# US 2018/0025368 A1 · Crowd-based ranking of types of food using measurements of affective response > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2018/0025368 A1 - Document ID: US20180025368A1 - Status: Published application - Kind: A1 - Application number: 15/701,101 - Filed: 2017-09-11 - Published: 2018-01-25 - Earliest claimed: 2014-08-21 - Assignees: Affectomatics Ltd. - Applicants: Affectomatics Ltd. - Inventors: Ari M. Frank; Gil Thieberger - Web page: https://patentgrep.com/patent/US20180025368A1 ## CPC - G06Q 30/0201: Market modelling; Market analysis; Collecting market data - G06F 16/24578: {using ranking} - G06F 16/337: {Profile generation, learning or modification} - G06F 16/9535: Search customisation based on user profiles and personalisation - G06Q 10/101: Collaborative creation, e.g. joint development of products or services - G06Q 10/40: Business processes related to social networking or social networking services - G06Q 30/02: Marketing; Price estimation or determination; Fundraising - G06Q 30/0282: Rating or review of business operators or products - G06Q 50/12: Hotels or restaurants - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Some aspects of this disclosure involve ranking types of food based on measurements of affective response of users who consumed the types of food. In one embodiment, a system that ranks types of food includes sensors that take measurements of affective response of users and a computer. The computer receives indications of times at which the users consumed the types of food and selects for each type of food, based on the indications, measurements of at least five of the users taken up to four hours after consuming the type of food. The computer ranks the types of food based on the selected measurements. Optionally, each of the types of food is a different item on a menu comprising food items. ## Claims ### Claim 1 A system configured to rank types of food, comprising: sensors configured to take measurements of affective response of users; and a computer configured to: receive indications of times at which the users consumed the types of food; select for each type of food, based on the indications, measurements of at least five of the users taken up to four hours after consuming the type of food; and rank the types of food based on the selected measurements. ### Claim 2 (depends on 1) The system of claim 1, wherein when a first type of food from among the types of food is ranked higher than a second type of food from among the types of food, on average, the at least five of the users who consumed the first type of food had a more positive affective response than the at least five of the users who consumed the second type of food. ### Claim 3 (depends on 1) The system of claim 1, wherein each of the types of food is a different item on a menu comprising food items. ### Claim 4 (depends on 1) The system of claim 1, wherein the computer is further configured to: (i) receive information, obtained from a financial account of a user from among the users, indicating that the user purchased the type of food from among the types of food; and (ii) select, based on the information, which measurements of affective response of the user to utilize for ranking the types of food. ### Claim 5 (depends on 1) The system of claim 1, wherein the computer is further configured to: (i) receive information, obtained from a social media account of a user from among the at least five of the users who consumed a certain type of food, indicating when the user consumed the certain type of food; and (ii) select, based on the information, which measurements of affective response of the user to utilize for ranking the types of food. ### Claim 6 (depends on 1) The system of claim 1, wherein the computer is further configured to: calculate for each type of food a score based on the measurements of the at least five of the users who consumed the type of food; wherein the computer is configured to rank the types of food based on magnitudes of the scores for the types of food. ### Claim 7 (depends on 1) The system of claim 1, wherein the computer is further configured to generate a plurality of preference rankings for the types of food; wherein each preference ranking is determined based on a subset of the measurements, and comprises a ranking of at least two of the types of food, such that one of the at least two of the types of food is ranked ahead of another type of food from among the at least two of the types of food; and wherein the computer is configured to utilize a method that satisfies the Condorcet criterion to rank the types of food based on the plurality of the preference rankings. ### Claim 8 (depends on 7) The system of claim 7, wherein the measurements in each subset used to determine a preference ranking are measurements of a single user. ### Claim 9 (depends on 1) The system of claim 1, wherein the computer is further configured to forward a result of the ranking of the types of food to be utilized by a module that makes a recommendation regarding one or more of the types of food. ### Claim 10 (depends on 1) The system of claim 1, wherein the computer is further configured to receive profiles of the users and first and second profiles of first and second users, respectively; the computer is further configured to generate a first output indicative of similarities between the first profile and the profiles of the users and a second output indicative of similarities between the second profile and the profiles of the users; the computer is further configured to calculate a first ranking of the types of food, based on the measurements and the first output, and to calculate a second ranking of the types of food, based on the measurements and the second output; and wherein in the first ranking, a third type of food is ranked higher than a fourth type of food, while in the second ranking, the fourth type of food is ranked higher than the third type of food. ### Claim 11 (depends on 10) The system of claim 10, wherein a profile of a user comprises indications of one or more of the following: (i) an indication of a preferred dietary choice comprising one or more of the following: vegetarian food, vegan food, and low-carb food; (ii) an indication of a sensitivity to a certain food ingredient; (iii) a food allergy; (iv) a preference regarding a certain brand; (v) a preference towards a certain restaurant; (vi) and an extent of previous consumption of one or more types of food. ### Claim 12 (depends on 10) The system of claim 10, wherein the computer is configured to generate the first output by calculating values indicative of a similarity between each of the profiles of the users and the first profile, and utilizing the values to calculate weights for the measurements of the users; wherein a weight for a