Microsoft Technology Licensing, LLC

Benjamin John McCann

Erik Eugene Buchanan

John Robert Jersin

Nadeem Anjum

Jerry Lin

Skylar Payne

Gio Borje

David DiCato

Apoorv Khandelwal

Alexis Blevins Baird

Jeffrey Michael Wright

Travis Nelson Hummel

Kevin Keck

Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.

Predicting feature values in a matrix

Negative sampling

Techniques for dynamically altering weights to re-weight attributes of an ordering model based on feedback in a streaming environment are described. In an embodiment, a system accesses, based on a candidate stream definition comprising a role including a title, one or more stream-related information sources, and extracts attributes from the sources. Additionally, the system inputs the attributes to a combined ordering model that is trained by a machine learning algorithm to output ordering scores for member profiles of an online system (e.g., hosting a social networking service). The combined ordering model includes weights assigned to the attributes. Moreover, the system orders, based on the ordering scores, the profiles. Furthermore, the system presents, on a display, of top-ordered profiles. Then, the system accesses feedback regarding the top-ordered profiles and dynamically trains the weights assigned to each of the attributes to alter the weights assigned to the attributes based on the feedback.

Using feedback to create and modify candidate streams

Systems and methods for query term weighting are disclosed. A server receives a search query for employment candidates, the search query comprising a set of parameters, each parameter having a weight. The server generates, from a data repository storing records associated with professionals, a first set of search results based on the set of parameters and the weights of the parameters in the set. The server transmits the first set of search results. The server receives a response to search result(s) from the first set of search results, the search result(s) being associated with a set of factors, the response indicating a level of interest in the search result(s). The server adjusts the parameters in the set of parameters or adjusts the weights of the parameters based on the response to the search result(s). The server provides an output based on the adjusted parameters or the adjusted weights.

Query term weighting

Ranking job candidate search results

Systems and methods for applicant tracking system (ATS) integration with a deduplicator are disclosed. A recruiting company computer system accesses a first entity record external to an ATS. The recruiting company computer system determines that the first entity record corresponds to a second entity record within the ATS based on at least first information of the first entity record and second information of the second entity record. The first information is different from the second information. The recruiting company computer system imports, into the second entity record within the ATS, information from the first entity record external to the ATS in response to the first entity record corresponding to the second entity record. The recruiting company computer system provides, in response a request to access information about an entity associated with the second entity record, the information from the first entity record.

Applicant tracking system integration

Systems and methods for messaging service integration with a deduplicator are disclosed. In example embodiments, a server determines that a first user from among a set of users is composing a message to an entity using a first contact information of the entity. The server determines that a second user from among the set of users previously contacted the entity using a second contact information of the entity, the second contact information being different from the first contact information. The server provides for display, within a graphical user interface, an indication that the second user has previously contacted the entity.

Messaging service integration with deduplicator

Machine learning to predict numerical outcomes in a matrix-defined problem space

Systems and methods for identifying user information from a set of pages are disclosed. In example embodiments, a server determines that a first set of pages is associated with a specific user based on addresses of the first set of pages having a common portion of a uniform resource locator (URL). The server determines that at least a threshold number of pages from the first set of pages include common information, the common information comprising contact information or social networking information. The server associates the contact information or the social networking information with a user profile of the specific user. The server provides, as a digital transmission, the contact information or the social networking information.

Identifying user information from a set of pages

Systems and methods for deduplication and disambiguation are disclosed. In example embodiments, a server accesses stored information about a first entity and stored information about a second entity. The server determines, based on the accessed stored information about the first entity and the accessed stored information about the second entity, a set of information items known about both the first entity and the second entity. The server computes, based on the set of information items, a probability that the first entity corresponds to the second entity by computing one or more expressiveness scores corresponding to a value of a first information item and a value of a second information item from the set of information items. The server provides, as a digital transmission, an output representing the computed probability.

Growing community of inventors

Mountain View, CA, United States of America

Benjamin John McCann