Wei Zhuang

20130041750, Feb 14, 2013

Aug 12, 2011

13/209256

Jun YE - Palo Alto CA, US
Yu Cao - Saratoga CA, US
Luoqi Chen - Saratoga CA, US
Ya Luo - Milpitas CA, US
Wei Zhuang - Palo Alto CA, US
Hanying Feng - Fremont CA, US

Founton Technologies, Ltd. - Mountain View CA

G06Q 30/00

705 1452, 705 1466

The various embodiments described in the present disclosure, in at least one aspect, relate to computer-implemented methods of online advertisement. In one embodiment, a method includes determining an attention score for each of a plurality of ad creatives corresponding to a common ad content based on at least a correlation between each ad creative and a user's subconscious interest. The method further includes selecting an ad creative among the plurality of ad creatives based at least in part on the attention scores, and presenting the ad content with the selected ad creative as an ad impression to the user.

20140012671, Jan 9, 2014

Jul 6, 2012

13/543705

Jun Ye - Palo Alto CA, US
Yu Cao - Saratoga CA, US
Luoqi Chen - Saratoga CA, US
Ya Luo - Milpitas CA, US
Wei Zhuang - Palo Alto CA, US
Hanying Feng - Fremont CA, US
Hong Chen - San Jose CA, US

G06Q 30/02

705 1454, 705 1449, 705 1457

A method of providing targeted online advertisement includes receiving a request for an ad impression to be provided to a user in a network environment. The request includes a first content and a second content. The method also includes, using a processor, determining a context of the first content and a context of the second content, determining a correlation between the context of the first content and the context of the second content, and identifying a plurality of ads as candidates for consideration. The method further includes, using the processor, ranking the plurality of identified ads, selecting an ad among the plurality of identified ads based at least in part on a result of the ranking, and providing the selected ad as the ad impression to be displayed to the user in response to receiving the request.

20140012672, Jan 9, 2014

Jul 6, 2012

13/543708

Jun Ye - Palo Alto CA, US
Yu Cao - Saratoga CA, US
Luoqi Chen - Saratoga CA, US
Ya Luo - Milpitas CA, US
Wei Zhuang - Palo Alto CA, US
Hanying Feng - Fremont CA, US
Hong Chen - San Jose CA, US

G06Q 30/02

705 1454, 705 1449

A method of providing targeted online advertisement includes receiving a request for an ad impression. The request includes a first content and a second content. The method also includes determining information related to (i) a context of the first content, (ii) a context of the second content, and (iii) a correlation between the context of the first content and the context of the second content, and providing the determined information to a bidding service, thereby enabling one or more advertisers to place one or more bids on the ad impression based on the provided information. Each of the one or more bids includes a bid price. The method further includes receiving the one or more bids for the ad impression, selecting one of the one or more received bids based at least in part on the bid prices, and providing an ad impression associated with the selected bid.

20190325085, Oct 24, 2019

Apr 20, 2018

15/959005

- Redmond WA, US
Paul T. Ogilvie - Palo Alto CA, US
Bee-Chung Chen - San Jose CA, US
Shaunak Chatterjee - Sunnyvale CA, US
Priyanka Gariba - San Mateo CA, US
Ke Wu - Sunnyvale CA, US
Grace W. Tang - Los Altos CA, US
Yangchun Luo - Sunnyvale CA, US
Boyi Chen - Santa Clara CA, US
Amit Yadav - Milpitas CA, US
Ruoyang Wang - Palo Alto CA, US
Divya Gadde - Sunnyvale CA, US
Wenxuan Gao - Santa Clara CA, US
Amit Chandak - Bangalore, IN
Varnit Agnihotri - Karnataka, IN
Wei Zhuang - Palo Alto CA, US
Joel D. Young - Milpitas CA, US
Weidong Zhang - San Jose CA, US

Microsoft Technology Licensing, LLC - Redmond WA

G06F 17/30
G06F 9/445
G06K 9/62
G06F 15/18

The disclosed embodiments provide a system for processing data. During operation, the system obtains a feature configuration for a feature. Next, the system obtains, from the feature configuration, an anchor containing metadata for accessing the feature in an environment. The system then uses one or more attributes of the anchor to retrieve one or more feature values of the feature from the environment. Finally, the system provides the one or more feature values for use with one or more machine-learning models.

20190325262, Oct 24, 2019

Apr 20, 2018

15/958990

- Redmond WA, US
Paul T. Ogilvie - Palo Alto CA, US
Bee-Chung Chen - San Jose CA, US
Ke Wu - Sunnyvale CA, US
Grace W. Tang - Los Altos CA, US
Priyanka Gariba - San Mateo CA, US
Yangchun Luo - Sunnyvale CA, US
Boyi Chen - Santa Clara CA, US
Jian Qiao - San Mateo CA, US
Benjamin Hoan Le - San Jose CA, US
Joel D. Young - Milpitas CA, US
Wei Zhuang - Palo Alto CA, US

Microsoft Technology Licensing, LLC - Redmond WA

G06K 9/62
G06Q 10/06
G06F 15/18

The disclosed embodiments provide a system for processing data. During operation, the system obtains feature configurations for a set of features. Next, the system obtains, from the feature configurations, an anchor containing metadata for accessing a first feature in an environment and a feature derivation for generating a second feature from the first feature. The system then uses the anchor to retrieve feature values of the first feature from the environment and uses the feature derivation to generate additional feature values of the second feature from the feature values of the first feature. Finally, the system provides the additional feature values for use with one or more machine learning models.

20160284368, Sep 29, 2016

Mar 25, 2016

15/080726

- Mountain View CA, US
Wei Zhuang - San Francisco CA, US
Konstantin Perevoztchikov - Saratoga CA, US

Guzik Technical Enterprises - Mountain View CA

G11B 5/455
G11B 5/48

An apparatus for securing an HGA to a tester includes a housing with a cylindrical cavity disposed about an axis, and having, at its top end, a mounting surface with a central aperture, for receiving an HGA base plate with a boss hole of the HGA overlying the central aperture. Axially elongated clamp fingers, radially dispersed about a spreader pin, move along the axis between (i) a loading position with upper ends extending through and relatively far beyond the central aperture, and (ii) a clamping position with the upper ends disposed at or near the mounting surface. With an HGA on the mounting surface, and the clamp fingers at their loading position, the clamp fingers are driven downward, while simultaneously, the clamp fingers are driven outward by the spreader pin, and the clamp fingers engage boss hole edges, securing the HGA to the tester.