Utility for determining competitive restaurants
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IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06Q-010/00
G06Q-030/00
출원번호
US-0337347
(2011-12-27)
등록번호
US-8595050
(2013-11-26)
발명자
/ 주소
Scotto, Stefano Alexander
Zivin, Rhiannon Sterling
출원인 / 주소
GrubHub, Inc.
대리인 / 주소
The Law Offices of Konrad Sherinian, LLC
인용정보
피인용 횟수 :
1인용 특허 :
44
초록▼
A utility for determining the competitors of a subject restaurant accesses a database that contains information about other, nearby restaurants. The utility assigns a competitor score to each restaurant within the maximum radius based on the distance from the subject restaurant, as well as the cuisi
A utility for determining the competitors of a subject restaurant accesses a database that contains information about other, nearby restaurants. The utility assigns a competitor score to each restaurant within the maximum radius based on the distance from the subject restaurant, as well as the cuisine types, menus, and order histories of the subject and competitor restaurants.
대표청구항▼
1. A method of determining competitors for a first restaurant within a database of restaurants, wherein each restaurant in the database has a location, an order history, a cuisine type and a menu comprising a plurality of menu items, the method operating within a computer and comprising the steps of
1. A method of determining competitors for a first restaurant within a database of restaurants, wherein each restaurant in the database has a location, an order history, a cuisine type and a menu comprising a plurality of menu items, the method operating within a computer and comprising the steps of: i) retrieving a plurality of restaurants from the database over a network interface wherein the network interface is coupled to a processor of the computer;ii) filtering, by the processor, the plurality of restaurants to produce a first set of restaurants within a radius of the location of the first restaurant;iii) filtering, by the processor, the first set of restaurants to produce a second set of restaurants with a similar cuisine as the first restaurant;iv) associating, by the processor, each menu item of each restaurant with a true item, wherein the true item is classified by a common nomenclature;v) assigning, by the processor, a match score for the similarity to each pair of true items;vi) comparing, by the processor, the true items of the first restaurant to the true items of each of the restaurants within the second set of restaurants to produce a set of menu scores for the second set of restaurants;vii) comparing, by the processor, an order history of the first restaurant with an order history of each of the restaurants within the second set of restaurants to produce a set of order history scores for the second set of restaurants, wherein each order history includes a plurality of orders wherein each order in the plurality of orders records at least a cost of the order;viii) computing a set of weighted average scores of the set of menu scores and the set of order history scores; andix) based on the set of weighted average scores, filtering, by the processor, the second set of restaurants to produce a first set of competitor restaurants. 2. A method of determining competitors for a first restaurant within a database of restaurants, wherein each restaurant in the database has a location, an order history, a cuisine type and a menu comprising a plurality of menu items, the method operating within a computer and comprising the steps of: i) retrieving a plurality of restaurants from the database over a network interface wherein the network interface is coupled to a processor of the computer;ii) filtering, by the processor, the plurality of restaurants to produce a first set of restaurants within a radius of the location of the first restaurant;iii) filtering, by the processor, the first set of restaurants to produce a second set of restaurants with a similar cuisine as the first restaurant;iv) associating, by the processor, each menu item of each restaurant with a set of true items to form a menu item association, wherein the true items are classified by a common nomenclature;v) assigning, by the processor, a similarity to each pair of true items;vi) comparing, by the processor, the sets of true items of the first restaurant to the sets of true items of each of the restaurants within the second set of restaurants to produce a set of menu scores for the second set of restaurants;vii) comparing, by the processor, an order history of the first restaurant with an order history of each of the restaurants within the second set of restaurants to produce a set of order history scores for the second set of restaurants, wherein each order history includes a plurality of orders wherein each order in the plurality of orders records at least a cost of the order;viii) computing a set of weighted average scores of the set of menu scores and the set of order history scores; andix) based on the set of weighted average scores, filtering, by the processor, the second set of restaurants to produce a first set of competitor restaurants. 3. The method of claim 2 wherein the comparing the sets of true items comprises deriving menu item association based match scores, wherein the set of menu scores are derived from the menu item association based match scores. 4. The method of claim 3 wherein the menu item association based match score between any two sets of true items is a sum of multiplication products of similarities corresponding to true items of the two sets of true items.
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