US20190279255A1 - Device, method and non-transitory computer readable storage medium for determining a match between profiles - Google Patents
Device, method and non-transitory computer readable storage medium for determining a match between profiles Download PDFInfo
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- US20190279255A1 US20190279255A1 US16/423,160 US201916423160A US2019279255A1 US 20190279255 A1 US20190279255 A1 US 20190279255A1 US 201916423160 A US201916423160 A US 201916423160A US 2019279255 A1 US2019279255 A1 US 2019279255A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
Definitions
- the present disclosure relates to determining a match between two or more profiles.
- an electronic device comprises a computer-readable memory constructed to store computer-executable process steps and a processor constructed to execute the computer-executable process steps stored in the memory.
- the process steps stored in the memory include computer-executable process steps to acquire a personal profile for a person identified by a unique identifier received at the electronic device.
- the personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. Responsive to reception of at least one candidate personal profile of at least one candidate person, the process steps control the electronic device to perform a match between the personal profile and the at least one candidate personal profile.
- the process steps control the electronic device to provide at least one user-perceivable indicator that indicates a result of the match.
- a method of controlling an electronic device to acquire a personal profile for a person includes controlling the electronic device to acquire a personal profile for a person identified by a unique identifier received at the electronic device.
- the personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. Responsive to reception of at least one candidate personal profile of at least one candidate person, the electronic device is controlled to perform a match between the personal profile and the at least one candidate personal profile. The electronic device is controlled to provide at least one user-perceivable indicator that indicates a result of the match.
- a non-transitory computer-readable storage medium stores computer-executable process steps that when executed by a processor of an electronic device, control the electronic device to acquire a personal profile for a person identified by a unique identifier received at the electronic device.
- the personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier.
- the process steps control the electronic device to perform a match between the personal profile and the at least one candidate personal profile.
- the process steps control the electronic device to provide at least one user-perceivable indicator that indicates a result of the match.
- people may more efficiently discover other people who share a common interest, and may discover a more meaningful connection with the other people.
- a method of controlling an electronic device to acquire a personal profile for a person includes receiving a unique identifier of a person at the electronic device, and controlling the electronic device to acquire a personal profile for the person identified by the received unique identifier.
- the personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier.
- the electronic device is controlled to store the acquired personal profile.
- the unique identifier of the person is received via a user-input device of the electronic device.
- the unique identifier of the person is a fingerprint received via a fingerprint scanner.
- the personal profile is generated and stored prior to receipt of the unique identifier, and the personal profile is acquired by accessing the stored profile in response to receipt of the unique identifier.
- the personal data is collected prior to receipt of the unique identifier, and the personal profile is acquired by applying big data analytics to the collected personal data in response to receipt of the unique identifier.
- the personal data is generated prior to receipt of the unique identifier
- the personal profile is acquired by collecting the generated personal data and applying big data analytics to the collected personal data in response to receipt of the unique identifier.
- the personal data includes at least one of purchase data, user profile data, user preferences data, user recommendation data, customer review data, media consumption data, web browsing data, tax filing data, social network data, legal data, financial data, calendar data, e-mail data, Twitter data, geo-location data, travel history, photo data, medical data, criminal record data, marriage records, birth records, wedding registry data, DNA data, and employment data.
- the personal data is passively collected without requiring a user-input from the person, and the personal data is collected anonymously without processing any personally identifiable information.
- the personal profile is generated anonymously without processing any personally identifiable information.
- the personal profile is acquired by using a trusted third party to access the personal profile associated with the unique identifier.
- the personal data is collected by using a trusted third party to access the personal data associated with the unique identifier.
- the personal data is collected from a plurality of data sources.
- the user-perceivable indicator is a display of information on a display device of the electronic device, the displayed information including a description of the match.
- the electronic device displays the personal profile in a human-readable format.
- the at least one candidate personal profile is received based on proximity of the electronic device to an electronic device of the at least one candidate person.
- the at least one candidate personal profile is received based on physical contact between the electronic device and an electronic device of the at least one candidate person.
- location information identifying a location of the electronic device is determined, and each received candidate personal profile is received from an electronic device having a location within an area determined by the determined location information.
- the location information describes a place, and each received candidate personal profile is received from an electronic device located in the place described by the location information.
- the location information describes an event, and each received candidate personal profile is received from an electronic device located at the event described by the location information.
- the location information describes location coordinates, and each received candidate personal profile is received from an electronic device located within a specified distance from the location coordinates described by the location information.
- the electronic device is at least one of a computer, a tablet, a wearable electronic device, a smart band, a digital watch, a smart watch, a digital camera, a video camera, a mobile phone, a mobile computer, a digital music player, and a personal digital assistant (PDA).
- a computer a tablet
- a wearable electronic device a smart band
- a digital watch a smart watch
- a digital camera a video camera
- a mobile phone a mobile computer
- a digital music player and a personal digital assistant (PDA).
- PDA personal digital assistant
- the match includes at least one of a social match, a romantic match, a business match, a job seeker and prospective employer match, a buyer and seller match, and a service provider and client match.
- the match is performed by using big data analytics.
- FIG. 1 is a view of an electronic device according to an example embodiment.
- FIG. 2 is a diagram depicting the internal architecture of the electronic device of FIG. 1 according to an example embodiment.
- FIG. 3 is a flow diagram for explaining processing performed by the electronic device of FIG. 1 according to an example embodiment.
- FIG. 4 is a diagram depicting a profile matching system according to an example embodiment.
- FIG. 5 is a block diagram depicting the internal architecture of a user-generated content profile generation device according to an example embodiment.
- FIG. 6 is a block diagram depicting the internal architecture of a personal data profile generation device according to an example embodiment.
- FIG. 7 is a block diagram depicting the internal architecture of a profile repository according to an example embodiment.
- FIG. 8 is a block diagram depicting the internal architecture of a photo profile generation device according to an example embodiment.
- FIG. 9 is a block diagram depicting the internal architecture of a marketing server according to an example embodiment.
- FIG. 10 is a flow diagram for explaining processing performed by the electronic device of FIG. 1 according to an example embodiment.
- a person's interests can be identified by performing Big Data analytics. For example, a person's purchase data (e.g., from credit cards, customer loyalty cards, and the like), media consumption data (e.g., TV viewing data, Internet media streaming data, iTunes media data), web browsing data, tax filing data, social network data, calendar data, e-mail data, Twitter data, geo-location data, travel history, photo data, medical data, criminal record data, DNA data, employment data, and the like can be analyzed determine a person's interests and objectives. Based on this analytics, a profile can be generated for the person, and this profile can be compared with similarly generated profiles of other people to determine a match between two or more people.
- Big Data analytics For example, a person's purchase data (e.g., from credit cards, customer loyalty cards, and the like), media consumption data (e.g., TV viewing data, Internet media streaming data, iTunes media data), web browsing data, tax filing data, social network data, calendar data, e-mail data, Twitter data, geo-location data,
- a device, method and non-transitory computer readable storage medium are provided for determining a match between two or more people, based on personal profiles generated by analyzing personal information.
- the device When a person carrying an electronic device that functions according to the claims herein is near a person with a similar device (or, alternatively, when bumping devices with another person), the device indicates whether the two people share common interests, based on big data analytics.
- the match could be a social match, a romantic match, a business match, a job seeker and prospective employer match, a buyer and seller match, a service provider and client match, and the like.
- Fingerprint recognition is used to automatically configure the device with the person's personal profile, which is then used to determine a match with other people.
- FIG. 1 is a view of an electronic device 100 according to an example embodiment.
