Abstract: A method and system for providing a data consolidation for improved customer communication and agent performance evaluation in a multi-channel contact center are provided. The method includes receiving interaction data of an agent with customers across different communication channels within the contact center, consolidating the interaction data received across the different communication channels, aggregating the consolidated data to generate a set of metrics indicative of agent performance, inputting the set of metrics into an agent performance measurement framework, and determining a performance score for the agent based on an output of the agent performance measurement framework.

Abstract: Described are systems and methods for product recommendation refinement in a topic-based virtual storefront embedded in a topical community web page. A system and method may facilitate determining user and community member activity in the virtual storefront based on which weighted keywords are derived. A topic set containing various weighted keywords may be iteratively configured for extracting and ordering one or more products that are extracted from a plurality of heterogeneous sources. A server may be configured for refining the topic set by modifying a baseline session keyword weight or a baseline contextual keyword weight based on a total topic set weight, an elasticity parameter, core topic keyword weights associated with core topic keywords, session keyword weights, and/or contextual keyword weights; and identifying, based at least on the configured topic set, products to be presented to a user as product recommendations in the virtual storefront.

Abstract: A computer-implemented method and system for streamlining interactions between a customer and a customer service representative of a company. An interaction is commenced between the customer and the customer service representative during which historical data is accessed related to the customer stored in a company controlled computer system responsive to the interaction. The historical data preferably relates to at least one product or service provided by the company to the customer. At least a part of the historical information is displayed to the customer service representative. On the display, a first tab is generated related to the historical data as is a second tab relating to a quote for a new product or service for offering to the customer. The customer service representative is thereafter enabled to switch between displaying the historical data and the quote by selecting the first or second tab, respectively, without having to save the quote.

Abstract: A system and method for comparative performance monitoring of software release versions is disclosed. A remote network management platform may include a computational instance for managing a network. Transactions between a server of the computational instance and a client device in the managed network may be logged to a database. Transactions may be carried out by a release version of a set of program code units executing on the server. A software application executing on a computing device may retrieve and analyze a first set of transactions carried out by a first release version of the set of program code units to determine a first set of performance metrics, and do the same for a second set of transactions carried out by a second release version of the set of program code units to determine a second set of performance metrics.

Abstract: A validation system and method are provided that examine data for use in tracking and/or generating an action plan. Data is received and stored at an implementation data store from production data sources. Evaluation rules are applied to the data by a data storage system. The evaluation rules are applied by running previously created scripts of commands of the data storage system. Applying the evaluation rules to the one or more sets of the data outputs a deviation measure for at least one of the sets of the data. The deviation measure and a restricted list of defined validation decisions is presented to an analyst for the data. A selected validation decision is received, and the data is validated for use in the action plan, rejected for use in the action plan, or identified as requiring additional analysis before being validated for use in the action plan.

Abstract: A machine learning device, which learns an operation program of a robot, includes a state observation unit which observes as a state variable at least one of a shaking of an arm of the robot and a length of an operation trajectory of the arm of the robot; a determination data obtaining unit which obtains as determination data a cycle time in which the robot performs processing; and a learning unit which learns the operation program of the robot based on an output of the state observation unit and an output of the determination data obtaining unit.

Abstract: A computer system for identifying merchant category code misclassifications includes at least one processor in communication with a transaction database and a high-risk merchant database. The transaction database stores transaction records by a plurality of account holders. The high-risk merchant database stores high-risk merchant records each associated with high-risk merchants. The processor queries the transaction database for transaction records and calculates a high-risk cardholder metric for each of the account numbers. The at least one processor further queries the transaction database for transaction records including (i) the account number of high-risk cardholders, and (ii) a merchant identifier associated with other than the plurality of high-risk merchants, to retrieve a second set of transaction records. The at least one processor further calculates a high-risk merchant metric for each of the merchant identifiers, identifying a MCC misclassified merchant.

