A system for classifying tasks based on workflow patterns detected on workflows through a real time video feed that shows steps being performed to accomplish a plurality of tasks. Each task is associated with a different set of steps. The system accesses a first set of steps known to be performed to accomplish a first task on the webpages. The first set of steps is represented by a first set of metadata. The system extracts a second set of metadata from the video feed. The second set of metadata represents a second set of steps to perform a second task. The system determines whether the second set of metadata corresponds to the first set of metadata. If it is determined that the second set of metadata corresponds to the first set of metadata, the system classifies the second task in a class to which the first task belongs.

A method, apparatus, and system of activating and using a contactless card are disclosed. A method includes receiving a transaction card application for a contactless transaction card from an applicant; issuing a contactless transaction card based on the transaction card application, wherein the contactless transaction card comprises a uniform resource locator (URL) embedded thereon; and activating the contactless transaction card in response to receiving information from a contactless communication between the contactless transaction card and a customer device, wherein the contactless communication causes access to a web site associated with the URL.

Systems and methods for performing a complete assessment of a disconnected environment to determine if any prerequisite components (dependencies) necessary for the installation of cloud infrastructure are missing from the disconnected environment and generating a report based on the assessment are provided. An offline bundle having an assessment playbook may be imported into the disconnected environment. The assessment playbook may determine whether the disconnected environment includes each of a set of prerequisite components of the cloud infrastructure and generate a report indicating one or more of the set of prerequisite components that are missing from the disconnected environment. An automation playbook may be generated based on the report, wherein the automation playbook installs each of the one or more of the set of prerequisite components that are missing from the disconnected environment.

Systems and methods for performing a complete assessment of a disconnected environment to determine if any prerequisite components (dependencies) necessary for the installation of cloud infrastructure are missing from the disconnected environment and generating a report based on the assessment are provided. An offline bundle having an assessment playbook may be imported into the disconnected environment. The assessment playbook may determine whether the disconnected environment includes each of a set of prerequisite components of the cloud infrastructure and generate a report indicating one or more of the set of prerequisite components that are missing from the disconnected environment. An automation playbook may be generated based on the report, wherein the automation playbook installs each of the one or more of the set of prerequisite components that are missing from the disconnected environment.

Apparatus and methods for sharing bookmarks are provided. Bookmarks may include queries to a chatbot or other interactive application. A server may include a shared bookmark controller and a personal computing device may include a user bookmark controller. A user may save a bookmark and share the bookmark with a chosen recipient. The user bookmark controller may send the bookmark and the identity of the recipient to the shared bookmark controller. The shared bookmark controller may then send the bookmark to the recipient and record whether the recipient saves or rejects the bookmark. Bookmarks may be collated and categorized into groups, and entire groups may be shared.

A centralized system may collect and aggregate assessments from multiple websites. An aggregate score may be calculated for the resource that cumulatively considers assessments from a plurality of different websites from which assessments are received from users. Text descriptions associated with each of the assessments may be provided to a machine-learning system that uses a trained model to assign identifiers to the assessments as they are received. These identifiers may include common words or text that are descriptive of different facets of user experiences related to receiving and using the resource. After selecting one or more identifiers, assessments associated with that identifier may be included or excluded from the display. Additionally, the overall aggregate score for the resource may be recalculated by removing components of that score that are based on assessments with identifiers that have been selected for exclusion.

A centralized system may collect and aggregate assessments from multiple websites. An aggregate score may be calculated for the resource that cumulatively considers assessments from a plurality of different websites from which assessments are received from users. Text descriptions associated with each of the assessments may be provided to a machine-learning system that uses a trained model to assign identifiers to the assessments as they are received. These identifiers may include common words or text that are descriptive of different facets of user experiences related to receiving and using the resource. After selecting one or more identifiers, assessments associated with that identifier may be included or excluded from the display. Additionally, the overall aggregate score for the resource may be recalculated by removing components of that score that are based on assessments with identifiers that have been selected for exclusion.

An online system presents content to its users, in which the content includes links that launch a messaging application and initiate conversations via the application. The system receives information indicating that negative experiences occurred during the conversations and may use this information and attributes of entities participating in the conversations to train a model to predict a likelihood of an occurrence of a negative experience. Upon determining an opportunity to present a user with a link that launches the application and initiates a potential conversation with an entity via the application, the system applies the model to predict a likelihood of an occurrence of the negative experience by the user during the potential conversation based on the entity's attributes. Based on the predicted likelihood, the system adjusts a value associated with presenting the link and passes the adjusted value to a process that selects content for presentation to the user.

A method for generating an electronic file associated with health care professionals (HCPs). The method includes receiving health information from a covered entity computing system and a file generation request from a user computing device. The method further includes matching HCP information with the health information and determining one or more statistical values based on at least one of the matched HCP information or the matched health information. The method further includes generating the electronic file including the one or more statistical values and at least a portion of the matched HCP information and providing the file to the destination address of the file generation request. The electronic file is generated as the file type identified by the file generation request, and is structured based on at least one of the file generation request or the file destination.

A method for generating an electronic file associated with health care professionals (HCPs). The method includes receiving health information from a covered entity computing system and a file generation request from a user computing device. The method further includes matching HCP information with the health information and determining one or more statistical values based on at least one of the matched HCP information or the matched health information. The method further includes generating the electronic file including the one or more statistical values and at least a portion of the matched HCP information and providing the file to the destination address of the file generation request. The electronic file is generated as the file type identified by the file generation request, and is structured based on at least one of the file generation request or the file destination.