Harry S Fung

8527346, Sep 3, 2013

Jun 28, 2004

10/880183

Michael Bigby - San Jose CA, US
Britton Glasser - San Francisco CA, US
Adam Taisch - San Francisco CA, US
Andy Atherton - San Francisco CA, US
Harry Fung - Milpitas CA, US

Yahoo! Inc. - Sunnyvale CA

G06Q 30/00

705 1461, 705 144, 705 1448, 705 1449, 705 1452, 705 1468

A method for scheduling advertising comprises the steps of: estimating a respective fraction of delivered advertisement impressions that result in a response from a user for each of a plurality of advertising contracts, estimating a value per impression for each of the advertising contracts, and scheduling an advertising line under the contract having the highest value per impression at a next available advertising window.

20050228775, Oct 13, 2005

Nov 30, 2004

11/000431

Lars Nilsen - Santa Cruz CA, US
Donna Boyer - San Francisco CA, US
Nilesh Gohel - Fremont CA, US
Nitin Sharma - Mountain View CA, US
Pete Orelup - Captain Cook HI, US
Ken Thomas - Santa Clara CA, US
Scott Gatz - San Francisco CA, US
Jawahar Malhotra - Los Altos CA, US
Harry Fung - Milpitas CA, US

Yahoo! Inc. - Sunnyvale CA

G06F017/30

707002000

A system for dynamically adaptively personalizing at least one navigation control for a web site. Based on collected behaviors for a user, at least one navigation control is dynamically updated to link to a portion of the web site that may be of most interest to the user. Personalized navigation controls for accessing portions of the web site can be dynamically arranged on the web page displayed to the user. Additionally, the personalized navigation may be employed to drives screens of a mobile or living room device.

20070088605, Apr 19, 2007

Oct 19, 2005

11/253907

Sanjiv Ghate - Sunnyvale CA, US
Harry Fung - Milpitas CA, US

G06Q 30/00

705014000

A tolerance band is determined for an online advertisement campaign. The tolerance band defines upper and lower bounds on acceptable deviation from a cumulative linear advertisement delivery goal for the length of the campaign and may be employed to manage delivery of advertisement impressions during the campaign. The upper and lower bounds of tolerance band may flatten with time: acceptable deviation is generally higher at the beginning of the campaign and is lower as the campaign approaches its end date. The tolerance band may be employed to modify a periodically-determined delivery quota for an advertisement line based on the current performance of the advertisement line in relation to its tolerance band. An advertisement line that has fallen below the lower bound may get higher delivery priority relative to other advertisement lines so that it may be given more delivery opportunities. An advertisement line that is delivering above the upper bound may have its quota reduced, possibly to zero, and get lower delivery priority.

20140025486, Jan 23, 2014

Sep 2, 2013

14/016220

Britton Glasser - San Francisco CA, US
Adam Taisch - San Francisco CA, US
Andy Atherton - San Francisco CA, US
Harry Fung - Milpitas CA, US

G06Q 30/02

705 1445

A method for scheduling advertising comprises the steps of: estimating a respective fraction of delivered advertisement impressions that result in a response from a user for each of a plurality of advertising contracts, estimating a value per impression for each of the advertising contracts, and scheduling an advertising line under the contract having the highest value per impression at a next available advertising window.

8364709, Jan 29, 2013

Nov 22, 2010

12/951529

Abhinandan S. Das - Sunnyvale CA, US
Harry S. Fung - Saratoga CA, US

Google Inc. - Mountain View CA

G06F 7/00

707780

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining word boundary likelihoods in potentially incomplete text. In one aspect, a method includes selecting query sequences from the query, each query sequence being at least a portion of a word n-gram, the word n-gram being a subsequence of up to n words selected from the second sequence of words of the query, and for each query sequence: determining one or more query sequence keys for the query sequence; determining at least one of a word boundary count and a non-word boundary count for each query sequence key, each word-boundary count and non-word boundary count being dependent on the context of the query sequence; and associating, in a data storage device, the at least one word boundary count and non-word boundary counts with each query sequence key.

20150213041, Jul 30, 2015

Mar 15, 2013

13/843167

- Mountain View CA, US
Othar Hansson - Sunnyvale CA, US
Bartlomiej Niechwiej - Fremont CA, US
Harry Fung - Saratoga CA, US
Mark Roth Pearson - San Francisco CA, US
David Charles Black - Mountain View CA, US

Google Inc. - Mountain View CA

G06F 17/30

Methods for ranking search suggestions are provided. In one aspect, a method includes receiving a search input and identifying at least one suggestion responsive to the search input from each of a plurality of suggestion sources. Each suggestion has an associated probability ranking value based on a likelihood that the search input is for a query or a likelihood that the search input is for an address. The method also includes providing, for display, each of the suggestions according to the associated probability ranking value of the suggestion. Systems and machine-readable media are also provided.