Abstract: A method and system for electronically annotating an image, or preferably, specific portions of an image, with information. In one aspect, a user may generate an image, annotate the image, and upload or otherwise disseminate the annotated image to a web page or the like. Annotations are provided as labels that provide information about the image or items therein. Further users may access the labels to access the information. The labels further enable searching and contextual advertising.

Abstract: An embodiment may involve storing, by a computing device and in a database, a set of pangenetic attributes of a set of individuals, wherein the pangenetic attributes of the set are respectively and statistically associated with products; based on the statistical associations between the pangenetic attributes and the products, determining, by the computing device, product recommendations for a second set of individuals; receiving, by the computing device and from the second set of individuals, a plurality of measures of satisfaction with the product recommendations; based on the plurality of measures of satisfaction, learning, by the computing device, an association between a subset of the pangenetic attributes and a particular product; and storing, by the computing device and in the database, the learned association, wherein the learned association provides a basis for subsequent recommendations of the particular product when a subsequent individual exhibits the subset of the pangenetic attributes.

Abstract: Embodiments described herein are configured to generate a smart contract deployed to a distributed ledger platform. In particular, a first party and a second party negotiate the terms of an engagement, jointly choose a mediator from those available on a social networking platform, and choose a smart contract template, and a user interface is thereafter presented to the parties for inclusion of negotiable elements. Upon agreement, a smart contract is thereafter generated and deployed to a smart contract platform such as, for example, a blockchain. Embodiments permit escrow of funds to the smart contract platform. Embodiments of the smart contract enable the parties to indicate completion or take other actions with respect to the engagement, or to initiate a dispute in which case, a chosen mediator is thereafter enabled by the smart contract to mediate the dispute through one or more smart contract actions made available to the mediator.

Abstract: An approach is provided for fully-automated learning to match heterogeneous feature spaces for mapping. The approach involves determining a first feature space comprising first features and a second feature space comprising second features, and classified by a feature detector into a first attribution category and a second attribution category, respectively. The approach further involves calculating a first similarity score for the first feature space based on a first distance metric applied to the first features, and a second similarity score for the second feature space based on a second distance metric applied to the second features. The approach also involves determining a transformation space comprising a first weight to be applied to the first similarity score and a second weight to be applied to the second similarity score based on matching the first attribution category and the second attribution category.

Abstract: Embodiments relate to a method comprising: analyzing a historical data of an entity over a past period comprising a past transaction and a past revenue to develop a buyer persona of a customer in order to identify ideal prospects; selling a target revenue goal for the entity; generating revenue economics using conversion metrics from the target revenue goal as an input; generating a marketing budget working backward from the revenue economics; and generating a marketing plan for a future period that is based on the marketing budget; wherein the method comprises conducting a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis to take an inventory of current situation of the entity and to identify target market segments by generating the opportunities that are in alignment with the strengths of the entity; and wherein the method is for generating a growth master plan for the future period.

Abstract: A recording medium records a simulation program for causing a computer to execute a process including: arranging an agent, which has cognitive information and behaves in a virtual space based on the cognitive information, in the virtual space in which a plurality of guidance displays is set; when, with respect to each of the plurality of guidance displays, the agent enters within a first range of the respective guidance displays, and first guidance information corresponding to the first range is related with a destination of the agent, changing cognitive information up to the destination of the agent; and when, with respect to each of the plurality of guidance displays, the agent enters within a second range different from the first range, and second guidance information corresponding to the second range is related with the destination of the agent, changing cognitive information not directly related with the destination of the agent.

Abstract: A system, method, and computer-readable medium are disclosed identification of demand for documentation for particular languages and facilitate modification of documentation to the particular languages based upon demand. A multi-region document revision model which includes a correction factor, provides for monitoring of how information is being consumed in different regions via different platforms. Identification is performed for demand for documentation for particular languages and facilitates modification of documentation to the particular languages based upon demand. Various internal and external social media platforms are searched to provide a data set which can then be used to customize a language set for a particular language. In certain implementations the documentation includes respective semantic files which are used by a /business unit to validate and update the documentation.

