed on the customer personal device while the vehicle is being washed or another convenient time. This provides a quick and easy way to register a new customer for a carwash subscription service or pay per wash product with automatic capture of much of the customer information—reducing the number of steps for the customer and team member operating the point-of-sale device. There is no need for manual entry of credit card information or vehicle information, enhancing enrollment efficiency for the customer.

Abstract: An apparatus and method for candidate tracking. The apparatus includes a processor that is configured to track a candidate through the recruiting process such that a recruiter may be compensated for their recruiting efforts. The apparatus includes receiving data sets from the recruiter and the employer, receiving a transfer request from either user, authenticating the users, determining if the data sets are the same, and processing the transfer request.

Abstract: Implementations generally relate to a method of matching job-seekers and employers in real-time with low required effort by the job-seekers and employers. A system-wide taxonomy is used in matching job-seekers and employers, thereby reducing the time for the recruiting process. Employers create a job position, and specify the relative importance of traits associated with the job position. Job-seekers answer profile questions (e.g. work experience), and the system uses the taxonomy to generate a list of job-seeker skills based on the answers to these questions. A list of job-seekers is then generated for the job position based on a mapping of the available job-seekers' skills and the employer rankings of the job position traits. A number of additional factors, like job seekers' in-app engagement, are used to further sort and filter the list of job-seekers.

Abstract: A method comprises generating a graphical user interface including a list of government representatives associated with a geographical indicator of a user, the list of government representatives allowing the user to select multiple government representatives for messaging simultaneously, and a plurality of links, each link of the plurality of links being associated with a corresponding government representative and configured to direct the user to a corresponding profile page of the corresponding government representative when selected. The method further comprises displaying the graphical user interface on a display of a user device associated with the user. The method further comprises receiving a selection of a link of the plurality of links from the user via the graphical user interface. The method further comprises displaying, based on the selection of the link, the corresponding profile page associated with the corresponding government representative.

Abstract: A method and system for determining collaboration between employees is disclosed. In some embodiments, the method includes receiving a plurality of collaboration parameters associated with a set of employees. The method further includes creating a plurality of employee nodes associated with the set of employees in a hierarchical tree, based on the plurality of collaboration parameters and a first pre-trained machine learning model. The method further includes generating a plurality of vector embeddings associated with the plurality of employee nodes, based on the first pre-trained machine learning model. The method further includes determining a degree of collaboration between at least two employees from the set of employees based on one or more vector embeddings from the generated plurality of embeddings.

Abstract: An electronic data review session is conducted between a host and a user needing to review specific accurate performance data that assists in mitigating the risks in hiring a musical act or artist for a performance in their venue. An established agreement between the host and client that supports the sharing the artist's performance data, bi-directionally, through an electronic communication interface using protocols of the World Wide Web is established between the host and the client and provides the client with access to web pages which are displayed on the client's computer using a standard web browser. In response to client applied filters, a subset of relevant, accurate performance data is displayed on web pages and served by the host to the client that may include data that was provided by the client or other clients.

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.