Alexander M Dekhtyar

20170148084, May 25, 2017

Nov 22, 2016

15/359518

- Paso Robles CA, US
Alexander Dekhtyar - San Luis Obispo CA, US
Toshihiro Kuboi - San Luis Obispo CA, US
Foaad Khosmood - San Luis Obispo CA, US
Evan Lanuza - Paso Robles CA, US
Timothy Scott - Clovis CA, US
Eric Thorndyke - Claremont CA, US

G06Q 30/06
G06F 7/02
G06F 17/30

Systems and methods for recommending an item from a plurality of items. The plurality of items includes chemistry-based features. The system comprises a computing device and a database. The database includes user preference data, item data, and mapping data. The system receives user input regarding user preferences, and associates user preference values with chemistry-based feature values. The system compares chemistry-based feature values for each item to the user preference values and returns items that best match. In one embodiment, the items are wines and the system uses chemistry-based features of wines such as wine volatile chemical compounds to return wine recommendations.

20140164100, Jun 12, 2014

Dec 12, 2013

14/105112

- Boca Raton FL, US
Alexander Dekhtyar - San Luis Obispo CA, US
Maxim Olegovich Rubtsov - Saransk, RU

Codemasters International, LLC - Boca Raton FL

G06Q 30/02

705 1443, 705 1445

A computerized recommender system and an associated computer-implemented method, which accumulate and analyze the information about various marketing actions for promoting brands as well as information about the subsequent brand performance within media channels. The channels include, but are not limited to web, blogs, social networks, search engines, contextual ad networks, email campaigns, and other promotional activities. Additional media channels can be added into the recommender system. The described recommender system enables the marketers to obtain custom advice for a given brand as to what should be the next most effective marketing actions to promote the brand.