Abstract: Provided is a server. The server comprises a communicator configured to receive or transmit data from or to an external network and a processor configured to receive, through the communicator, service data of an electronic device, device data of the electronic device, and weather data for the electronic device and to calculate emotion index data based on the service data, the device data, and the weather data. Accordingly, customer's emotion index data may be efficiently calculated.

Abstract: One embodiment relates to a financial institution computing system. The financial institution computing system includes a network circuit enabling the financial institution computing system to exchange information over a network and a risk analysis circuit. The risk analysis circuit is configured to receive user information, simulate a plurality of investment outcomes for a first investment risk level based on the received user information, display at least one augmented reality or virtual reality depiction of at least one of the investment outcomes via a display device, monitor a reaction of the user to each displayed augmented reality or virtual reality depiction, and select an investment strategy for the user based on the reactions of the user.

Abstract: Methods and systems of optimization constraint adaptation for long-term target achievement. One system includes an electronic processor configured to divide a multiple time-step optimization problem into a plurality of successive single time-step optimization problems. The processor is configured to determine a first optimal variable value for a first single time-step optimization problem and determine a first resulting value of a secondary quantity based on the first optimal variable value. The processor is configured to determine a first divergence of the first resulting value from a first target value and determine a cumulative target divergence based on the first divergence. The processor is configured to determine a first target value adjustment for a second time-step based on the cumulative target divergence, adjust a first original target value of the secondary quantity for the second time-step using the first target value adjustment, and output the adjusted first original target value for display.

Abstract: Systems and methods for generating customer ID within an E-commerce platform are provided. Based on customer interactions with the e-commerce platform, evidence is collected, such as telephone numbers, names, addresses etc. The evidence is standardized to allow comparison/correlation. The evidence is then filtered to remove certain evidence determined to be unreliably associated with specific customers. For example, many customers may enter a fake phone number “0000000000”. Then, correlation is performed based on the filtered evidence to identify links between the evidence and associate sets of linked evidence with unique customer IDs.

Abstract: A technique for predictive modeling to generate ratings forecasts in a media network is described. An episode-level programming schedule is imported into a viewership forecasting application to generate episode-level ratings predictions. Episode-level ratings predictions for media content in the episode-level programming schedule are generated by implementing multiple different predictive algorithms in parallel for each instance of specific media content in the programming schedule. In addition, for each such predicted viewership value, an accuracy value is generated that indicates the likely accuracy of that predicted viewership value. The episode-level ratings predictions can be uploaded by a business unit of the media network, and merged with a programming schedule currently employed by the business unit.

Abstract: A method of determining a second alimentary provider is disclosed. The method inputs an order for an alimentary combination from a user. The alimentary combination is prepared by a first alimentary provider. The method classifies a plurality of alimentary providers. The method computes a alimentary provider score for a plurality of second alimentary combinations prepared by the plurality of alimentary providers as a function of a first machine-learning process, the machine learning process trained by training data correlating alimentary provider scores to alimentary combinations. The method selects a second alimentary provider from the plurality of alimentary providers as a function of the alimentary provider score. The method outputs the second alimentary provider to the user. A system of determining a second alimentary provider is also disclosed.

Abstract: A user establishes an account with an account management system and downloads a service application on a user computing device associated with the user. The user enters a service provider location and signs into a service application. A service camera device captures a video feed of one or more users within a visual field of the service camera device and a service computing device compares movement data received from user computing devices at the service provider location against movement of detected objects in the video feed to identify one or more users in the video feed. After identifying the one or more users within the video feed of the service camera device, in response to a particular user initiating a service request at the service computing device, the service computing device identifies the particular user at the service computing device as being within a service area of the video feed.