- electronic device 100 is a smart phone.
- the electronic device can be one or more of a computer, a tablet, a wearable electronic device, a smart band, a digital watch, a smart watch, a digital camera, a video camera, a mobile phone, a mobile computer, a digital music player, and a personal digital assistant (PDA)
- PDA personal digital assistant
- the electronic device 100 is controlled to acquire a personal profile for a person identified by a unique identifier received at the electronic device 100 .
- the personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. Responsive to reception of at least one candidate personal profile of at least one candidate person, the electronic device 100 is controlled to perform a match between the personal profile and the at least one candidate personal profile. The electronic device 100 is controlled to provide at least one user-perceivable indicator that indicates a result of the match.
- the unique identifier of the person is a fingerprint received via a fingerprint scanner 102 .
- the unique identifier of the person can be any type of identifier that can uniquely identify a person, and the unique identifier can be received via any type of user-input device of the electronic device.
- the unique identifier can be any combination of one or more of a fingerprint, a social security number, a driver's license number, a phone number, a birth date, a passport number, a biometric identifier, a credit card number, an address, an employer identifier, an educational identifier, a marital status identifier, and a DNA identifier.
- the personal profile is generated by applying big data analytics to personal data collected for the person identified by the unique identifier, and the generated profile is stored prior to receipt of the unique identifier.
- the personal profile is generated by a data processing system (not shown).
- the personal profile can be generated by the electronic device 100 .
- the electronic device 100 acquires the personal profile by accessing the stored profile in response to receipt of the unique identifier.
- the personal data is data that is automatically generated by a data processing system, such as, for example, the data processing system used to generate the personal profile, or a different data processing system.
- the personal data is collected prior to receipt of the unique identifier.
- the personal data is collected by a data processing system (not shown).
- the personal data is generated prior to receipt of the unique identifier.
- the personal data is generated by a data processing system (not shown).
- the personal data can be collected by the electronic device 100 .
- the electronic device can acquire the personal profile by applying big data analytics to the collected personal data in response to receipt of the unique identifier.
- the personal data can be generated by the electronic device 100 .
- the electronic device can acquire the personal profile by collecting the generated personal data and applying big data analytics to the collected personal data in response to receipt of the unique identifier.
- the personal data includes, for example, at least one of purchase data, user profile data, user preferences data, user recommendation data, customer review data, media consumption data, web browsing data, tax filing data, social network data, legal data, financial data, calendar data, e-mail data, Twitter data, geo-location data, travel history, photo data, medical data, criminal record data, marriage records, birth records, wedding registry data, DNA data, employment data, and the like.
- the personal data is passively collected without requiring a user-input from the person for whom the profile is acquired.
- this person is the person using the electronic device 100 .
- the personal data is collected anonymously without processing any personally identifiable information, and the personal profile is generated anonymously without processing any personally identifiable information.
- the personal profile is acquired by using a trusted third party to access the personal profile associated with the unique identifier, and the personal data is collected by using a trusted third party to access the personal data associated with the unique identifier.
- the personal data is collected from a plurality of data sources.
- the personal data can be collected from a single source. In another embodiment, the personal data is not collected anonymously. In another embodiment, the personal profile is not generated anonymously.
- the user-perceivable indicator is a display of information on display device, such as, for example, the touch screen display 101 of the electronic device 100 .
- the displayed information includes a description of the match.
- any user-perceivable indicator capable of indicating a result of the match can be provided.
- Other user-perceivable indicators include, for example, visual indicators, such as a LED or a display, and audible indicators.
- the electronic device 100 displays the personal profile in a human-readable format on the display 101 .
- a candidate personal profile is received by the electronic device 100 based on physical contact between the electronic device 100 and an electronic device of a candidate person. For example, the user of electronic device 100 can bump the device 100 against the electronic device of a candidate person.
- a candidate personal profile is received based on proximity of the electronic device 100 to an electronic device of the candidate person.
- location information identifying a location of the electronic device 100 is determined, by using, for example, a GPS unit in electronic device 100 .
- a candidate personal profile from an electronic device having a location within an area determined by the determined location information is received by the electronic device 100 .
- the location information describes a place, and each received candidate personal profile is received from an electronic device located in the place described by the location information.
- a place can be, for example, a restaurant, a stadium, an amusement park, an attraction, a museum, an airport, a building, a school, a subway, an airplane, a boat, a bus, a library, and the like.
- the location information describes an event, and each received candidate personal profile is received from an electronic device located at the event described by the location information.
- a place can be, for example, a concert, a sporting event, a conference, a social event, a business event, and the like.
- the location information describes location coordinates, and each received candidate personal profile is received from an electronic device located within a specified distance from the location coordinates described by the location information.
- the match is performed by using at least one matching algorithm.
- the match is performed by the electronic device 100 .
- the match can be performed by another device or data processing system.
- the matching algorithm includes at least one of a heuristic match, a keyword match, a value match, an image match, a statistical match, a social match, and an audio match.
- the match is performed by using multiple, different matching algorithms, each matching algorithm for matching a particular type of profile data included in the personal profile and the at least one candidate personal profile.
- the match is performed by using big data analytics.
- the match includes at least one of a social match, a romantic match, a business match, a job seeker and prospective employer match, a buyer and seller match, and a service provider and client match.
- FIG. 2 is a detailed block diagram depicting the internal architecture of the device 100 of FIG. 1 according to an example embodiment.
- the bus 201 interfaces with a one or more processors 202 , a random access memory (RAM) 203 , a read only memory (ROM) 204 , a computer-readable storage medium 205 , an image capture device 206 , a display device 207 , a user input device 208 , a network device 209 , a microphone 210 , a speaker 211 , a GPS device (not shown), a proximity sensor (not shown), a motion sensor (not shown), an accelerometer (not shown), and a gyroscope (not shown).
- the one or more processors 202 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like.
- CPU central processing unit
- MPU multi-processor unit
- ARM processor ARM processor
- the one or more processors 202 and the random access memory (RAM) 203 form a processing unit 220 .
- the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions.
- the processing unit is an ASIC (Application-Specific Integrated Circuit).
- the processing unit is a SoC (System-on-Chip).
- User input device 208 receives scanned fingerprint data from fingerprint scanner 102 , and receives user input from touch screen display 101 .
- Display device 207 controls display of touch screen display 101 .
- the network device 209 provides one or more wired or wireless interfaces for exchanging data and commands between the device 100 and other devices.
- wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like.
- USB Universal Serial Bus
- NFC Near Field Communication
- Machine-executable instructions in software programs and modules are loaded into the memory 203 (of the processing unit 220 ) from the computer-readable storage medium 205 , the ROM 204 or any other storage location.
- the respective machine-executable instructions are accessed by the CPU 202 (of the processing unit 220 ) via the bus 201 , and then executed by the CPU 202 .
- Data used by the software programs and modules are also stored in the memory 203 , and such data is accessed by the CPU 202 during execution of the machine-executable instructions of the software programs and modules.
- the computer-readable storage medium 205 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like.
- the computer-readable storage medium 205 includes an operating system 212 , the software programs 213 , device drivers 214 , a profile module 215 , a matching module 216 , a fingerprint module 217 , and profiles 218 .
- the processing unit 220 loads machine-executable instructions of the profile module 215 and executes the instructions to acquire a personal profile for a person identified by a unique identifier received at the electronic device 100 .
- the unique identifier of the person is a fingerprint received via the fingerprint scanner 102 and the user input device 208 .
