Abstract:
A system determines whether a user is a member of a segment, and this segment membership determination can be used to determine what content is provided to the user. Each segment has a corresponding set of criteria that includes multiple different elements describing users in the segment. A confidence value that the user is included in the segment is generated based on user data, and this confidence value can be used in different manners, such as to determine what content to provide to the user or to determine a financial value of providing content to the user. The confidence value is based on a fuzzy matching technique that generates element scores indicating how well the elements are satisfied by the user. The confidence value can also be based on weighted element scores, and estimates generated for elements for which user data is unknown.
Abstract:
A system and method is disclosed for measuring contributor weight or influence in social media. Content posted by a user on one or more social media platforms is identified. The identifying the content posted by the user includes searching the one or more social media platforms for content posted by the user with identifying information. Downstream content associated with the content posted by the user is identified. Metrics measuring a contributor weight of the user based on the downstream content are calculated.
Abstract:
Digital experience content personalization and recommendation techniques within an AR or VR environment are described. In one example, a user profile is received that models how user interaction occurs with respect to virtual objects within a virtual or augmented reality environment. Digital experience content is obtained that defines a virtual or augmented reality environment. A virtual object is selected for inclusion as part of the digital experience content based at least in part on the user profile. Digital experience content is generated to support user interaction with the selected virtual object as part of the virtual or augmented reality environment.
Abstract:
Object amalgamation based on categorization and protocol granularization is described. For certain example embodiments, each object belongs to a category of objects that is associated with a particular protocol. A protocol may include a wireless communication protocol and/or a characteristic description protocol. The object is capable of communicating a characteristic in accordance with the corresponding particular protocol. The characteristic may be an intrinsic attribute or a sensed value. A coordinator object groups other objects so as to amalgamate them into subnetworks in which the member objects are empowered to communicate with each other. If two objects correspond to different protocols, another object may translate a wireless communication from one protocol to another protocol. A coordinator object amalgamates characteristics received from other objects into a combined characteristic entity that may be used to jointly analyze the characteristics locally and produce a report for an end user based on the amalgamated characteristics.
Abstract:
In embodiments of customized and automated dynamic infographics, an infographic template is received at a cloud-based service from a computing device, where a user at the computing device creates the infographic template in a graphics application to display data obtained from data sources. The cloud-based service assigns an identifier to associate the infographic template and the data sources of the data, and posts the infographic template making it available for cloud-based access by other computing devices that request to display the posted infographic template. The cloud-based service can receive a request from one of the computing devices to update the displayed data, and then query the data sources for current data, where the query is based on the identifier that is associated with the posted infographic template. The cloud-based service can then transform the current data to generate updated data, and update the posted infographic template with the updated data.
Abstract:
Methods and techniques are disclosed for matching user profiles on distinct social media platforms. A first profile is retrieved from a first social media platform. The first profile is identified by one or more search criteria. Responsive to identifying an instance of the one or more search criteria on a second social media platform, a first probability is determined. A second profile is identified by the one or more search criteria on the second social media platform. The first probability predicts whether the second profile is associated with an entity associated with the first profile. The determining the first probability further comprises comparing an attribute of the first profile to an attribute of the second profile. Responsive to determining that the first probability exceeds a threshold, a match indicating that the second profile is associated with an entity associated with the first profile is recorded.
Abstract:
In an online environment, a baseline attitude of an author of online content is determined. Based on the baseline attitude and a raw sentiment score for an instance of online content, an adjusted sentiment score for the online content instance is generated. A variance from the baseline attitude may be detected, based on the online content of the author. In response to the variance, a current mood of the author is determined and, using the current mood and the raw sentiment score, another adjusted sentiment score for the online content instance is generated. The baseline attitude of the author may be determined using one or more of an analysis of the online content instance, a demographic profile of the author, and a subject matter area of the online content instance. The detection of the variance from the baseline attitude may incorporate a frequency of instances of online content.
Abstract:
User interactions with a physical object are monitored via one or more sensors integrated with the physical object. The sensors collect usage data for the physical object, based on the user interactions. Analyzed usage data is generated from the usage data collected via the sensors in the physical object as well as from usage data for the physical object that is collected by sensors integrated with one or more additional physical objects that are connected to the physical object by a network. Training feedback, based on the analyzed usage data, is then presented to the user in real-time.
Abstract:
The present disclosure is directed toward systems and methods for identifying contributing factors associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify sub-factors associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors that caused the particular anomaly and how those factors correlate with each other.
Abstract:
Techniques are disclosed for using natural language processing techniques to define, manipulate, and interact with consumer segmentations. In such embodiments a content consumption analytics engine can be configured to receive and process a natural language segmentation query. The query may comprise, for example, a command that defines a new segmentation, a command that manipulates existing segmentations, or a command that solicits information relating to existing consumer segmentations. The query is parsed to identify individual grammatical tokens which are then correlated with specific segment token types through the use of a token repository. A custom thesaurus is used to identify synonymous terms for grammatical tokens which may not exist in the token repository. User feedback enables the custom thesaurus to learn additional synonyms for future use. Once the grammatical tokens are mapped onto the identified segment token types, a formal segment definition can be constructed based on a segment definition structure.