Michael H Chow

20100153884, Jun 17, 2010

Dec 12, 2008

12/333937

Michael Chow - San Mateo CA, US
Tim Rechin - San Carlos CA, US
Martin Price - Volpedo, IT
Tussanee Garcia Shelton - San Mateo CA, US
Joff Redfern - Palo Alto CA, US
Luke Wroblewski - San Jose CA, US

Yahoo! Inc. - Sunnyvale CA

G06F 3/048

715841

An enhanced toolbar is disclosed. The enhanced toolbar is not static but is rather updated dynamically. In one aspect, the enhanced toolbar has a bounded perimeter and comprises a plurality of icons visibly displayed on a display of a computing device. Each icon occupies a first space within the bounded perimeter of the toolbar. Upon a selection of a first icon in the plurality of icons by a user, the first space associated with the first icon expands horizontally along a longitudinal axis of the toolbar to display information in a second bounded space within the perimeter. The information is not visible absent the expansion.

20120252557, Oct 4, 2012

Apr 4, 2011

13/079148

Michael Chow - San Francisco CA, US
Justin Rouse - Dallas TX, US
Kevin Holme - Allen TX, US

A63F 9/24

463 25, 463 42, 463 43

An advertisement is associated with a particular user move in a gaming environment where playing of the user move by a user results in the advertisement being displayed at the user's gaming device. With multiple users, each play of a unique user move results in a corresponding uniquely targeted advertisement being displayed at the respective gaming device of each user. User moves and associated advertisements are bound to one another based on a frequency of use of the user move in game play and the desirability of the advertiser to associate the advertisement with the user move.

20120252559, Oct 4, 2012

Sep 26, 2011

13/244861

Michael Chow - San Francisco CA, US
Justin Rouse - Dallas TX, US
Kevin Holme - Allen TX, US

A63F 9/24

463 25

An advertisement is associated with a particular user move in a gaming environment where playing of the user move by a user results in the advertisement being displayed at the user's gaming device. With multiple users, each play of a unique user move results in a corresponding uniquely targeted advertisement being displayed at the respective gaming device of each user. User moves and associated advertisements are bound to one another based on a frequency of use of the user move in game play and the desirability of the advertiser to associate the advertisement with the user move.

20120252573, Oct 4, 2012

Sep 26, 2011

13/244739

Michael Chow - San Francisco CA, US
Justin Rouse - Dallas TX, US
Kevin Holme - Allen TX, US

A63F 13/00

463 30

An advertisement is associated with a particular user move in a gaming environment where playing of the user move by a user results in the advertisement being displayed at the user's gaming device. With multiple users, each play of a unique user move results in a corresponding uniquely targeted advertisement being displayed at the respective gaming device of each user. User moves and associated advertisements are bound to one another based on a frequency of use of the user move in game play and the desirability of the advertiser to associate the advertisement with the user move.

20120252574, Oct 4, 2012

Sep 26, 2011

13/244858

Michael Chow - San Francisco CA, US
Justin Rouse - Dallas TX, US
Kevin Holme - Allen TX, US

A63F 13/00

463 31

An advertisement is associated with a particular user move in a gaming environment where playing of the user move by a user results in the advertisement being displayed at the user's gaming device. With multiple users, each play of a unique user move results in a corresponding uniquely targeted advertisement being displayed at the respective gaming device of each user. User moves and associated advertisements are bound to one another based on a frequency of use of the user move in game play and the desirability of the advertiser to associate the advertisement with the user move.

20210299575, Sep 30, 2021

Mar 31, 2020

16/836133

- Tokyo, JP
Justice Adams - San Mateo CA, US
Mario Sarria, JR. - San Mateo CA, US
Jorge Arroyo Palacios - San Mateo CA, US
Nirmal Rajkumar - San Mateo CA, US
Michael Chow - San Mateo CA, US

A63F 13/79

A method is provided, including the following operations: monitoring gameplay activity in a plurality of game sessions, wherein the monitoring includes, for each game session, analyzing the gameplay activity in said game session to predict future gameplay activity in said game session; identifying one or more characteristics of a plurality of spectators interacting with a virtual character, wherein each of the spectators interacting with the virtual character accesses, over a network, a channel that is attributed to the virtual character; through the channel, providing access to the spectators to spectate a selected game session that is one of the plurality of game sessions, selected based on the predicted future gameplay activity and based on the characteristics of the plurality of spectators.

20210154585, May 27, 2021

Feb 3, 2021

17/166979

- San Francisco CA, US
Paul David Bettner - McKinney TX, US
David Bettner - McKinney TX, US
Paolo Malabuyo - San Mateo CA, US
Benjamin F. Gregorski - Mountain View CA, US
Michael Chow - San Francisco CA, US
Yie Lyn Choo - San Francisco CA, US

A63F 13/79
H04L 12/58
G06Q 50/00
G06Q 30/02
A63F 13/69
A63F 13/85
A63F 13/35
A63F 13/537
A63F 13/61

Systems and methods for processing recommendations of online games to friends of social network are described. A method for processing recommendations includes identifying a gaming session of a user on an online game provider network, accessing a use profile of the user for the online games of the online game provider network, and accessing a social graph of the user to identify friends of the user and respective friend profiles from the social network. The method further includes producing a recommendation of an online game. The recommendation includes an identification of a target friend of the user and is being provided by examination of the use profile of the user and friend profiles in the social graph. The method includes providing the recommendation to the user. The recommendation also includes an offer incentive to the user to share the recommendation with the target friend.

20210142624, May 13, 2021

Nov 8, 2019

16/678630

- Tokyo, JP
Michael Chow - San Mateo CA, US

G07F 17/32
G06F 9/451
G06N 5/04
G06Q 50/34

Odds for various propositions concerning the play of a computer simulation are determined and presented to a viewer for pecuniary or non-pecuniary wagering purposes. The odds may be determined using past game analytics, or may be determined parimutuelly.