measurement of a user is proportional to an extent of a similarity between the profile of the user and the profile of the first user, such that a weight calculated for a measurement of a user whose profile is more similar to the profile of the first user is higher than a weight calculated for a measurement of a user whose profile is less similar to the profile of the first user; wherein the first output is indicative of the weights for the measurements of the users; and wherein the computer is configured to: calculate for each type of food a score based on the measurements of the at least five of the users who consumed the type of food and the weights calculated for said measurements, and to rank the types of food based on magnitudes of the scores for the types of food; wherein the score calculated for the third type of food is higher than the score calculated for the fourth type of food. ### Claim 13 (depends on 10) The system of claim 10, wherein the computer is configured to generate the first output by calculating values indicative of a similarity between each of the profiles and the first profile, and utilizing the values to calculate weights for the measurements of the users; wherein the weight for a measurement of a user is proportional to an extent of a similarity between the profile of the user and the profile of the first user, such that a weight calculated for a measurement of a user whose profile is more similar to the profile of the first user is higher than a weight calculated for a measurement of a user whose profile is less similar to the profile of the first user; the first output is indicative of the weights for the measurements of the users; the computer is further configured to generate a plurality of preference rankings for the types of food; each preference ranking is determined based on a subset of the measurements, has a corresponding weight determined based on the weights of the measurements comprised in the subset, and comprises a ranking of at least two of the types of food, such that one of the at least two types of food is ranked ahead of another type of food from among the at least two types of food; and wherein the computer is further configured to rank the types of food based on the plurality of the preference rankings utilizing a method that satisfies the Condorcet criterion. ### Claim 14 (depends on 10) The system of claim 10, wherein the computer is configured to generate the first output by clustering users into clusters based on similarities between the profiles of the users, with each cluster comprising a single user or multiple users with similar profiles, and selecting, based on the first profile, a subset comprising at most half of the clusters; wherein, on average, the first profile is more similar to a profile of a user who is a member of a cluster in the subset, than it is to a profile of a user, from among the users, who is not a member of any of the clusters in the subset; the computer is further configured to select at least eight users from among the users belonging to clusters in the subset; wherein the first output is indicative of the at least eight users; and wherein the computer is configured to rank the types of food based on the measurements of the at least eight users. ### Claim 15 A method for ranking types of food, comprising: taking measurements of affective response of users with sensors; receiving indications of times at which the users consumed the types of food; selecting for each type of food, based on the indications, measurements of at least five of the users taken up to four hours after consuming the type of food; and ranking the types of food based on the selected measurements. ### Claim 16 (depends on 15) The method of claim 15, further comprising: calculating for each type of food a score based on the measurements of the at least five of the users who consumed the type of food, and ranking the types of food based on magnitudes of the scores for the types of food. ### Claim 17 (depends on 15) The method of claim 15, further comprising generating a plurality of preference rankings for the types of food; wherein each preference ranking is determined based on a subset of the measurements, and comprises a ranking of at least two of the types of food, such that one of the at least two types of food is ranked ahead of another type from among the at least two types of food; and further comprising ranking the types of food based on the plurality of preference rankings utilizing a method that satisfies the Condorcet criterion. ### Claim 18 (depends on 15) The method of claim 15, further comprising: receiving profiles of the users and first and second profiles of first and second users, respectively; generating a first output indicative of similarities between the first profile and the profiles of the users, and a second output indicative of similarities between the second profile and the profiles of the users; and calculating a first ranking of the types of food based on the measurements and the first output, and a second ranking of the types of food based on the measurements and the second output; wherein in the first ranking, a first type of food is ranked higher than a second type of food, while in the second ranking, the second type of food is ranked higher than the first type of food. ### Claim 19 A non-transitory computer-readable medium having instructions stored thereon that, in response to execution by a system including a processor and memory, causes the system to perform operations comprising: receiving measurements of affective response of users taken with sensors; receiving indications of times at which the users consumed the types of food; selecting for each type of food, based on the indications, measurements of at least five of the users taken up to four hours after consuming the type of food; and ranking the types of food based on the selected measurements. ### Claim 20 (depends on 19) The non-transitory computer-readable medium of claim 19, further comprising additional instructions that, in response to execution, cause the system to perform operations comprising: receiving profiles of the users and first and second profiles of first and second users, respectively; generating a first output indicative of similarities between the first profile and the profiles of the users and a second output indicative of similarities between the second profile and the profiles of the users; and calculating a first ranking of the types of food based on the measurements and the first output, and a second ranking of the types of food based on the measurements and the second output; wherein in the first ranking, a first type of food is ranked higher than a second type of food, while in the second ranking, the second type of food is ranked higher than the first type of food.