- the fingerprint scanner 102 is controlled by machine-readable instructions of the fingerprint module 217 .
- the personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier.
- the personal profile is generated by a data processing system (not shown).
- processing unit 220 acquires the personal profile by accessing the profile from stored profiles 218 in response to receipt of the unique identifier.
- the processing unit 220 acquires the personal profile by accessing a remotely stored profile via the network device 209 , in response to receipt of the unique identifier.
- the processing unit 220 Responsive to reception of at least one candidate profile (e.g., a personal profile of at least one candidate person or a target personal profile of a marketer) via the network device 209 , the processing unit 220 loads machine-executable instructions of the matching module 216 and executes the instructions to perform a match between the personal profile and the at least one candidate profile. In the example embodiment, the match is performed by comparing keywords of the personal profile with one or more keywords of the candidate profile. The processing unit 220 controls the display device 207 to display at least one user-perceivable indicator that indicates a result of the match on touch screen display 101 .
- at least one candidate profile e.g., a personal profile of at least one candidate person or a target personal profile of a marketer
- FIG. 3 is a flow diagram for explaining processing performed by the electronic device 100 of FIG. 1 according to an example embodiment.
- the following is an example of a matching scenario performed by the electronic device 100 .
- a user of device 100 posts an updated resume on a job searching web-site, and the resume indicates that the user of device 100 is a software developer.
- the data processing system (not shown) collects the resume of the user of device 100 and uses it, along with other personal data, to generate a personal profile for the user of device 100 .
- the personal profile indicates, for example, that the user is a software engineer seeking employment at a software company.
- the electronic device 100 Responsive to the user of device 100 scanning their finger on the fingerprint scanner 102 of device 100 , at 301 , the electronic device 100 is controlled to acquire the personal profile for the user, who is identified by the scanned fingerprint data received at the electronic device 100 via the fingerprint scanner 102 .
- the user of electronic device 100 bumps the device 100 against the electronic device of a candidate person to exchange profiles. If a candidate profile has not been received (“NO” at 302 ) processing returns to 302 . If a candidate profile has been received (“YES” at 302 ) processing proceeds to 303 .
- the electronic device 100 is controlled to perform a match between the personal profile of the user and the at least one candidate personal profile.
- the candidate personal profile is a profile that has been generated the same way as with the user profile of device 100 by using big analytics.
- the data processing system collects the candidate's social network profile data and the software company's job listing, and uses this collected data, along with other personal data, to generate a personal profile for the candidate.
- the candidate profile indicates, for example, that the candidate is a hiring manager seeking to hire a software engineer for the software company. If the user of device 100 and the candidate meet at a software developer conference and bump devices, then their profiles will be matched.
- the personal profile of the user of device 100 indicates that the user is a software engineer seeking employment at a software company and the candidate profile indicates that the candidate is a hiring manager seeking to hire a software engineer for the software company, the result of the match will indicate that a match has been found between the user of device 100 and the candidate.
- processing proceeds to 304 and the processing unit 220 executes instructions of the matching module 216 to control the display device 207 to display at least one user-perceivable indicator that indicates a result of the match on touch screen display 101 .
- processing returns to 302 .
- FIG. 4 is a diagram depicting a profile matching system 400 that includes the electronic device 100 and an electronic device 401 , a profile generation system 410 , a marketing server 402 , a photo sharing server 403 , a social media server 404 , and a personal data processing server 405 .
- the profile generation system 410 includes a photo profile generation device 406 , a user-generated content profile generation device 407 , a personal data profile generation device 408 , and a profile repository 409 .
- FIG. 5 is a detailed block diagram depicting the internal architecture of the user-generated content profile generation device 407 .
- FIG. 6 is a detailed block diagram depicting the internal architecture of the personal data profile generation device 408 .
- FIG. 7 is a detailed block diagram depicting the internal architecture of the profile repository 409 .
- FIG. 8 is a detailed block diagram depicting the internal architecture of the photo profile generation device 406 .
- FIG. 9 is a detailed block diagram depicting the internal architecture of the marketing server 402 .
- the electronic device 100 is constructed to communicatively couple with another electronic device 401 , which is similar to the electronic device 100 . More specifically, the electronic device 401 has an architecture that is similar to the architecture described above with respect to FIG. 2 , and the electronic device is constructed to perform the process described above with respect to FIG. 3 .
- the electronic device 401 is constructed to communicatively couple with the electronic device 100 and the profile generation system 410 .
- the electronic device 100 is also constructed to communicatively with the marketing server 402 , the profile generation system 410 , the photo sharing server 403 , the social media server 404 , and the personal data processing server 405 .
- the electronic device 100 is not communicatively coupled with one or more of the photo sharing server 403 , the social media server 404 , the personal data processing server 405 , the marketing server 402 , and the electronic device 401 .
- the electronic device 100 is not communicatively coupled with one or more of the photo sharing server 403 , the social media server 404 , the personal data processing server 405 , the profile generation system 410 , and the electronic device 401 .
- the electronic device 100 is not communicatively coupled with one or more of the photo sharing server 403 , the social media server 404 , the personal data processing server 405 , the profile generation system 410 , and the marketing server 402 .
- the electronic device 100 is not communicatively coupled with one or more of the electronic device 401 , the social media server 404 , the personal data processing server 405 , the profile generation system 410 , and the marketing server 402 .
- the electronic device 100 is not communicatively coupled with one or more of the electronic device 401 , the photo sharing server 403 , the personal data processing server 405 , the profile generation system 410 , and the marketing server 402 .
- the electronic device 100 is not communicatively coupled with one or more of the electronic device 401 , the photo sharing server 403 , the social media server 404 , the profile generation system 410 , and the marketing server 402
- the photo profile generation device 406 the user-generated content profile generation device 407 , and the personal data profile generation device 408 are constructed to communicatively couple with the photo sharing server 403 , the social media server 404 , and the personal data processing server 405 , respectively, by using a corresponding application programming interface (API).
- API application programming interface
- the photo profile generation device 406 , the user-generated content profile generation device 407 , and the personal data profile generation device 408 are each communicatively coupled with the profile repository 409 .
- the profile generation system 410 includes one or more of the photo profile generation device 406 , the user-generated content profile generation device 407 , and the personal data profile generation device 408 .
- the electronic devices 100 and 401 each include a profile matching system similar to the profile matching system 400 .
- the marketing server 402 includes a profile matching system similar to the profile matching system 400 .
- the personal data processing server 405 is constructed to automatically generate personal data.
- personal data includes, for example, one or more of purchase data, user profile data, user preferences data, user recommendation data, customer review data, media consumption data, web browsing data, tax filing data, social network data, legal data, financial data, calendar data, e-mail data, Twitter data, geo-location data, travel history, photo data, medical data, criminal record data, marriage records, birth records, wedding registry data, DNA data, employment data, and the like.
- FIG. 5 is a detailed block diagram depicting the internal architecture of the user-generated content profile generation device 407 .
- the bus 501 interfaces with a one or more processors 502 , a random access memory (RAM) 503 , a read only memory (ROM) 504 , a computer-readable storage medium 505 , a display device 507 , a user input device 508 , and a network device 509 .
- processors 502 a random access memory (RAM) 503 , a read only memory (ROM) 504 , a computer-readable storage medium 505 , a display device 507 , a user input device 508 , and a network device 509 .
- the one or more processors 502 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like.
- CPU central processing unit
- MPU multi-processor unit
- ARM processor ARM processor
- the one or more processors 502 and the random access memory (RAM) 503 form a processing unit 520 .
- the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions.
