Achint O Thomas

US Patent:

20110197268, Aug 11, 2011

Filed:

Feb 5, 2010

Appl. No.:

12/701347

Inventors:

Shanmugasundaram Ravikumar - Santa Clara CA, US
Anirban Dasgupta - Berkeley CA, US
Kunal Punera - Mountain View CA, US
Achint Oommen Thomas - Tonawanda NY, US

Assignee:

YAHOO! INC. - Sunnyvale CA

International Classification:

H04L 9/32

US Classification:

726 6, 345419, 345426, 345629

Abstract:

Techniques are described herein for generating CAPTCHAs that include overlapped characters, projections on virtual three-dimensional (3D) surfaces, and/or virtual 3D objects. A CAPTCHA is a type of challenge-response test that a content provider may present to users for authorizing the users to access content that the content provider hosts. For example, when a user attempts to access content, a CAPTCHA may be generated in accordance with one or more of the techniques described herein and provided to the user. The user may be asked to identify characters that overlap in the CAPTCHA, characters that are projected on a virtual 3D surface, and/or a designated virtual 3D object, so that the user may be authorized to access the content. The user may enter the characters and/or select the designated virtual 3D object that is identified in the CAPTCHA using an input device, such as a keyboard, touch screen, pointing device, etc.

US Patent:

20120166379, Jun 28, 2012

Filed:

Dec 23, 2010

Appl. No.:

12/978186

Inventors:

Anirban Dasgupta - Berkeley CA, US
Liang Zhang - Fremont CA, US
Maxim Gurevich - Cupertino CA, US
Achint Oommen Thomas - Buffalo NY, US
Belle Tseng - Cupertino CA, US

Assignee:

Yahoo! Inc. - Sunnyvale CA

International Classification:

G06N 5/02

US Classification:

706 50

Abstract:

Embodiments are directed towards clustering cookies for identifying unique mobile devices for associating activities over a network with a given mobile device. The cookies are clustered based on a Bayes Factor similarity model that is trained from cookie features of known mobile devices. The clusters may be used to determine the number of unique mobile devices that access a website. The clusters may also be used to provide targeted content to each unique mobile device.

US Patent:

20130159227, Jun 20, 2013

Filed:

Feb 14, 2013

Appl. No.:

13/767695

Inventors:

Yahoo! Inc. - Sunnyvale CA, US
Liang Zhang - Fremont CA, US
Maxim Gurevich - Cupertino CA, US
Achint Oommen Thomas - Sunnyvale CA, US
Belle Tseng - Cupertino CA, US

Assignee:

Yahoo! Inc. - Sunnyvale CA

International Classification:

G06N 99/00

US Classification:

706 12

Abstract:

Embodiments are directed towards clustering cookies for identifying unique mobile devices for associating activities over a network with a given mobile device. The cookies are clustered based on a Bayes Factor similarity model that is trained from cookie features of known mobile devices. The clusters may be used to determine the number of unique mobile devices that access a website. The clusters may also be used to provide targeted content to each unique mobile device.

US Patent:

20190260731, Aug 22, 2019

Filed:

Apr 30, 2019

Appl. No.:

16/398940

Inventors:

- New York NY, US
Keiko Horiguchi - Palo Alto CA, US
Amanda Joy Stent - Chatham NJ, US
Jeffrey Kuwano - San Jose CA, US
Achint Oommen Thomas - Milpitas CA, US
Yi Chang - Milpitas CA, US

International Classification:

H04L 29/06
G06F 3/16
G10L 21/003
G06F 21/31
G10L 25/51
H04L 9/32
G10L 17/06

Abstract:

One or more techniques and/or systems are provided for audio verification. An audio signal, comprising a code for user verification, may be identified. A second audio signal is created comprising speech. The audio signal and the second audio signal may be altered to comprise a same or similar volume, pitch, amplitude, and/or speech rate. The audio signal and the second audio signal may be combined to generate a verification audio signal. The verification audio signal may be presented to a user for the user verification. Verification may be performed to determine whether the user has access to content or a service based upon user input, obtained in response to the user verification audio signal, matching the code within the user verification audio signal. In an example, the user verification may comprise verifying that the user is human.

