A method for generating a sentiment score for a computer application user. An interface receives user input accessing a first observable goal as part of a user application. In response to receiving user input accessing the first observable goal, the system generates a first observable goal record for the first observable goal. In response to identifying an issue with the first observable goal, system tags the first observable with an issue notice tag for the issue and tracks one or more interactions that correspond to the first observable goal and the issue based on the issue notice tag. Each interaction is assigned a sentiment value score. The system generates a first sentiment score for the first observable goal by combining the sentiment value score for each of the interactions.

A method includes performing a search on a body of information based on a first perspective, wherein the first perspective is determined using a first corpus of information associated with a first particular set of people; and providing at least some results of the search. The search may be a perspective search. Results of the search may be evaluated based on a second perspective, which is based on a second corpus of information associated with a second particular set of people. The perspective may be determined using an avatar mechanism that was trained using a corpus of information.

A computer extracts from contact records that each include a contact identifier, a group identifier for each group with which the contact has had an interaction, and interaction information that indicates a number of interactions and a timing of a most recent interaction. The contact data records are processed to generate a contact profile record for each contact including group metric values and a corresponding value for each group metric value based on an interaction history of groups the contact has interacted with. An interaction analytics databases stores a set of contact profile records and group profile records for groups that include metric values associated with the group and an interaction history. They are processed with at least thousands of the contact profile records to determine group-contact compatibility factors. A compatibility parameter is generated and communicated for each of at least thousands of contacts based on the group-contact compatibility parameters.

Methods, computer-readable media, systems, and/or apparatuses are provided for providing offer and insight generation functions. User input requesting an offer or insight may be received and an image of a photographic identification of a user may be requested. The image of the photographic identification may be captured and stored. A self-captured image of the user may be captured (e.g., via an image capture device of the computing device) and compared to an image of a user from the photographic identification. Responsive to determining that the images match, displaying an instruction to capture a vehicle identification number. The vehicle identification number may be captured. Data, including location data, may be extracted and an archive including the extracted data may be generated and the data may be transmitted to an entity computing system for processing. The entity computing system may evaluate the data and generate one or more insights and/or outputs.

An interactive system (1) for interacting with a user is disclosed. The interactive system (1) includes at least one interface (3), a measuring device (5), and a processing unit (7) comprising an interpretation module for receiving a physiological parameter obtained by the measuring device (5) and for defining, based on the physiological parameter, a datum representative of the physiological state of the user (U). The processing unit (7) comprises a data communication module for communicating data with a server (11) storing a library of applications, a data processing module for selecting an application on the basis of the datum representative of the physiological state, an information module for notifying the user (U) of the selected application, and detecting a validation action from the user (U) validating the notified application, and a download module for downloading the validated application.

Systems and methods comprising: analyzing an electronic resource to identify Entities in textual content (wherein each Entity comprises word(s)); performing machine learning operations to assign an entity type classification of a plurality of entity type classifications to at least one of the Entities; performing machine learning operations to assign each said Entity to one or more segments of the textual content that respectively comprise facts about people; performing machine learning operations to recognize relationships of the Entities to each person or business entity identified in the textual content and assign a relationship classification of a plurality of relationship classifications to at least one of the Entities associated with one of the recognized relationships; converting the electronic resource into relationship vectors based on outputs of the first, second and third classifiers; and controlling operations of a software application using the relationship vector.

Systems and techniques that facilitate keyword-object taxonomy generation and utilization are provided. In various embodiments, a system can comprise a receiver component that can access an input object class. In various aspects, the system can comprise a taxonomy component that can output one or more keyword combinations that are non-redundant and relevant to the input object class, based on querying a keyword-object taxonomy. In various instances, the receiver component can access (and/or be provided with an electronic link to) a set of recorded keyword combinations and a set of recorded object classes respectively corresponding to the set of keyword combinations. In various cases, the taxonomy component can generate the keyword-object taxonomy based on the set of recorded keyword combinations and the set of recorded object classes.

Systems and methods are described for tailoring shareable content object reference model (SCORM)-compliant content to one or more users. A learning management system (LMS), configured to be SCORM-compliant, initiates shareable content object (SCO) to provide content to users. The LMS implements an instance of application programming interface (API) comprising a plurality of functions to be called by SCO during runtime to access data model elements accessible via LMS. The LMS is configured to support one or more data model elements undefined by SCORM. Further, LMS receives a call to a function of the plurality of functions of the API from SCO to access information about users. The call references a name of a data model element undefined by SCORM. The data model element identifies information about users. The LMS provides information about the users to SCO and the SCO tailors the content to the users based on the information.

Systems and methods for multi-source reference class identification, base rate calculation, and prediction are disclosed. The systems and method can guide on, then elicit, information about reference class identification on a case-by-case basis, connects to a database in order to calculate historical base rates according to user reference class selections, and collect additional quantitative and qualitative information from users. The systems and methods can then generate predictive estimates based on the combination of the inputs by one or more users.

The present application describes a system and method for searching for content items in an application executing on a computing device. In order to increase the efficiency of the search, the present disclosure provides a refiner that is used to filter or otherwise refine search results. The refiner is user-specific and/or tenant/entity-specific. The refiner may be based on long-term aggregated data and/or contextual information associated with the user.