- the processing unit is an ASIC (Application-Specific Integrated Circuit).
- the processing unit is a SoC (System-on-Chip).
- the network device 509 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated content profile generation device 407 and other devices.
- wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like.
- USB Universal Serial Bus
- NFC Near Field Communication
- Machine-executable instructions in software programs and modules are loaded into the memory 503 (of the processing unit 520 ) from the computer-readable storage medium 505 , the ROM 504 or any other storage location.
- the respective machine-executable instructions are accessed by the CPU 502 (of the processing unit 520 ) via the bus 501 , and then executed by the CPU 502 .
- Data used by the software programs are also stored in the memory 503 , and such data is accessed by the CPU 502 during execution of the machine-executable instructions of the software programs and modules.
- the computer-readable storage medium 505 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like.
- the computer-readable storage medium 505 includes an operating system 512 , the software programs 513 , device drivers 514 , a user-generated content profile generation module 515 , and user-generated content 516 .
- the processing unit 520 loads machine-executable instructions of the user-generated content profile generation module 515 and executes the instructions to collect user-generated content 516 uploaded by a person (that is identified by a unique identifier) to the social-media server 404 .
- the processing unit 520 collects the user-generated content 516 by using an application programming interface (API) of the social-media server 404 .
- API application programming interface
- Executing the instructions of the user-generated content profile generation module 515 the processing unit 520 generates a personal profile of the person by applying one or more of object recognition, voice recognition, character recognition, and textual analysis processing to the user-generated content 516 to generate one or more keywords, the generated personal profile including the one or more keywords.
- Executing the instructions of the user-generated content profile generation module 515 the processing unit 520 stores the generated personal profile in a storage medium ( 705 of FIG. 7 ) of the profile repository 409 .
- FIG. 6 is a detailed block diagram depicting the internal architecture of the personal data profile generation device 408 .
- the bus 601 interfaces with a one or more processors 602 , a random access memory (RAM) 603 , a read only memory (ROM) 604 , a computer-readable storage medium 605 , a display device 607 , a user input device 608 , and a network device 609 .
- processors 602 a random access memory (RAM) 603 , a read only memory (ROM) 604 , a computer-readable storage medium 605 , a display device 607 , a user input device 608 , and a network device 609 .
- the one or more processors 602 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like.
- CPU central processing unit
- MPU multi-processor unit
- ARM processor ARM processor
- the one or more processors 602 and the random access memory (RAM) 603 form a processing unit 620 .
- the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions.
- the processing unit is an ASIC (Application-Specific Integrated Circuit).
- the processing unit is a SoC (System-on-Chip).
- the network device 609 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated content profile generation device 407 and other devices.
- wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like.
- USB Universal Serial Bus
- NFC Near Field Communication
- Machine-executable instructions in software programs and modules are loaded into the memory 603 (of the processing unit 620 ) from the computer-readable storage medium 605 , the ROM 604 or any other storage location.
- the respective machine-executable instructions are accessed by the CPU 602 (of the processing unit 620 ) via the bus 601 , and then executed by the CPU 602 .
- Data used by the software programs are also stored in the memory 603 , and such data is accessed by the CPU 602 during execution of the machine-executable instructions of the software programs and modules.
- the computer-readable storage medium 605 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like.
- the computer-readable storage medium 605 includes an operating system 612 , the software programs 613 , device drivers 614 , a personal data profile generation module 615 , and personal data 616 .
- the processing unit 620 loads machine-executable instructions of the personal data profile generation module 615 and executes the instructions to collect personal data 616 (for person that is identified by a unique identifier) that is generated by the personal data processing server 405 .
- the processing unit 620 collects the personal data 616 by using an application programming interface (API) of the personal data processing server 405 .
- API application programming interface
- Executing the instructions of the personal data profile generation module 615 the processing unit 620 generate a personal profile of the person by applying big data analytics to the collected personal data to generate one or more keywords to the personal data 616 to generate one or more keywords, the generated personal profile including the one or more keywords.
- Executing the instructions of the personal data profile generation module 615 the processing unit 620 stores the generated personal profile in a storage medium ( 705 of FIG. 7 ) of the profile repository 409 .
- FIG. 7 is a detailed block diagram depicting the internal architecture of the profile repository 409 .
- the bus 701 interfaces with a one or more processors 702 , a random access memory (RAM) 703 , a read only memory (ROM) 704 , a computer-readable storage medium 705 , a display device 707 , a user input device 708 , and a network device 709 .
- the one or more processors 702 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like.
- CPU central processing unit
- MPU multi-processor unit
- ARM processor ARM processor
- the one or more processors 702 and the random access memory (RAM) 703 form a processing unit 720 .
- the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions.
- the processing unit is an ASIC (Application-Specific Integrated Circuit).
- the processing unit is a SoC (System-on-Chip).
- the network device 709 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated content profile generation device 407 and other devices.
- wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like.
- USB Universal Serial Bus
- NFC Near Field Communication
- Machine-executable instructions in software programs and modules are loaded into the memory 703 (of the processing unit 720 ) from the computer-readable storage medium 705 , the ROM 704 or any other storage location.
- the respective machine-executable instructions are accessed by the CPU 702 (of the processing unit 720 ) via the bus 701 , and then executed by the CPU 702 .
- Data used by the software programs are also stored in the memory 703 , and such data is accessed by the CPU 702 during execution of the machine-executable instructions of the software programs and modules.
- the computer-readable storage medium 705 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like.
- the computer-readable storage medium 705 includes an operating system 712 , the software programs 713 , device drivers 714 , an authentication module 715 and a profile data store 716 .
- the processing unit 720 loads machine-executable instructions of the authentication module 715 and executes the instructions to authenticate a unique identifier provided by an electronic device (e.g., the electronic device 100 or 401 ) that is requesting a personal profile for a person identified by the unique identifier. Responsive to a determination that the unique identifier has been authenticated, the processing unit 720 executes loads and executes instructions of the profile data store 716 to access one or more profiles that correspond to the authenticated unique identifier and to provide the one or more profiles to the electronic device that has requested the personal profile (e.g., the electronic device 100 or 401 ).
- the processing unit 720 executes loads and executes instructions of the profile data store 716 to store one or more personal profiles received from one or more of the photo profile generation device 406 , the user-generated content profile generation device 407 , and the personal data profile generation device 408 in the storage medium 705 in association with a corresponding unique identifier.
- the processing unit 720 executes loads and executes instructions of the profile data store 716 to combine profiles associated with the same unique identifier. For example, the processing unit 720 can combine a profile generated for a person by each of photo profile generation device 406 , the user-generated content profile generation device 407 , and the personal data profile generation device 408 into a single profile for the person, the profile being associated with a single unique identifier.
- FIG. 8 is a detailed block diagram depicting the internal architecture of the photo profile generation device 406 .
- the bus 801 interfaces with a one or more processors 802 , a random access memory (RAM) 803 , a read only memory (ROM) 804 , a computer-readable storage medium 805 , a display device 807 , a user input device 808 , and a network device 809 .
- processors 802 a random access memory (RAM) 803 , a read only memory (ROM) 804 , a computer-readable storage medium 805 , a display device 807 , a user input device 808 , and a network device 809 .
- RAM random access memory
- ROM read only memory
- the one or more processors 802 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like.
- CPU central processing unit
- MPU multi-processor unit
- ARM processor ARM processor
- the one or more processors 802 and the random access memory (RAM) 803 form a processing unit 820 .
- the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions.
- the processing unit is an ASIC (Application-Specific Integrated Circuit).
