Microsoft Technology Licensing, LLC

Rajan Ramesh Chaudhari

Aaron Tyler Rucker

Tomer Cohen

Divyakumar Menghani

Tuhin Chakraborty

Henry Kwan

Sparsh Agarwal

Chong Bu Won

Pablo Crespo

The technical problem of predicting the level of activity driven by a web page representing a company in an on-line social network system is addressed by providing a company page assessment system. A company page assessment system is configured to use a machine learning model to determine features and respective thresholds that signal the likelihood of a web page representing a company (a company page) to drive member activity in the on-line social network system. The company page assessment system also provides the ability to assess quality of a company page. Different quality levels of a company page can be indicated by respective labels 'Complete Page,' 'Quality Page,' and &#x201c;Engaged Quality Page.&#x201d;

Capturing company page quality

Methods, systems, and computer programs are presented for managing company job listings in a social network by selecting which job posts are included in the company job slots. One method includes an operation for selecting a job post, from a company job pool, for inclusion in the job slots that are presented to members. Further, the method includes operations for presenting the selected job post to members, and for determining a view threshold number based on the day of a week that the job post was posted. The number of views within a period is determined, and when the number is greater than or equal to the view threshold number, the job post is kept in the job slot; otherwise, the job post is marked as a rotatable job post, where rotatable job posts are discarded from the job slots when other jobs are available in the job pool.

Job post selection based on predicted performance

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San Francisco, CA, United States of America

Rajan Ramesh Chaudhari