Abstract: Systems and methods are disclosed for determining an estimate of available user impressions on a network, comprising receiving a request for an estimate of available user impressions for viewing one or more media elements on a network, the request comprising one or more viewer demographic group limitations. A request may be received to include deterministic users and probabilistic users in the estimate of available user impressions. A number of deterministic users may be determined based on query results from a deterministic user data set. A number of probabilistic users may be determined based on query results from a probabilistic user data set, and the estimate of available user impressions may be determined based on the number of deterministic users and the number of probabilistic users.

Abstract: Systems as described herein may include making recommendations for patterned purchases. Transaction information for a user that is associated with a plurality of merchants in a geographic location may be received. Frequencies of visits and transaction patterns associated with the plurality of merchants may be determined. Risk factors and a success rate that the user to complete shopping successfully may be determined. In a variety of embodiments, after detecting that the success rate falls below a threshold value, a recommendation for the user to shop at an alternative merchant and alternative time/date may be presented to the user.

Abstract: Systems and methods to determine when to rejoin a live media broadcast after an interruption are presented herein. Weighting information including individual weights conveying importance of attribute values for a set of broadcast attributes of the live media broadcast may be obtained. One or more of the weighting information, the attribute values, and/or other information may facilitate making a determination of a rejoin point in time in the live media broadcast for rejoining the live media broadcast upon a completion of an interruption.

Abstract: Embodiments of a system as described herein may receive financial institution product information from a plurality of financial institutions distributed across a computing network. The system may also receive data from the plurality of financial institutions distributed across the computer network and create or update an ontology. A relevance score may be generated for a set of financial institution products which may, in conjunction with a campaign definition provided by a financial institution administrator, be used to associate users with a list of campaigns which may be stored as campaign data. An online banking application at a user device may request campaign data for a user. In response, the system may return campaign data for the user to the online banking application. Using the campaign data, the online banking application may select one or more products to recommend to the user and display content for the selected products on the user device.

Abstract: Automated computing machinery agnostically augmenting a CRM application, including an agent hub that associates an identity of a tele-agent and an indication whether the tele-agent is logged on to the agent hub; the agent hub operatively coupled to a browser, the browser bearing a browser extension through which a sales template for a sales campaign to which the tele-agent is assigned to work is operatively exposed as a GUI overlay of the browser, the overlay overlaid upon a web page of the CRM application; a leadership hub that associates the tele-agent and the sales campaign to which the tele-agent is assigned, the leadership hub operatively coupled to the agent hub; and a campaign management portal that associates the sales campaign and the display template, the display template associating a question and an answer form, the campaign management portal operatively coupled for data communications to the agent hub.

Abstract: Described are a system, method, and computer program product for generating real-time predictions for vehicle transportation requests using machine learning.

Abstract: Systems, programs, and media for creating virtual events and presenting the virtual event content to attendees of the virtual events are described herein. A virtual event hosting system may receive input from an event creator for creating an event comprising stages, sessions, networking, and expos. The event may provide a virtual environment for presenting users to make presentations and attendees to view and interact with the presenting users and other attendees. Data associated with the event and the attendees may be collected for analysis to improve engagement in future virtual events.

Abstract: A method for imparting sustainability credence attributes for animal source food products is provided. First, at least one animal source food product is produced. The manure associated with that production is collected and treated, and the nitrogen and phosphorus content of the manure is analyzed and time stamped. At least one sustainability outcome from the treated manure is quantified, and an animal source food product, including a product package, animal package lot, individual live animal, or a plurality of live animals, is identified and labeled, and direct and indirect sustainability outcomes are linked with the animal source food product. Sustainability outcomes are demonstrated to buyers or post-processors of animal source food products, first by combining the sustainability outcome data and food animal production data with food animal producer provenance data from the same or a corresponding time interval, and then by providing access to that data.