- the processing unit is a SoC (System-on-Chip).
- the network device 809 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated content profile generation device 407 and other devices.
- wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like.
- USB Universal Serial Bus
- NFC Near Field Communication
- Machine-executable instructions in software programs and modules are loaded into the memory 803 (of the processing unit 820 ) from the computer-readable storage medium 805 , the ROM 804 or any other storage location.
- the respective machine-executable instructions are accessed by the CPU 802 (of the processing unit 820 ) via the bus 801 , and then executed by the CPU 802 .
- Data used by the software programs are also stored in the memory 803 , and such data is accessed by the CPU 802 during execution of the machine-executable instructions of the software programs and modules.
- the computer-readable storage medium 805 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like.
- the computer-readable storage medium 805 includes an operating system 812 , the software programs 813 , device drivers 814 , a photo profile generation module 815 , and photos 816 .
- the processing unit 820 loads machine-executable instructions of the photo profile generation module 815 and executes the instructions to collect photos 816 uploaded by a person (that is identified by a unique identifier) to the photo sharing server 403 .
- the processing unit 820 collects the photos 816 by using an application programming interface (API) of the photo sharing server 403 .
- API application programming interface
- Executing the instructions of the photo profile generation module 815 the processing unit 820 generates a personal profile of the person by applying one or more of object recognition and character recognition to the photos 816 to generate one or more keywords, the generated personal profile including the one or more keywords.
- Executing the instructions of the photo profile generation module 815 the processing unit 820 stores the generated personal profile in a storage medium ( 705 of FIG. 7 ) of the profile repository 409 .
- FIG. 9 is a detailed block diagram depicting the internal architecture of the marketing server 402 .
- the bus 901 interfaces with a one or more processors 902 , a random access memory (RAM) 903 , a read only memory (ROM) 904 , a computer-readable storage medium 905 , a display device 907 , a user input device 908 , and a network device 909 .
- the one or more processors 902 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like.
- CPU central processing unit
- MPU multi-processor unit
- ARM processor ARM processor
- the one or more processors 902 and the random access memory (RAM) 903 form a processing unit 920 .
- the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions.
- the processing unit is an ASIC (Application-Specific Integrated Circuit).
- the processing unit is a SoC (System-on-Chip).
- the network device 909 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated content profile generation device 407 and other devices.
- wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like.
- USB Universal Serial Bus
- NFC Near Field Communication
- Machine-executable instructions in software programs and modules are loaded into the memory 903 (of the processing unit 920 ) from the computer-readable storage medium 905 , the ROM 904 or any other storage location.
- the respective machine-executable instructions are accessed by the CPU 902 (of the processing unit 920 ) via the bus 901 , and then executed by the CPU 902 .
- Data used by the software programs are also stored in the memory 903 , and such data is accessed by the CPU 902 during execution of the machine-executable instructions of the software programs and modules.
- the computer-readable storage medium 905 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like.
- the computer-readable storage medium 905 includes an operating system 912 , the software programs 913 , device drivers 914 , a target profile management module 915 , target personal profiles 916 , and marketer information 917 .
- the processing unit 920 loads machine-executable instructions of the target profile management module 915 and executes the instructions to provide an electronic device (e.g., the electronic device 100 of FIG. 1 ) with one or more target personal profiles 916 .
- the marketing server processing unit 920 executing the instructions of the target profile management module 915 , the marketing server processing unit 920 provides at least one target personal profile 916 to an electronic device (e.g., the electronic device 100 ) responsive to a request received from the electronic device.
- an electronic device e.g., the electronic device 100
- the marketing server 402 receives location information for one or more electronic devices, and executing the instructions of the target profile management module 915 , the marketing server processing unit 920 provides target personal profiles 916 to electronic devices (e.g., the electronic device 100 ) based on the received location information.
- a retail location can contain a retail electronic device that is associated with the marketing server, the retail electronic device can receive location information of electronic devices, and the marketing server 402 can provide one or more target profiles to one or more electronic devices (via the retail electronic device) based on proximity of the electronic devices to the retail electronic device.
- the marketing server processing unit 920 executing the instructions of the target profile management module 915 , provides at least one target personal profile 916 to an electronic device (e.g., the electronic device 100 ) based on proximity of the electronic device to an electronic device associated with the marketing server 402 .
- the marketing server processing unit 920 executing the instructions of the target profile management module 915 , provides at least one target personal profile 916 to an electronic device (e.g., the electronic device 100 ) based on physical contact between the electronic device and an electronic device associated with the marketing server 402 .
- an electronic device e.g., the electronic device 100
- location information identifying a location of an electronic device associated with the marketing server 402 is determined, executing the instructions of the target profile management module 915 , the marketing server processing unit 920 provides at least one target personal profile 916 to an electronic device (e.g., the electronic device 100 ) having a location within an area determined by the determined location information.
- the location information describes a place, and the marketing server processing unit 920 provides at least one target personal profile 916 to an electronic device (e.g., the electronic device 100 ) located in the place described by the location information.
- the location information describes an event
- the marketing server processing unit 920 provides at least one target personal profile 916 to an electronic device (e.g., the electronic device 100 ) located at the event described by the location information.
- the location information describes location coordinates
- the marketing server processing unit 920 provides at least one target personal profile 916 to an electronic device (e.g., the electronic device 100 ) located within a specified distance from the location coordinates described by the location information.
- the processing unit 920 loads machine-executable instructions of the target profile management module 915 and executes the instructions to provide an electronic device (e.g., the electronic device 100 of FIG. 1 ) with marketer information 917 responsive.
- the marketing server processing unit 920 executes the instructions of the target profile management module 915 .
- the marketing server processing unit 920 provides the electronic device with marketer information 917 responsive to a request for marketer information from the electronic device, the request indicting that the electronic device processing unit 220 has executed the instructions of the matching module 216 and has determined a match between a target personal profile 916 (received by the electronic device from the marketing server 402 ) and a personal profile for a user that is associated with a unique identifier (e.g., a scanned fingerprint data received at the electronic device 100 via the fingerprint scanner 102 ) received by the electronic device.
- a unique identifier e.g., a scanned fingerprint data received at the electronic device 100 via the fingerprint scanner 102
- the marketing server processing unit 920 executing the instructions of the target profile management module 915 , provides the electronic device with marketer information 917 responsive to a request for marketer information from the electronic device, the request including a personal profile for a user that is associated with a unique identifier (e.g., a scanned fingerprint data received at the electronic device 100 via the fingerprint scanner 102 ) received by the electronic device.
- the marketing server processing unit 920 determines a match between a target personal profile 916 and the received personal profile, and responsive to a determination of a match, the marketing server processing unit 920 provides the electronic device with marketer information 917 .
- the marketer information 917 includes at least one of advertising information and reward information.
- the reward information includes information related to at least one of a coupon, a prize, a credit, a monetary reward, information for a marketing promotion, and the like.
- the electronic device displays a visual representation of the received marketer information.
- FIG. 10 is a flow diagram for explaining processing performed by the electronic device 100 of FIG. 1 according to an example embodiment.
- the electronic device 100 Responsive to the user of device 100 scanning their finger on the fingerprint scanner 102 of device 100 , at 1001 , the electronic device 100 is controlled to acquire the personal profile for the user (from the profile generation system 400 ), who is identified by the scanned fingerprint data received at the electronic device 100 via the fingerprint scanner 102 .
