Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of features associated with a customer, wherein the set of features includes profile data from an online professional network and one or more standardized features related to a role of the customer. Next, the system applies a set of whitelists and a set of blacklists to the features to identify a market segment for the customer. The system then uses the market segment to generate output for use in targeting the customer with an educational technology product.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of features associated with a customer, wherein the set of features includes profile data from an online professional network. Next, the system uses a statistical model and the features to predict a likelihood of acquiring the customer for an educational technology product. The system then uses the likelihood to generate output for use in targeting the customer with the educational technology product.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of features associated with a sales lead for an educational technology product, wherein the set of features includes profile data from an online professional network. Next, the system uses the set of features to generate a set of quality indicators for the sales lead. The system then aggregates the quality indicators into a lead score representing a quality of the sales lead. Finally, the system outputs the lead score for use in managing sales activity with the sales lead.

Abstract: System and methods for correlating members with clusters of online course content are disclosed. A server system accessing a plurality of course records associated with a plurality of courses from a database. The server system identifies, for each particular course in the plurality of courses, a list of members of the server system that have accessed content associated with the particular course. The server system applies a clustering algorithm to each course to create a third group of courses. The server system determines member demand for courses included in the third group of courses. In accordance with a determination that the member demand for courses in included in the third group of courses is equal to or greater than a member demand threshold, the server system transmits a request for additional course content to a content provider.

Abstract: In managing incoming bus traffic storage for store cell memory (SCM) in a sequential-write, random-read system, a priority encoder system can be used to find a next empty cell in the sequential-write step. Each cell in the SCM has a bit that indicates whether the cell is full or empty. The priority encoder encodes the next empty cell using these bits and the current write pointer. The priority encoder can also find next group of empty cells by being coupled to AND operators that are coupled to each group of cells. Further, a cell locator selector selects a next empty cell location among priority encoders for cell groups of various sizes according to an opcode by appending ‘0’s to cell locations outputs from priority encoders that are smaller than the size of the SCM.

Abstract: In managing incoming bus traffic storage for store cell memory (SCM) in a sequential-write, random-read system, a priority encoder system can be used to find a next empty cell in the sequential-write step. Each cell in the SCM has a bit that indicates whether the cell is full or empty. The priority encoder encodes the next empty cell using these bits and the current write pointer. The priority encoder can also find next group of empty cells by being coupled to AND operators that are coupled to each group of cells. Further, a cell locator selector selects a next empty cell location among priority encoders for cell groups of various sizes according to an opcode by appending ‘0’s to cell locations outputs from priority encoders that are smaller than the size of the SCM.

Abstract: In managing incoming bus traffic storage for store cell memory (SCM) in a sequential-write, random-read system, a priority encoder system can be used to find a next empty cell in the sequential-write step. Each cell in the SCM has a bit that indicates whether the cell is full or empty. The priority encoder encodes the next empty cell using these bits and the current write pointer. The priority encoder can also find next group of empty cells by being coupled to AND operators that are coupled to each group of cells. Further, a cell locator selector selects a next empty cell location among priority encoders for cell groups of various sizes according to an opcode by appending ‘0’s to cell locations outputs from priority encoders that are smaller than the size of the SCM.

Abstract: In managing incoming bus traffic storage for store cell memory (SCM) in a sequential-write, random-read system, a priority encoder system can be used to find a next empty cell in the sequential-write step. Each cell in the SCM has a bit that indicates whether the cell is full or empty. The priority encoder encodes the next empty cell using these bits and the current write pointer. The priority encoder can also find next group of empty cells by being coupled to AND operators that are coupled to each group of cells. Further, a cell locator selector selects a next empty cell location among priority encoders for cell groups of various sizes according to an opcode by appending ‘0’s to cell locations outputs from priority encoders that are smaller than the size of the SCM.