Abstract: The present disclosure provides computer systems and methods for searching for multi-dimensional career content over a network. The method comprises: collecting content related to educational attributes about a plurality of job candidates from one or more resources over the network; processing the content to identify a plurality of tags in the content and generating a contextual relationship among the plurality of tags; organizing the content in a memory location based on the plurality of tags and the contextual relationship that permits searching of the content along multiple dimensions; and providing, on a graphical user interface, a first panel comprising a plurality of filtering options corresponding to the multiple dimensions and a second panel displaying indicators for at least a subset of the plurality of job candidates, wherein the indicators are generated based on the contextual relationship and the plurality of tags.

Abstract: Techniques for optimized web domains classification based on progressive crawling with clustering are disclosed. In some embodiments, optimized web domains classification based on progressive crawling with clustering includes crawling a domain (e.g., a web site domain) to collect data for a subset of pages (e.g., web pages) of a corpus of content associated with the domain; classifying each of the crawled pages into one or more category clusters, in which the category clusters represent a content categorization of the corpus of content associated with the domain (e.g., a URL content categorization for the domain, host of that domain, and/or directory of that domain); and determining which of the one or more category clusters to publish for the domain.

Abstract: The present disclosure provides computer systems and user interfaces for learning and/or talent discovery. A computer system can include a user interface that includes a search field and a facet field for refining a search directed to a query inputted in the search field. The query can be directed to learning or talent discovery. The facet field can display one or more descriptors that are indicative of a characteristic of one or more users or courses that are returned from a search directed to the query. The facet field can display a number of users or courses associated with each of the one or more descriptors.

Abstract: Techniques for optimized web domains classification based on progressive crawling with clustering are disclosed. In some embodiments, optimized web domains classification based on progressive crawling with clustering includes crawling a domain (e.g., a web site domain) to collect data for a subset of pages (e.g., web pages) of a corpus of content associated with the domain; classifying each of the crawled pages into one or more category clusters, in which the category clusters represent a content categorization of the corpus of content associated with the domain (e.g., a URL content categorization for the domain, host of that domain, and/or directory of that domain); and determining which of the one or more category clusters to publish for the domain.

Abstract: Techniques for optimized web domains classification based on progressive crawling with clustering are disclosed. In some embodiments, optimized web domains classification based on progressive crawling with clustering includes crawling a domain (e.g., a web site domain) to collect data for a subset of pages (e.g., web pages) of a corpus of content associated with the domain; classifying each of the crawled pages into one or more category clusters, in which the category clusters represent a content categorization of the corpus of content associated with the domain (e.g., a URL content categorization for the domain, host of that domain, and/or directory of that domain); and determining which of the one or more category clusters to publish for the domain.

Abstract: Techniques are disclosed for solving deliverability issues of HTTP long polling push messages in a multi-server environment. When a push server generates a push event to be sent to a client web browser, the push server affixes an identifier and a timestamp to the push event. The client web browser application retains all recent push event identifiers in a list, and the push server retains all recent push events in memory. When the client web browser application requests a subsequent push connection, the browser application sends the list of event identifiers to the push server. Using this list, the push server evaluates which of these identifiers corresponds to the earliest event, and from there generates a list of push events that have occurred after that earliest event. Then, the push server compares this generated list with the browser application's list of identifiers for missing events in the identifier list. The push server delivers all missing events to the client web browser application.

Abstract: Techniques are disclosed for generating a web-based user content feed given a set of sort and filter criteria. Upon receiving such criteria from a client web browser application, a feed server merges a first feed object and a second feed object having subsets of metadata deriving from a feed item table in the database. The feed server performs the sort, filter, and search operations on the sortable list and retrieves the full metadata from the database. The feed server returns the result to the client web browser application, which displays the content feed to a user.