- the electronic device processing unit 220 of the electronic device determines whether the electronic device 100 has received a target personal profile from the marketing server 402 , as described above with respect to FIG. 9 . If a target personal profile has not been received (“NO” at 1002 ) processing returns to 1002 . If a target personal profile has been received (“YES” at 1002 ) processing proceeds to 1003 .
- the electronic device 100 is controlled to perform a match between the personal profile of the user and the target personal profile.
- the target personal profile is a profile that specifies a marketer's target consumer.
- processing proceeds to 1004 and the processing unit 220 executes instructions of the matching module 216 to provide the marketing server 402 with a request for marketer information from the electronic device 100 , the request indicting that the electronic device processing unit 220 has executed the instructions of the matching module 216 and has determined a match between the target personal profile 916 (received by the electronic device from the marketing server 402 ) and the personal profile received by the electronic device at the process S 1001 .
- the processing unit 220 executes instructions of the matching module 216 to control the display device 207 to display a visual representation of the received marketer information on the touch screen display 101 of the electronic device 100 .
- processing returns to 1002 .
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Abstract
Controlling an electronic device to acquire a personal profile for a person. The electronic device acquires a personal profile for a person identified by a unique identifier. The personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. Responsive to reception of at least one candidate profile, the electronic device is controlled to perform a match between the personal profile and the at least one candidate personal profile. The electronic device is controlled to provide at least one user-perceivable indicator that indicates a result of the match. The unique identifier of the person is a fingerprint received via a fingerprint scanner. The personal profile is generated and stored by a data processing system prior to receipt of the unique identifier.
Description
- This application is a continuation of U.S. application Ser. No. 14/520,302, filed Oct. 21, 2014, which claims the benefit of U.S. Provisional Patent Application No. 61/893,857, entitled “DEVICE, METHOD AND NON-TRANSITORY COMPUTER READABLE STORAGE MEDIUM FOR DETERMINING A MATCH BETWEEN TWO OR MORE PEOPLE,” filed Oct. 21, 2013, the disclosures of which are incorporated by reference herein in their entirety.
- The present disclosure relates to determining a match between two or more profiles.
- When meeting other people in person, it is often helpful to quickly discover other people who share a common interest. Knowledge of common interests helps spark conversation, and allows the people to work together more efficiently towards achieving a common objective.
- When providing targeted advertising, it is often helpful to identify consumers who match a target profile.
- In an example embodiment, an electronic device comprises a computer-readable memory constructed to store computer-executable process steps and a processor constructed to execute the computer-executable process steps stored in the memory. The process steps stored in the memory include computer-executable process steps to acquire a personal profile for a person identified by a unique identifier received at the electronic device. The personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. Responsive to reception of at least one candidate personal profile of at least one candidate person, the process steps control the electronic device to perform a match between the personal profile and the at least one candidate personal profile. The process steps control the electronic device to provide at least one user-perceivable indicator that indicates a result of the match.
- In an example embodiment, a method of controlling an electronic device to acquire a personal profile for a person is provided. The method includes controlling the electronic device to acquire a personal profile for a person identified by a unique identifier received at the electronic device. The personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. Responsive to reception of at least one candidate personal profile of at least one candidate person, the electronic device is controlled to perform a match between the personal profile and the at least one candidate personal profile. The electronic device is controlled to provide at least one user-perceivable indicator that indicates a result of the match.
- In an example embodiment, a non-transitory computer-readable storage medium is provided. The non-transitory computer-readable storage medium stores computer-executable process steps that when executed by a processor of an electronic device, control the electronic device to acquire a personal profile for a person identified by a unique identifier received at the electronic device. The personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. Responsive to reception of at least one candidate personal profile of at least one candidate person, the process steps control the electronic device to perform a match between the personal profile and the at least one candidate personal profile. The process steps control the electronic device to provide at least one user-perceivable indicator that indicates a result of the match.
- By virtue of the foregoing, people may more efficiently discover other people who share a common interest, and may discover a more meaningful connection with the other people.
- In an example embodiment, a method of controlling an electronic device to acquire a personal profile for a person is provided. The method includes receiving a unique identifier of a person at the electronic device, and controlling the electronic device to acquire a personal profile for the person identified by the received unique identifier. The personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. The electronic device is controlled to store the acquired personal profile.
- According to an aspect, the unique identifier of the person is received via a user-input device of the electronic device. According to an aspect, the unique identifier of the person is a fingerprint received via a fingerprint scanner.
- According to an aspect, the personal profile is generated and stored prior to receipt of the unique identifier, and the personal profile is acquired by accessing the stored profile in response to receipt of the unique identifier.
- According to an aspect, the personal data is collected prior to receipt of the unique identifier, and the personal profile is acquired by applying big data analytics to the collected personal data in response to receipt of the unique identifier.
- According to an aspect, the personal data is generated prior to receipt of the unique identifier, and the personal profile is acquired by collecting the generated personal data and applying big data analytics to the collected personal data in response to receipt of the unique identifier.
- According to an aspect, the personal data includes at least one of purchase data, user profile data, user preferences data, user recommendation data, customer review data, media consumption data, web browsing data, tax filing data, social network data, legal data, financial data, calendar data, e-mail data, Twitter data, geo-location data, travel history, photo data, medical data, criminal record data, marriage records, birth records, wedding registry data, DNA data, and employment data.
- According to an aspect, the personal data is passively collected without requiring a user-input from the person, and the personal data is collected anonymously without processing any personally identifiable information. The personal profile is generated anonymously without processing any personally identifiable information. The personal profile is acquired by using a trusted third party to access the personal profile associated with the unique identifier. The personal data is collected by using a trusted third party to access the personal data associated with the unique identifier. According to one aspect, the personal data is collected from a plurality of data sources.
- According to an aspect, the user-perceivable indicator is a display of information on a display device of the electronic device, the displayed information including a description of the match.
- According to one aspect, the electronic device displays the personal profile in a human-readable format.
- According to one aspect, the at least one candidate personal profile is received based on proximity of the electronic device to an electronic device of the at least one candidate person. According to one aspect, the at least one candidate personal profile is received based on physical contact between the electronic device and an electronic device of the at least one candidate person. According to one aspect, location information identifying a location of the electronic device is determined, and each received candidate personal profile is received from an electronic device having a location within an area determined by the determined location information. According to one aspect, the location information describes a place, and each received candidate personal profile is received from an electronic device located in the place described by the location information. According to one aspect, the location information describes an event, and each received candidate personal profile is received from an electronic device located at the event described by the location information. According to one aspect, the location information describes location coordinates, and each received candidate personal profile is received from an electronic device located within a specified distance from the location coordinates described by the location information.
- According to one aspect, the electronic device is at least one of a computer, a tablet, a wearable electronic device, a smart band, a digital watch, a smart watch, a digital camera, a video camera, a mobile phone, a mobile computer, a digital music player, and a personal digital assistant (PDA).
- According to one aspect, the match includes at least one of a social match, a romantic match, a business match, a job seeker and prospective employer match, a buyer and seller match, and a service provider and client match. According to one aspect, the match is performed by using big data analytics.
- This brief summary has been provided so that the nature of this disclosure may be understood quickly. A more complete understanding can be obtained by reference to the following detailed description and to the attached drawings.
