Abstract: Systems and methods for generating and displaying a non-time bound content channel in a time-bound grid is provided. The system comprises receiving content data representing non-time bound content to be displayed in the time bound grid. The system generates the time bound grid, by creating, based on the content data, a non-time bound content channel. The non-time bound content channel displays one or more content objects representing the non-time bound content in the time bound grid. The system incorporates the non-time bound content channel with a plurality of time bound channels in the time bound grid. The system then causes display of the generated time bound grid on a viewing device of a user.

Abstract: Systems and methods for generating and displaying groupings of content recommendations using personas are provided. The system determines content for each of the plurality of personas. The determined content for each of the plurality of personas comprises content that shares a common genre or theme for each persona. The system populates each of the plurality of personas using the determined content for each of the plurality of personas. The system then causes display of at least some of the plurality of personas on a viewing device of a user. The at least some of the plurality of personas is selected for the user based on device data corresponding to the user, whereby the device data indicates user preferences and interactions with previous content.

Abstract: A web browser that records and displays browsing history. For each web page, a thumbnail image of the web page and a group associated with the web page are recorded. A group is displayed along a first axis, the thumbnail image of each page associated with that group displayable along a second orthogonal axis.

Abstract: A method and system for using social tagging to identify a search engine user's intent are described. A search engine selects a set of pages that are relevant to a query. The engine determines neighbors of these pages and groups the neighbors into topical clusters. For each cluster, the engine determines tags that a community of users has frequently associated with pages in that cluster. For each cluster, the engine matches that cluster's dominant tags with phrases in various intent lists. By matching a particular cluster's tags to various lists, an intent corresponding to that particular cluster is determined. For each cluster's intent, the search engine may present, with query results, types of content that correspond especially to that intent (e.g., a map for a location intent, possibly along with driving directions). Additionally or alternatively, for each such intent, the search engine may format the query results in a manner that suits the intent.