Helen E Fisher

US Patent:

8583563, Nov 12, 2013

Filed:

Dec 23, 2008

Appl. No.:

12/342158

Inventors:

Francisco J. Bonilla - Carrollton TX, US
Sharmistha Dubey - Coppell TX, US
Amanda W. Ginsberg - Dallas TX, US
James C. Moore - Frisco TX, US
Clark T. Rothrock - McKinney TX, US
Helen E. Fisher - New York NY, US

Assignee:

Match.com, L.L.C. - Dallas TX

International Classification:

G06Q 99/00
G06Q 10/00

US Classification:

705319, 705 11

Abstract:

In one example embodiment, a method is provided that includes interfacing with one or more end users via a central website and managing information related to one or more of the end users. The method also includes determining a personality type for one or more end users and matching end users based on relationship rules of the personality types that outline compatibilities between the personality types. In more specific embodiments, the determining of the personality type includes an evaluation of a hand of a selected end user. The personality types can be based on inferred levels of testosterone, serotonin, or estrogen. The personality type determination can also be made based on a set of questions. The personality type determination can also be based on evaluating a selected end user's word choice and/or the frequency in their word choice in their writing.

US Patent:

20150142839, May 21, 2015

Filed:

Nov 20, 2013

Appl. No.:

14/084723

Inventors:

- DALLAS TX, US
DEVARAJ SUNDARAM - DALLAS TX, US
MONICA KLAWITTER - DALLAS TX, US
AMARNATH THOMBRE - DALLAS TX, US
HELEN FISHER - NEW YORK NY, US
SYDNEY LAM - DALLAS TX, US
TODD CARRICO - MELISSA TX, US

Assignee:

MATCH.COM, L.L.C. - DALLAS TX

International Classification:

G06F 17/30

US Classification:

707758

Abstract:

Finding a match for an end user on an online social platform is not a trivial task. To improve match making, various methods and systems are disclosed which are configured to compute heuristics for various end users, which help to predict the likelihood that two end users would ultimately engage in some form of communication with each other. The heuristics are used in an algorithm (i.e., a statistical/predictive model) for providing a set of matches to an end user. These heuristics may be computed based on varying forms of communication which indicate different levels of engagement between end users, and/or based on some other indication of how an end user may react to another end user.