Abstract: Technologies for automatically validating marketing asset compliance include a marketing compliance server configured to receive a marketing asset file. The marketing asset file includes a data interchange document containing multiple objects and multiple key/value pairs. Each object is associated with a different group of the key/value pairs. The server extracts the data interchange document from the marketing asset file, parses the document to identify the different key/value pair groups, and identifies the objects of the document based on the identification of the different key/value pair groups. The identified objects are analyzed as a function of a brand rule configuration file that includes brand rules corresponding to brand marketing guidelines. Based on the analysis, the server determines whether the objects are in compliance with the marketing guidelines. The server generates an interactive compliance report and non-compliant objects can be corrected. Other embodiments are described and claimed.

Abstract: Embodiments provide a computer implemented method of evaluating one or more IR systems, the method including: providing, by a processor, a pre-indexed knowledge-based document to a pre-trained sentence identification model; identifying, by the sentence identification model, a predetermined number of query-worthy sentences from the pre-indexed knowledge-based document, wherein the query-worthy sentences are ranked based on a prediction probability value of each query-worthy sentence; providing, by the sentence identification model, the query-worthy sentences to a pre-trained query generation model; generating, by the query generation model, a query for each query-worthy sentence; and evaluating, by the processor, the one or more IR systems using the generated queries, wherein one or more searches are performed via the one or more IR systems, and the one or more searches are performed in a set of knowledge-based documents including the pre-indexed knowledge-based document.

Abstract: Reinforcement learning agents for resource allocation for iterative workloads, such as training Deep Neural Networks, are configured. One method comprises obtaining a specification of an iterative workload comprising multiple states and a set of available actions for each state, and a domain model of the iterative workload relating allocated resources with service metrics; adjusting weights of a reinforcement learning agent by performing iteration steps for each simulated iteration of the iterative workload and using variables from the simulated iteration to refine the reinforcement learning agent; and determining a dynamic resource allocation policy for the iterative workload.

Abstract: The present disclosure relates to a method for determining a completion score for a record object based on electronic activities. The method includes accessing record objects, each of which corresponds to a record object type and includes object fields having object field-values. The method includes selecting one of the record objects. The method includes identifying electronic activities transmitted or received associated with the record object. Each of the electronic activities has a timestamp indicating a receipt time or transmission time of the respective electronic activity. The method includes determining a participant of each of the electronic activities. The method includes determining a completion score indicating a likelihood of completing an event associated with the record object based on the timestamp of each of the electronic activities and the participant of each of the electronic activities. The method includes storing an association between the record object and the completion score.

Abstract: According to some embodiments, an existing risk relationship data store may contain electronic records, each electronic record including a risk relationship identifier and a risk relationship characteristic for an existing risk relationship between the enterprise and an entity. A prediction platform may receive electronic records associated with a set of existing risk relationships along with an indication of a future adjustment to a parameter associated with the set of existing risk relationships. The prediction platform may then automatically calculate a projected future impact to a key metric for the set of existing risk relationships based on the future adjustment to the parameter. A rendering platform may receive the projected future impact to the key metric and present an interactive graphical user interface, including an indication of projected future impact, to an administrator.

Abstract: An electronic device that includes a communication module and a processor operatively connected to the communication module to exchange data with an external electronic device through the communication module is provided. The processor generates user data and a user profile based on collected user information related to a plurality of items, receive learning information data related to the plurality of items from the external electronic device, generate user learning data by applying the learning information data to the user data, learn a user preference pattern based on the user learning data, update the user profile based on the learned user preference pattern, and receive recommended item data from the external electronic device based on the updated user profile.

Abstract: Methods, systems, apparatus and articles of manufacture to determine causal effects are disclosed herein. An example apparatus includes a weighting engine to calculate a first set of weights corresponding to a first treatment dataset, a second set of weights corresponding to a second treatment dataset, and a third set of weights corresponding to a control dataset, the weighting engine to increase an operational efficiency of the apparatus by calculating the first set of weights, second set of weights, and third set of weights independently, a weighting response engine to calculate a first weighted response for the first treatment dataset, a second weighted response for the second treatment dataset, and determine a causal effect between the first treatment dataset and the second treatment dataset based on a difference between the first weighted response and the second weighted response, and a report generator to transmit a report to an audience measurement entity.

Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for using metrics in association with process flows. For instance, a set of metrics associated with a flow can be generated or updated based, at least in part, on flow performance data. Provided for presentation via a display device and within a flow builder application is an indication of the set of metrics associated with the flow in relation to one or more elements of the flow. At least a portion of the set of metrics is provided for presentation in close proximity to a visual representation of an element of the flow. A request to modify the flow can be received via the flow builder application.

Abstract: A method for automatically updating electronic shopping lists of customers of retail stores may include accessing an electronic shopping list of a customer of a retail store, the electronic shopping list including at least one product associated with a shopping order; receiving image data from a plurality of image sensors mounted in the retail store; analyzing the image data to predict an inventory shortage of the at least one product included on the electronic shopping list, wherein the predicted inventory shortage is expected to occur prior to fulfillment of the shopping order; and automatically updating the electronic shopping list based on the predicted inventory shortage of the at least one product.

Abstract: Systems and methods record tracking events during a presentation of supplementary content items to determine whether viewer(s) stopped watching the supplementary content item or watched the supplementary content item in its entirety. This determination may provide value to content publishers or (multi video programming distributors (MVPDs)) through preventing such supplementary content items from showing, whether in certain contexts, to certain viewers, and/or to certain audience segments. In some instances, the systems and methods may utilize machine-learning model(s) to determine which combinations of supplementary content items, contextual signals, viewers, and/or audience segments are likely to abandonment a supplementary content item. Preventing these combinations from showing, improves viewer experiences, permits MVPDs to effectively utilize opportunities for presenting supplementary content to viewers, in order to maximize revenue yield paid by supplementary content providers (e.g.

Abstract: Computer-implemented techniques for repeatable and interpretable divisive analysis. In one embodiment, for example, a method comprises: identifying top-level cohorts of data items based on one or more characteristics of the data items in common; recursively or iteratively dividing a selected top-level cohort in a top-down manner resulting in a plurality of sub-level cohorts arranged in a hierarchy; detecting a particular data item that is a statistical outlier among data items of a leaf cohort in the hierarchy; and causing display of an indication in a computer user interface that the particular data item is an outlier.

Abstract: Computer-implemented methods for providing real-time customer, patient or accountability, security, consumer and employee metrics include: providing at least one strategic goal; providing at least one metric associated with the at least one strategic goal; providing at least one communication channel between a customer and a company; providing at least one communication code; utilizing the at least one communication code to access the at least one communication channel; providing a survey tool to the customer using the at least one communication channel; capturing data from the survey tool in a database; converting the captured data to the at least one metric; and providing the at least one metric on a dashboard application. An executable software application that implements the computer-implemented method disclosed is also contemplated.

Abstract: Computer-implemented systems and methods, trained through machine learning, score a sentiment expressed in a document. Individual sentences are scored and then overall document sentiment score is computed based on scores of individual sentences. Sentence scores can be computed with machine learning models. Digital matrix generator can generate N×M matrix for each sentence, where the matrix comprises vectors of word embeddings for the individual words of the sentence. A classifier computes a sentence sentiment score for each sentence based on the digital matrix for the sentence. Sentence sentiment scores computed by classifier can be adjusted based on a fuzzy matching of a phrase(s) in the sentence to key phrases in a lexicon that are labeled with a sentiment relevant to the context.

Abstract: Protected audience selection system. Media consumption histories of browsers which have converted are received at a modeling system where targeting of browsers is prohibity. A model is built by determining a frequency of each respective media consumption event among the histories and comparing each determined frequency of a respective media consumption event to a frequency of the respective media consumption event among a population of browsers without the conversion event. The model is sent to a targeting system which excludes conversion events. A description of the conversion event is received at the targeting system. A history of a targetable browser is received at the targeting system. The model is applied to the history of the targetable browser at the targeting system, where conversion events have been excluded from the history. Advertising content is sent to the targetable browser according to a result of applying the model.

