Abstract: Systems and methods are provided for providing a navigation interface to access or otherwise use electronic content items. In one embodiment, an augmentation application identifies at least one entity referenced in a document. The entity can be referenced in at least two portions of the document by at least two different words or phrases. The augmentation application associates the at least one entity with at least one multimedia asset. The augmentation application generates a layout including at least some content of the document referencing the at least one entity and the at least one multimedia asset associated with the at least one entity. The augmentation application renders the layout for display.

Abstract: Systems and methods are provided for providing a navigation interface to access or otherwise use electronic content items. In one embodiment, an augmentation application identifies at least one entity referenced in a document. The entity can be referenced in at least two portions of the document by at least two different words or phrases. The augmentation application associates the at least one entity with at least one multimedia asset. The augmentation application generates a layout including at least some content of the document referencing the at least one entity and the at least one multimedia asset associated with the at least one entity. The augmentation application renders the layout for display.

Abstract: Systems and methods of rendering webpage interaction statistics data over graphical user interfaces is provided herein. A computing device can transmit a request for an interaction statistics identifying an information resource. The computing device can receive the interaction data set for the identified information resource. The computing device can calculate a similarity measure among the client devices based on the interaction data set using a clustering algorithm. The computing device can identity a subset of client devices based on the similarity measure. The computing device can calculate the interaction sequence metrics for the client devices for each selected content element. The computing device can select the content elements based on the calculated interaction sequence metrics. The computing device can generate a graph element including nodes representing each selected content element and paths representing the interaction sequence metrics. The computing device can display the graph element.

Abstract: Systems and methods of rendering webpage interaction statistics data over graphical user interfaces is provided herein. A computing device can transmit a request for an interaction statistics identifying an information resource. The computing device can receive the interaction dataset for the identified information resource. The computing device can calculate a similarity measure among the client devices based on the interaction dataset using a clustering algorithm. The computing device can identify a subset of client devices based on the similarity measure. The computing device can calculate the interaction sequence metrics for the client devices for each selected content element. The computing device can select the content elements based on the calculated interaction sequence metrics. The computing device can generate a graph element including nodes representing each selected content element and paths representing the interaction sequence metrics. The computing device can display the graph element.

Abstract: Systems and methods of rendering webpage interaction statistics data over graphical user interfaces is provided herein. A computing device can transmit a request for an interaction statistics identifying an information resource. The computing device can receive the information resource including content element and numbers and time durations of interactions for each content element. The computing device can calculate interaction statistics for interacting with one content element prior to interacting with another content element based on the numbers and the time durations of interactions. The computing device can select content elements based on the calculated interaction statistics. The computing device can generate a graph element including nodes for each content element and directed paths among the nodes indicating the interaction statistics. The computing device can insert the graph element into the information resource. The computing device can display the graph element with the information resource.

Abstract: Systems and methods of dynamically rendering webpage interaction statistics data are described herein. A computing device can receive, at a first time, the information resource. The information resource can include a content element, a first interaction metric for the content element, and a style specifier. The style specifier can a first and second visual style corresponding to a first and second range of interaction metrics respectively. The computing device can determine that the first interaction metric is within the first range and set the content element to the first style based on the determination. The computing device can receive, at a second time, a second interaction metric for the content element. The computing device can determine that the second interaction metric is within the second range and set the content element to the second style based on the determination.

Abstract: Systems and methods of rendering webpage interaction statistics data over graphical user interfaces is provided herein. A computing device can transmit a request for an interaction statistics identifying an information resource. The computing device can receive the interaction dataset for the identified information resource. The computing device can calculate a similarity measure among the client devices based on the interaction dataset using a clustering algorithm. The computing device can identify a subset of client devices based on the similarity measure. The computing device can calculate the interaction sequence metrics for the client devices for each selected content element. The computing device can select the content elements based on the calculated interaction sequence metrics. The computing device can generate a graph element including nodes representing each selected content element and paths representing the interaction sequence metrics. The computing device can display the graph element.

