Mark L Braverman, 761815 NW 27Th Ave, Portland, OR 97210

2010019, Aug 5, 2010

Jan 30, 2009

12/362492

Mohsen Bayati - Salem MA, US
Mark Braverman - Boston MA, US
Satyen Chandrakant Kale - Cambridge MA, US
Yury Makarychev - Cambridge MA, US

Microsoft Corporation - Redmond WA

G06Q 30/00
G06F 7/06
G06F 17/30

705 1452, 707E17014

Described is a paid search advertising technology in which ratings values are computed for advertisements (or other web content items) based upon head-to-head evaluations as to which advertisement or advertisements were selected (clicked) from among a set of advertisements that were shown together. Records of a query log contain data of advertisements that were shown together, and each advertisement of those shown together that was clicked. Pairs of advertisements are selected, with the rating value of an advertisement that was clicked increased, and the rating value of the non-clicked advertisement decreased. Only those pairs in which one advertisement was selected and another was not selected may be used as a pair. Elo ratings formulas may be employed for the increasing and decreasing computations. The rating values may be combined with other prediction results into a combined result used to select and/or rank advertisements for returning with a query response.

2012000, Jan 5, 2012

Jun 30, 2010

12/828055

Mark Braverman - Boston MA, US
Mohsen Bayati - Palo Alto CA, US
Eric Horvitz - Kirkland WA, US
Michael Gillam - Washington DC, US

MICROSOFT CORPORATION - Redmond WA

G06Q 50/00
G06F 15/18
G06N 5/02
G06Q 10/00

705 2, 706 12, 706 52, 706 47, 706 46

Technology is described for developing health care policies for use in a health care facility. In one example method, a health care policy can be applied in a health care software application and stored in a health care database. A correlated feature set can be correlated to the health care policy being developed. A selection of health care cases can be obtained from the health care database for testing the health care policy. A model can predict a defined effect of the health care policy based on the correlated feature set. A cost of implementing the health care policy on a defined percentage of patients can be predicted using the defined effect by the model and a specified predictor by applying statistical analysis. The system can guide the allocation of resources in a patient-specific manner. The policies can also be applied in conjunction with user models to guide alerting.

2009028, Nov 19, 2009

May 18, 2009

12/467991

Philipp Frank Hermann Udo Hertel - Victoria, CA
Alexander Wolfgang Karl Kurt Hertel - Victoria, CA
John David Trevor Graham - Victoria, CA
Mark Braverman - Boston MA, US

ZETAWIRE INC. - Toronto

G06F 3/048
G06Q 40/00

715738, 715769, 705 39

A configuration (a system and/or a method) are disclosed that includes a unified and integrated configuration that is composed of a payment system, an advertising system, and an identity management system as well as their associated methods such that the unified system has all of the benefits of the individual systems as well as several additional synergistic benefits. Also described are specific configurations (subsystems and/or methods) including the system's access point architecture, a user interface that acts as a visual wallet simulator, a security architecture, coupon handling as well as the system's structure and means for delivering them as targeted advertising, business card handling, membership card handling for the purposes of login management, receipt handling, and the editors and grammars provided for customizing the different types of objects in the system as well as the creation of new custom objects with custom behaviors. The configurations are operable on-line as well as through physical presence transactions, e.g., mobile transaction through a mobile phone or dedicated device at a physical site for a transaction.