-
FIG. 1 is a view of an electronic device according to an example embodiment. -
FIG. 2 is a diagram depicting the internal architecture of the electronic device ofFIG. 1 according to an example embodiment. -
FIG. 3 is a flow diagram for explaining processing performed by the electronic device ofFIG. 1 according to an example embodiment. -
FIG. 4 is a diagram depicting a profile matching system according to an example embodiment. -
FIG. 5 is a block diagram depicting the internal architecture of a user-generated content profile generation device according to an example embodiment. -
FIG. 6 is a block diagram depicting the internal architecture of a personal data profile generation device according to an example embodiment. -
FIG. 7 is a block diagram depicting the internal architecture of a profile repository according to an example embodiment. -
FIG. 8 is a block diagram depicting the internal architecture of a photo profile generation device according to an example embodiment. -
FIG. 9 is a block diagram depicting the internal architecture of a marketing server according to an example embodiment. -
FIG. 10 is a flow diagram for explaining processing performed by the electronic device ofFIG. 1 according to an example embodiment. - The inventor has observed that a person's interests can be identified by performing Big Data analytics. For example, a person's purchase data (e.g., from credit cards, customer loyalty cards, and the like), media consumption data (e.g., TV viewing data, Internet media streaming data, iTunes media data), web browsing data, tax filing data, social network data, calendar data, e-mail data, Twitter data, geo-location data, travel history, photo data, medical data, criminal record data, DNA data, employment data, and the like can be analyzed determine a person's interests and objectives. Based on this analytics, a profile can be generated for the person, and this profile can be compared with similarly generated profiles of other people to determine a match between two or more people.
- In view of the foregoing, a device, method and non-transitory computer readable storage medium are provided for determining a match between two or more people, based on personal profiles generated by analyzing personal information.
- When a person carrying an electronic device that functions according to the claims herein is near a person with a similar device (or, alternatively, when bumping devices with another person), the device indicates whether the two people share common interests, based on big data analytics. The match could be a social match, a romantic match, a business match, a job seeker and prospective employer match, a buyer and seller match, a service provider and client match, and the like. Fingerprint recognition is used to automatically configure the device with the person's personal profile, which is then used to determine a match with other people.
-
FIG. 1 is a view of anelectronic device 100 according to an example embodiment. In the example embodiment,electronic device 100 is a smart phone. In some embodiments, the electronic device can be one or more of a computer, a tablet, a wearable electronic device, a smart band, a digital watch, a smart watch, a digital camera, a video camera, a mobile phone, a mobile computer, a digital music player, and a personal digital assistant (PDA) - In the example embodiment, the
electronic device 100 is controlled to acquire a personal profile for a person identified by a unique identifier received at theelectronic device 100. The personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. Responsive to reception of at least one candidate personal profile of at least one candidate person, theelectronic device 100 is controlled to perform a match between the personal profile and the at least one candidate personal profile. Theelectronic device 100 is controlled to provide at least one user-perceivable indicator that indicates a result of the match. - In the example embodiment, the unique identifier of the person is a fingerprint received via a
fingerprint scanner 102. - In some embodiments, the unique identifier of the person can be any type of identifier that can uniquely identify a person, and the unique identifier can be received via any type of user-input device of the electronic device. For example, the unique identifier can be any combination of one or more of a fingerprint, a social security number, a driver's license number, a phone number, a birth date, a passport number, a biometric identifier, a credit card number, an address, an employer identifier, an educational identifier, a marital status identifier, and a DNA identifier.
- In the example embodiment, the personal profile is generated by applying big data analytics to personal data collected for the person identified by the unique identifier, and the generated profile is stored prior to receipt of the unique identifier. In the example embodiment, the personal profile is generated by a data processing system (not shown). In some embodiments, the personal profile can be generated by the
electronic device 100. In the example embodiment, theelectronic device 100 acquires the personal profile by accessing the stored profile in response to receipt of the unique identifier. In the example embodiment, the personal data is data that is automatically generated by a data processing system, such as, for example, the data processing system used to generate the personal profile, or a different data processing system. In the example embodiment, the personal data is collected prior to receipt of the unique identifier. In the example embodiment, the personal data is collected by a data processing system (not shown). In the example embodiment, the personal data is generated prior to receipt of the unique identifier. In the example embodiment, the personal data is generated by a data processing system (not shown). - In some embodiments, the personal data can be collected by the
electronic device 100. In some embodiments, the electronic device can acquire the personal profile by applying big data analytics to the collected personal data in response to receipt of the unique identifier. - In some embodiments, the personal data can be generated by the
electronic device 100. In some embodiments, the electronic device can acquire the personal profile by collecting the generated personal data and applying big data analytics to the collected personal data in response to receipt of the unique identifier. - In the example embodiment, the personal data includes, for example, at least one of purchase data, user profile data, user preferences data, user recommendation data, customer review data, media consumption data, web browsing data, tax filing data, social network data, legal data, financial data, calendar data, e-mail data, Twitter data, geo-location data, travel history, photo data, medical data, criminal record data, marriage records, birth records, wedding registry data, DNA data, employment data, and the like.
- In the example embodiment, the personal data is passively collected without requiring a user-input from the person for whom the profile is acquired. In the example embodiment, this person is the person using the
electronic device 100. The personal data is collected anonymously without processing any personally identifiable information, and the personal profile is generated anonymously without processing any personally identifiable information. The personal profile is acquired by using a trusted third party to access the personal profile associated with the unique identifier, and the personal data is collected by using a trusted third party to access the personal data associated with the unique identifier. The personal data is collected from a plurality of data sources. - In some embodiments, the personal data can be collected from a single source. In another embodiment, the personal data is not collected anonymously. In another embodiment, the personal profile is not generated anonymously.
- In the example embodiment, the user-perceivable indicator is a display of information on display device, such as, for example, the
touch screen display 101 of theelectronic device 100. In the example embodiment, the displayed information includes a description of the match. In some embodiments, any user-perceivable indicator capable of indicating a result of the match can be provided. Other user-perceivable indicators include, for example, visual indicators, such as a LED or a display, and audible indicators. - In the example embodiment, the
electronic device 100 displays the personal profile in a human-readable format on thedisplay 101. - In the example embodiment, a candidate personal profile is received by the
electronic device 100 based on physical contact between theelectronic device 100 and an electronic device of a candidate person. For example, the user ofelectronic device 100 can bump thedevice 100 against the electronic device of a candidate person. - In another embodiment, a candidate personal profile is received based on proximity of the
electronic device 100 to an electronic device of the candidate person. - In another embodiment, location information identifying a location of the
electronic device 100 is determined, by using, for example, a GPS unit inelectronic device 100. A candidate personal profile from an electronic device having a location within an area determined by the determined location information is received by theelectronic device 100. In some embodiments, the location information describes a place, and each received candidate personal profile is received from an electronic device located in the place described by the location information. A place can be, for example, a restaurant, a stadium, an amusement park, an attraction, a museum, an airport, a building, a school, a subway, an airplane, a boat, a bus, a library, and the like. In some embodiments, the location information describes an event, and each received candidate personal profile is received from an electronic device located at the event described by the location information. A place can be, for example, a concert, a sporting event, a conference, a social event, a business event, and the like. In some embodiments, the location information describes location coordinates, and each received candidate personal profile is received from an electronic device located within a specified distance from the location coordinates described by the location information. - In the example embodiment, the match is performed by using at least one matching algorithm. In the example embodiment, the match is performed by the
electronic device 100. In some embodiments, the match can be performed by another device or data processing system. - In the example embodiment, the matching algorithm includes at least one of a heuristic match, a keyword match, a value match, an image match, a statistical match, a social match, and an audio match. In the example embodiment, the match is performed by using multiple, different matching algorithms, each matching algorithm for matching a particular type of profile data included in the personal profile and the at least one candidate personal profile. In the example embodiment, the match is performed by using big data analytics.