Abstract: An apparatus, system and process for tracking and analyzing target person movements, captured while the target person is performing ordinary tasks outside of a medical context, for medical diagnosis and treatment review are described. The method may include constructing a model of a target person from three-dimensional (3D) image data of the target person performing an activity over a period of time. The method may also include tracking movement of the model of the target person in the 3D image data over the period of time, and detecting one or more motion features in the movement of the model of the target person that are relevant to diagnosis, treatment, care, or a combination thereof, of a potential chronic neurodegenerative or musculoskeletal medical condition. The method may also include computing a risk score associated with likelihood of the target person having the medical condition based on the detected motion features.

Abstract: Systems and methods of dynamically varying the intensity of providing content items in a remarketing campaign based on tracking client device interactions are provided. The system can assign an account identifier to a first segment for a pre-conversion model, responsive to receiving a first interaction associated with a content provider from a client device. The system can assign the account identifier to a second segment for the pre-conversion model, responsive to receiving a second interaction. The system can assign the account identifier to a third segment, responsive to receiving a third interaction. The third interaction can include a conversion event. The system can generate a post-conversion model based on the third segment and the pre-conversion model. The system can determine an intent index for the account identifier based on the post-conversion model. The system can store the account identifier into an interest cluster based on the intent index.

Abstract: In techniques for trending topics tracking, input text data is received as communications from a user or between users, where the communications are from one user to other users, or between two or more of the users. A topics tracking application is implemented to determine topics from the communications that are from or between the users, and track how the topics are trending over a time duration. The topics can include expressed sentiments and/or expressed emotions. An input selection of at least one of the topics can be received, and the topics tracking application generates a visual dashboard that displays a trending representation of the at least one topic that is trending over the time duration. The visual dashboard can also display data sources of the communications between the two or more users and/or an overview of one or more of the topics determined from a selected data source.

Abstract: In techniques for contextual sentiment text analysis, a sentiment analysis application is implemented to receive sentences as text data, and each of the sentences can include one or more sentiments about a subject of the sentence. The text data can be received as part-of-speech information that includes noun expressions, verb expressions, and tagged parts-of-speech of the sentences. The sentiment analysis application is implemented to analyze the text data to identify the sentiment about the subject of a sentence, and determine a context of the sentiment as the sentiment pertains to a topic category of the subject in the sentence, where the topic category of the subject is determined based on text categorization of the text data. The sentiment analysis application can also determine whether the sentiment is positive about the subject or negative about the subject based on the context of the sentiment within the topic category of the subject.

Abstract: In techniques for causal modeling and attribution, a causal modeling application implements a dynamical causal modeling framework. Input data is received as a representation of communications between users, such as social media interactions between social media users, and causal relationships between the users can be determined based in part on the input data that represents the communications. Influence variables, such as exogenous variables and/or endogenous variables, can also be determined that influence the causal relationships between the users. A causal relationships model is generated based on the influence variables and the causal relationships between the users, where the causal relationships model is representative of causality, influence, and attribution between the users.

Abstract: In techniques for contextualized sentiment text analysis vocabulary generation, a contextual analysis application is implemented to receive input data derived from rated product or service reviews. Each of the domain-specific reviews across multiple categories include a rating that is associated with expressed sentiments about a subject within a rated review. The contextual analysis application determines categories of the subjects of the rated reviews, and then generates a sentiment score for a term that is an expressed sentiment in a rated review. The sentiment score is generated based in part on a context of the term as it pertains to the category and rating of the rated review. The contextual analysis application is implemented to then determine a polarity of a term-category pair based on the sentiment score, and generate a contextualized sentiment vocabulary for all of the term-category pairs of the expressed sentiments about the subjects of the rated reviews.

Abstract: This document describes techniques for contextualization and enhancement of textual content. In one or more implementations, textual content is analyzed to determine whether the textual content is appropriate for an intended context. The intended context corresponds to an intended mood, emotion, tone, or sentiment of the textual content. If it is determined that the textual content does not conform to the intended context, suggestions are generated to modify the textual content to conform to the intended context.

Abstract: Systems and methods are provided for providing a navigation interface to access or otherwise use electronic content items. In one embodiment, an augmentation application identifies at least one entity referenced in a document. The entity can be referenced in at least two portions of the document by at least two different words or phrases. The augmentation application associates the at least one entity with at least one multimedia asset. The augmentation application generates a layout including at least some content of the document referencing the at least one entity and the at least one multimedia asset associated with the at least one entity. The augmentation application renders the layout for display.