Abstract: A method for testing medical data is provided. Each medical datum includes a plurality of information units and a plurality of separators, and the method includes the following steps: a. matching the medical data against a standard library including a plurality of patterns, a matching expression being: [\s\S][number/sequence/relation]&[\b|\B] (S101); and b. determining, based on a matching result of the step a, whether the medical datum is qualified (S102). A standardized standard library is first established, a matching result is obtained by matching the medical datum and the standard library for a non-initial boundary, an initial boundary, an information quantity, information sequences, a semantic relationship quantity, a character boundary, and a non-character boundary, and whether the medical datum meets a requirement is further determined according to the matching result.

Abstract: A method including determining a zip code of a user using a website that displays items. The method also can include receiving a selection by the user to display information about an item of the items. The method additionally can include retrieving first information including a predetermined geo-classification for the item. The method further can include retrieving second information including a list of fulfillment nodes that can currently deliver to the zip code of the user within a first shipping speed via ground shipping. The method additionally can include retrieving third information including a node-level inventory for the item. The method further can include determining a shipping speed to display to the user for the item based on (a) the predetermined geo-classification for the item, (b) the list of fulfillment nodes that can currently deliver to the zip code of the user within the first shipping speed, and (c) the node-level inventory for the item.

Abstract: A computer system, computer-implemented method, and computer program product include a processor(s) (executing code) that obtains a data set(s) related to a patient population diagnosed with a medical condition a database(s). The processor(s) identifies common features, generates patterns of the common features, and generates machine learning algorithms based on the patterns to identify presence or absence of the given medical condition in an undiagnosed patient. The processor(s) compiles a training set of data and tunes the machine learning algorithms with the training set of data. The processor(s) integrates the machine learning algorithms into a graphical user interface.

Abstract: Techniques configuring a machine learning model include receiving, via a user interface configured to communicate with a machine learning model hosted on a collaborative computing platform, a selection of a file for input to the machine learning model, a selection of content in the file for input to the machine learning model, and instructions for applying the selected content to the machine learning model, which are sent to the machine learning model. As new files are uploaded to the selected directories of the collaborative computing platform, the machine learning model is applied to the uploaded files to classify the files and extract metadata. The extracted metadata and associated classification data are stored in data structures associated with the new files. The data structures are existing data structures of the collaborative computing platform.

Abstract: In a method for communicating information about a service or product, a record can be retrieved from a database storing records of communications related to a second entity. The record can include information related to an identity of a first entity. The first entity can be defined, at a processor and based upon content of the record, as a member of a set designated to be sent the information about the product or service. The first entity can have previously engaged in a first communication related to the second entity. The second entity can be associated with the product or service. A second communication, which can include the information related to the identity of the first identity, can be sent from the processor to an advertising platform. A third communication, which can include the information about the product or service, can be sent from the processor to the advertising platform.

Abstract: An exception-resolution monitoring system determines an exception error is detected corresponding to a failed transmission of a message between servers of a distributed network. Changes are monitored that are tested and implemented to correct the detected exception errors. An executable corrective action is determined based on the monitored changes. The executable action is stored for future use and linked to a root cause of the exception error and properties of the distributed network at the time of the exception error.

Abstract: A behavior pattern search system and method is disclosed. A change in a behavior pattern contributing to improving a Key Performance Indicator (KPI) is discovered from among changes in the behavior pattern arising in common among customers having a specific characteristic. The behavior pattern search system classifies transfiguration candidates that are customers satisfying transfiguration result information. The transfiguration result information indicates a characteristic purchase behavior predicted to occur by a change in a behavior pattern of each of the customers.