Recommendation system that identifies a valuable user action by mining data supplied by a plurality of users to find a correlation that suggests one or more actions for notification

US7657493B2 · kind B2 · utility

Assignee

• Microsoft Corporation · US

Inventors

• Henricus Johannes Maria Meijer · Mercer Island, US
• William H. Gates, III · Bellevue, US
• Raymond E. Ozzie · Seattle, US
• Gary W. Flake · Bellevue, US
• Thomas F. Bergstraesser · Kirkland, US
• Arnold Blinn · Clyde Hill, US
• Christopher W. Brumme · Mercer Island, US
• Lili Cheng · Bellevue, US
• Michael Connolly · Royal Oak, US
• Nishant V. Dani · Issaquah, US
• Dane Glasgow · Los Gatos, US
• Daniel S. Glasser · Mercer Island, US
• Alexander G. Gounares · Kirkland, US
• James R. Larus · Mercer Island, US
• Matthew Bret MacLaurin · Woodinville, US
• Debi P. Mishra · Bellevue, US
• Amit Mital · Bellevue, US
• Ira L. Snyder, Jr. · Bellevue, US
• Chandramohan A. Thekkath · Palo Alto, US
• David R. Treadwell, III · Seattle, US
• Melora Zaner-Godsey · Redmond, US

Key dates

• Filing date: Dec 20, 2006
• Grant date: Feb 2, 2010
• Expiry date: Jun 20, 2028

Classification

• Technology area (CPC G): Physics
• CPC primary: G06F2216/03
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Personal data mining mechanisms and methods are employed to identify relevant information that otherwise would likely remain undiscovered. Users supply personal data that can be analyzed in conjunction with data associated with a plurality of other users to provide useful information that can improve business operations and/or quality of life. Personal data can be mined alone or in conjunction with third party data to identify correlations amongst the data and associated users. Applications or services can interact with such data and present it to users in a myriad of manners, for instance as notifications of opportunities.