US Patent:

20180255012, Sep 6, 2018

Filed:

May 7, 2018

Appl. No.:

15/973130

Inventors:

- New York NY, US
Martin Zinkevich - Santa Clara CA, US
Lihong Li - Santa Clara CA, US
Achint Oommen Thomas - Buffalo NY, US
Belle Tseng - Cupertino CA, US

International Classification:

H04L 12/58
G06N 5/02
G06F 11/00
G06Q 50/20
G06N 7/00
G06F 15/16

Abstract:

Software for online active learning receives content posted to an online stream at a website. The software converts the content into an elemental representation and inputs the elemental representation into a probit model to obtain a predictive probability that the content is abusive. The software also calculates an importance weight based on the elemental representation. And the software updates the probit model using the content, the importance weight, and an acquired label if a condition is met. The condition depends on an instrumental distribution. The software removes the content from the online stream if a condition is met. The condition depends on the predictive probability, if an acquired label is unavailable.

US Patent:

20170068805, Mar 9, 2017

Filed:

Sep 8, 2015

Appl. No.:

14/847742

Inventors:

- Sunnyvale CA, US
Keiko Horiguchi - Palo Alto, JP
Amanda Joy Stent - Chatham NJ, US
Jeffrey Kuwano - San Jose CA, US
Achint Oommen Thomas - Milpitas CA, US
Yi Chang - Milpitas CA, US

International Classification:

G06F 21/32
G06F 3/16

Abstract:

One or more techniques and/or systems are provided for audio verification. An audio signal, comprising a code for user verification, may be identified. A second audio signal is created comprising speech. The audio signal and the second audio signal may be altered to comprise a same or similar volume, pitch, amplitude, and/or speech rate. The audio signal and the second audio signal may be combined to generate a verification audio signal. The verification audio signal may be presented to a user for the user verification. Verification may be performed to determine whether the user has access to content or a service based upon user input, obtained in response to the user verification audio signal, matching the code within the user verification audio signal. In an example, the user verification may comprise verifying that the user is human.

US Patent:

20160253598, Sep 1, 2016

Filed:

Feb 27, 2015

Appl. No.:

14/634515

Inventors:

- Sunnyvale CA, US
Chao Qin - Sunnyvale CA, US
Hua Ouyang - Sunnyvale CA, US
Achint Thomas - Sunnyvale CA, US
Yi Chang - Sunnyvale CA, US

International Classification:

G06N 99/00

Abstract:

In one embodiment, a set of training data consisting of inliers may be obtained. A supervised classification model may be trained using the set of training data to identify outliers. The supervised classification model may be applied to generate an anomaly score for a data point. It may be determined whether the data point is an outlier based, at least in part, upon the anomaly score.

US Patent:

20140229487, Aug 14, 2014

Filed:

Jun 13, 2012

Appl. No.:

14/119202

Inventors:

Smruthi Mukund - Sunnyvale CA, US
Venugopal Govindaraju - Williamsville NY, US
Anurag Bhardwaj - Sunnyvale CA, US
Achint Oommen Thomas - Sunnyvale CA, US
Srirangaraj Setlur - Getzville NY, US

Assignee:

The Research Foundation of State University of New York - Amherst NY

International Classification:

G06F 17/30

US Classification:

707740, 707748, 707736

Abstract:

A system and method are disclosed for user preference augmentation through social network inner-circle knowledge discovery. A user's activity may be captured allow a user preference model to be created. The user preference model is compared to other models in the user's social network. A inner-circle social network is created, and the user preference model is augmented based on other preference models in the inner-circle social network, and the user's own preference for certain categories of information element. Information elements can be provided to the user based on suggestions and the user's preference model. The information elements may be organized such that the more relevant information elements are more easily accessible to the user.