Abstract: Systems and methods are described for obtaining evidence of online commercial use of a trademark. In embodiments, a query generator receives information about the trademark and generates search queries based thereon. A search results collector submits the search queries to at least one Internet search engine to obtain a set of search results pertaining to a plurality of web pages. A web page content analyzer obtains and analyzes page content of each web page in the plurality of web pages to generate a brand score indicative of a degree of confidence that the web page includes the trademark and a commercial score indicative of a degree of confidence that the web page relates to commerce. A user interface (UI) manager presents information about each web page in the plurality of web pages via a UI, including associated brand score and commercial score representations, in a ranked order based on relevance.

Abstract: Systems and methods for generating strings based on a seed string are disclosed. Machine learning models are trained using domain-specific training data. Random walk models are derived from the trained machine learning models. A seed string is input into each of the random walk models, and each of the random walk models iteratively generate one or more next characters for the seed string to generate at least one term from each of the random walk models. A predicted class for the at least one term generated by each of the random walk models can be determined, and a ranked order for the at least one term generated by each of the random walk models with the predicted classes can be output to a graphical user interface.

Abstract: The system and methods described herein determine whether to override commands to modify content presentation in a multi-user content consumption environment. A media guidance application detects a first and second user consuming content. Upon receiving a command from the first user to modify the presentation of the content, the media guidance application retrieves a user profile of the second user and compares attributes in the user profile to metadata for the segment of the content. Based on the comparison, the media guidance application determines whether to override the command, for example based on a predicted interest level or importance level determined by the comparison. In response to determining to override the command, the media guidance application refrains from executing the command by canceling or delaying the command and generates a notification message to the user with a reason why the command was overridden.

Abstract: The system and methods described herein determine whether to override commands to modify content presentation in a multi-user content consumption environment. A media guidance application detects a first and second user consuming content. Upon receiving a command from the first user to modify the presentation of the content, the media guidance application retrieves a user profile of the second user and compares attributes in the user profile to metadata for the segment of the content. Based on the comparison, the media guidance application determines whether to override the command, for example based on a predicted interest level or importance level determined by the comparison. In response to determining to override the command, the media guidance application refrains from executing the command by canceling or delaying the command and generates a notification message to the user with a reason why the command was overridden.

Abstract: The system and methods described herein determine whether to override commands to modify content presentation in a multi-user content consumption environment. A media guidance application detects a first and second user consuming content. Upon receiving a command from the first user to modify the presentation of the content, the media guidance application retrieves a user profile of the second user and compares attributes in the user profile to metadata for the segment of the content. Based on the comparison, the media guidance application determines whether to override the command, for example based on a predicted interest level or importance level determined by the comparison. In response to determining to override the command, the media guidance application refrains from executing the command by canceling or delaying the command and generates a notification message to the user with a reason why the command was overridden.

Abstract: The system and methods described herein determine whether to override commands to modify content presentation in a multi-user content consumption environment. A media guidance application detects a first and second user consuming content. Upon receiving a command from the first user to modify the presentation of the content, the media guidance application retrieves a user profile of the second user and compares attributes in the user profile to metadata for the segment of the content. Based on the comparison, the media guidance application determines whether to override the command, for example based on a predicted interest level or importance level determined by the comparison. In response to determining to override the command, the media guidance application refrains from executing the command by canceling or delaying the command and generates a notification message to the user with a reason why the command was overridden.

Abstract: The system and methods described herein determine whether to override commands to modify content presentation in a multi-user content consumption environment. A media guidance application detects a first and second user consuming content. Upon receiving a command from the first user to modify the presentation of the content, the media guidance application retrieves a user profile of the second user and compares attributes in the user profile to metadata for the segment of the content. Based on the comparison, the media guidance application determines whether to override the command, for example based on a predicted interest level or importance level determined by the comparison. In response to determining to override the command, the media guidance application refrains from executing the command by canceling or delaying the command and generates a notification message to the user with a reason why the command was overridden.

Abstract: Systems and methods for generating strings based on a seed string are disclosed. Machine learning models are trained using domain-specific training data. Random walk models are derived from the trained machine learning models. A seed string is input into each of the random walk models, and each of the random walk models iteratively generate one or more next characters for the seed string to generate at least one term from each of the random walk models. A predicted class for the at least one term generated by each of the random walk models can be determined, and a ranked order for the at least one term generated by each of the random walk models with the predicted classes can be output to a graphical user interface.