Tak Chung Yan

20080091524, Apr 17, 2008

Oct 13, 2006

11/580586

Tak W. Yan - Palo Alto CA, US
Kerem Tomak - Mountain View CA, US
Chi-Chao Chang - Santa Clara CA, US

Yahoo! Inc. - Sunnyvale CA

G06Q 30/00

705 14

The present invention relates to systems and methods for generating an adjustment factor for a cost associated with a user selection of an advertisement displayed at a website. The method of the present invention comprises retrieving analytics data and traffic quality metric data associated with the website, and calculating a traffic quality score for the website. An adjustment factor for the website is calculated based upon the traffic quality score associated with the website and a benchmark traffic quality score.

20090171728, Jul 2, 2009

Dec 27, 2007

11/965002

Tak W. Yan - Palo Alto CA, US
Prabhakar Krishnamurthy - Pleasanton CA, US
Ketan Deshpande - San Jose CA, US
Chih-Chao Chang - Santa Clara CA, US
Soam Acharya - San Bruno CA, US

G06Q 10/00
G06F 17/30
G06Q 30/00

705 8, 707 3, 705 14, 705 30, 707E17014

The present invention provides a method and apparatus for sponsored Internet-based search simulation. The present invention includes receiving a search query sequence that represents a search query and selecting one or more advertisements based on the search query sequence. The present invention further includes filtering the plurality of advertisements based on advertising budget data and determining a number of user-selections on the advertisements using a pre-calculated user-selection model. The present invention further includes updating advertiser account information regarding advertising rates in response to the number of user-selections and generating simulation log data reflecting the advertisings, user-selections and advertising account information. This technique thereby performs the simulation based on user search queries, in response to user-selection models and references the user-selection and advertisement with advertisement budget data, consistent with live sponsored search result operations.

20090254410, Oct 8, 2009

Apr 3, 2008

12/062289

Chi-Chao Chang - Santa Clara CA, US
Ramazan Demir - Sherman Oaks CA, US
Matthew Hall - San Jose CA, US
Sai-Ming Li - Santa Clara CA, US
Darshan Kantak - Pasadena CA, US
Tak Woon Yan - Palo Alto CA, US

Yahoo! Inc. - Sunnyvale CA

G06Q 30/00

705 10, 705 14

A method and system for constructing and delivering sponsored search contracts is provided. In one implementation, the method may include generating a financial instrument with terms, such as a contract, for selling click-throughs. The terms may include a volume of click-throughs, a price, and a core market. The price of the contract may be related to an expected quality of the advertisement. The core market may be described in terms of key words. The contract terms may be communicated to an advertiser. The advertiser may then bind an advertisement to the contract or sell the contract to another advertiser. The contract performance may be tracked and communicated.

20130346218, Dec 26, 2013

Jun 21, 2012

13/528898

Weiguo Liu - Dublin CA, US
Tak Yan - Palo Alto CA, US
Victor Chu - Milpitas CA, US

MICROSOFT CORPORATION - Redmond WA

G06Q 30/02

705 1471

Various embodiments pertain to techniques for utilizing confidence indicators to adjust bidding values used to obtain impression opportunities. In various embodiments, a system clusters a plurality of ad impression opportunities according to received information regarding each of the ad impression opportunities. Information about the clusters, referred to as data spots, is calculated and utilized to classify the data spots into one or more categories. Bidding strategies are assigned to each category. When the system receives an ad impression opportunity from an impression provider, the system identifies a data spot to which the received ad impression opportunity corresponds and determines a bid for the ad impression opportunity according to the bidding strategy assigned to the category into which the identified data spot is classified.

20130346219, Dec 26, 2013

Jun 25, 2012

13/532310

Ye Chen - Sunnyvale CA, US
Pavel Berkhin - Sunnyvale CA, US
Jie Li - Palo Alto CA, US
Xia Sharon Wan - Saratoga CA, US
Tak Yan - Palo Alto CA, US

MICROSOFT CORPORATION - Redmond WA

G06Q 30/02

705 1471

Methods and systems for estimating the value of a contextual ad impression are provided. Requests for value-based bids for ad impressions are received from bidders and the value of the ad impression is estimated based primarily upon leveraging sell-side data (user and publisher). The estimation is highly economized through a fast implementation of k-nearest-neighbor (kNN) regression. Embodiments of the present invention further address the cold-start problem or the exploration vs. exploitation requirement by Bayesian (hierarchical) smoothing using a beta prior, and adapt to the temporal dynamics using an autoregressive model to decay importance of certain data.

56089040, Mar 4, 1997

Feb 13, 1995

8/387527

Surajit Chaudhuri - Stanford CA
Umeshwar Dayal - Saratoga CA
Tak W. Yan - Stanford CA

Hewlett-Packard Company - Palo Alto CA

G06F 1730

395602

Probe-based query processing for a database system that loosely integrates a structured database and a text retrieval system is described. The query processing constructs a query plan that efficiently evaluates a conjunctive query having joins of structured and textual data by sending to the text retrieval system one or more text search/retrieve operations.

20150142566, May 21, 2015

Nov 19, 2013

14/083694

- Redmond WA, US
Tak W. Yan - Palo Alto CA, US
Ye Chen - Sunnyvale WA, US

Microsoft Corporation - Redmond WA

G06Q 30/02

705 1454

Systems, methods, and computer-readable media for providing fresh product listing advertisements in response to a search query are presented. More particularly, in response to receiving a search query, a plurality of search results are identified, which search results are relevant to the search query. Additionally, a first set of product listing advertisements is identified. A second set of product listing advertisements, which are fresh product listing advertisements, are also identified and combined into the first set. Upon generating the search results page, at least some of the identified search results and some of the product listing advertisements are included. At least one of the fresh product listing advertisements is included in the generated search results page. The at least one fresh product listing advertisement is tagged with an annotation indicating that the advertisement is a fresh product listing advertisement.

20140129323, May 8, 2014

Nov 6, 2012

13/670348

- Redmond WA, US
Ye Chen - Sunnyvale CA, US
Alan Lu - Santa Clara CA, US
Tak Yan - Palo Alto CA, US
Liangzhong Yin - Palo Alto CA, US

MICROSOFT CORPORATION - Redmond WA

G06Q 30/02

705 1445

Traffic quality on online properties may be assessed continually, and the traffic quality may be used to determine the price of a click-through for an ad placed on the web property. Advertisers bid on keywords, and the bids are used by an advertising engine to place ads on web pages and other online properties. A benchmark price may be set based on the bids. When a user clicks on (or otherwise activates) an ad, the advertiser pays an amount for the click that is based on the benchmark price and on the traffic quality of the property on which the ad had been placed. Machine learning may be used to create a model that predicts traffic quality based on observable feature of a property, thereby allowing the traffic quality of a property to be assessed in real time rather than historically.