- In the example embodiment, the match includes at least one of a social match, a romantic match, a business match, a job seeker and prospective employer match, a buyer and seller match, and a service provider and client match.
-
FIG. 2 is a detailed block diagram depicting the internal architecture of thedevice 100 ofFIG. 1 according to an example embodiment. - The
bus 201 interfaces with a one ormore processors 202, a random access memory (RAM) 203, a read only memory (ROM) 204, a computer-readable storage medium 205, animage capture device 206, adisplay device 207, a user input device 208, anetwork device 209, amicrophone 210, aspeaker 211, a GPS device (not shown), a proximity sensor (not shown), a motion sensor (not shown), an accelerometer (not shown), and a gyroscope (not shown). - The one or
more processors 202 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like. - In the example embodiment, the one or
more processors 202 and the random access memory (RAM) 203 form aprocessing unit 220. In some embodiments, the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions. In some embodiments, the processing unit is an ASIC (Application-Specific Integrated Circuit). In some embodiments, the processing unit is a SoC (System-on-Chip). - User input device 208 receives scanned fingerprint data from
fingerprint scanner 102, and receives user input fromtouch screen display 101.Display device 207 controls display oftouch screen display 101. - The
network device 209 provides one or more wired or wireless interfaces for exchanging data and commands between thedevice 100 and other devices. Such wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like. - Machine-executable instructions in software programs and modules (such as an
operating system 212,application programs 213, and device drivers 214) are loaded into the memory 203 (of the processing unit 220) from the computer-readable storage medium 205, theROM 204 or any other storage location. During execution of these software programs and modules, the respective machine-executable instructions are accessed by the CPU 202 (of the processing unit 220) via thebus 201, and then executed by theCPU 202. Data used by the software programs and modules are also stored in thememory 203, and such data is accessed by theCPU 202 during execution of the machine-executable instructions of the software programs and modules. - The computer-
readable storage medium 205 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like. The computer-readable storage medium 205 includes anoperating system 212, thesoftware programs 213,device drivers 214, aprofile module 215, amatching module 216, afingerprint module 217, and profiles 218. - In the example embodiment, the
processing unit 220 loads machine-executable instructions of theprofile module 215 and executes the instructions to acquire a personal profile for a person identified by a unique identifier received at theelectronic device 100. In the example embodiment, the unique identifier of the person is a fingerprint received via thefingerprint scanner 102 and the user input device 208. Thefingerprint scanner 102 is controlled by machine-readable instructions of thefingerprint module 217. - The personal profile is a profile generated by applying big data analytics to personal data collected for the person identified by the unique identifier. In the example embodiment, the personal profile is generated by a data processing system (not shown). In the example embodiment, processing
unit 220 acquires the personal profile by accessing the profile from storedprofiles 218 in response to receipt of the unique identifier. Alternatively, theprocessing unit 220 acquires the personal profile by accessing a remotely stored profile via thenetwork device 209, in response to receipt of the unique identifier. - Responsive to reception of at least one candidate profile (e.g., a personal profile of at least one candidate person or a target personal profile of a marketer) via the
network device 209, theprocessing unit 220 loads machine-executable instructions of thematching module 216 and executes the instructions to perform a match between the personal profile and the at least one candidate profile. In the example embodiment, the match is performed by comparing keywords of the personal profile with one or more keywords of the candidate profile. Theprocessing unit 220 controls thedisplay device 207 to display at least one user-perceivable indicator that indicates a result of the match ontouch screen display 101. -
FIG. 3 is a flow diagram for explaining processing performed by theelectronic device 100 ofFIG. 1 according to an example embodiment. - The following is an example of a matching scenario performed by the
electronic device 100. A user ofdevice 100 posts an updated resume on a job searching web-site, and the resume indicates that the user ofdevice 100 is a software developer. The data processing system (not shown) collects the resume of the user ofdevice 100 and uses it, along with other personal data, to generate a personal profile for the user ofdevice 100. The personal profile indicates, for example, that the user is a software engineer seeking employment at a software company. - Responsive to the user of
device 100 scanning their finger on thefingerprint scanner 102 ofdevice 100, at 301, theelectronic device 100 is controlled to acquire the personal profile for the user, who is identified by the scanned fingerprint data received at theelectronic device 100 via thefingerprint scanner 102. - At 302, a determination is made as to whether a candidate profile has been received. In the example embodiment, the user of
electronic device 100 bumps thedevice 100 against the electronic device of a candidate person to exchange profiles. If a candidate profile has not been received (“NO” at 302) processing returns to 302. If a candidate profile has been received (“YES” at 302) processing proceeds to 303. At 303, theelectronic device 100 is controlled to perform a match between the personal profile of the user and the at least one candidate personal profile. The candidate personal profile is a profile that has been generated the same way as with the user profile ofdevice 100 by using big analytics. - For example, if a candidate has a social network profile indicating that they are in the hiring department at a software company, and the software company's web site has a job posting for a software engineer, the data processing system (not shown) collects the candidate's social network profile data and the software company's job listing, and uses this collected data, along with other personal data, to generate a personal profile for the candidate. The candidate profile indicates, for example, that the candidate is a hiring manager seeking to hire a software engineer for the software company. If the user of
device 100 and the candidate meet at a software developer conference and bump devices, then their profiles will be matched. Since, in this example, the personal profile of the user ofdevice 100 indicates that the user is a software engineer seeking employment at a software company and the candidate profile indicates that the candidate is a hiring manager seeking to hire a software engineer for the software company, the result of the match will indicate that a match has been found between the user ofdevice 100 and the candidate. - If a match has been identified (“YES” at 303), then processing proceeds to 304 and the
processing unit 220 executes instructions of thematching module 216 to control thedisplay device 207 to display at least one user-perceivable indicator that indicates a result of the match ontouch screen display 101. - If a match has not been identified (“NO” at 303), then processing returns to 302.
-
FIG. 4 is a diagram depicting a profile matching system 400 that includes theelectronic device 100 and anelectronic device 401, aprofile generation system 410, amarketing server 402, aphoto sharing server 403, asocial media server 404, and a personaldata processing server 405. Theprofile generation system 410 includes a photoprofile generation device 406, a user-generated contentprofile generation device 407, a personal dataprofile generation device 408, and aprofile repository 409. -
FIG. 5 is a detailed block diagram depicting the internal architecture of the user-generated contentprofile generation device 407.FIG. 6 is a detailed block diagram depicting the internal architecture of the personal dataprofile generation device 408.FIG. 7 is a detailed block diagram depicting the internal architecture of theprofile repository 409.FIG. 8 is a detailed block diagram depicting the internal architecture of the photoprofile generation device 406.FIG. 9 is a detailed block diagram depicting the internal architecture of themarketing server 402. - Reverting to
FIG. 4 , theelectronic device 100 is constructed to communicatively couple with anotherelectronic device 401, which is similar to theelectronic device 100. More specifically, theelectronic device 401 has an architecture that is similar to the architecture described above with respect toFIG. 2 , and the electronic device is constructed to perform the process described above with respect toFIG. 3 . - The
electronic device 401 is constructed to communicatively couple with theelectronic device 100 and theprofile generation system 410. - The
electronic device 100 is also constructed to communicatively with themarketing server 402, theprofile generation system 410, thephoto sharing server 403, thesocial media server 404, and the personaldata processing server 405. - In some embodiments, during communication between the
electronic device 100 and theprofile generation system 410, theelectronic device 100 is not communicatively coupled with one or more of thephoto sharing server 403, thesocial media server 404, the personaldata processing server 405, themarketing server 402, and theelectronic device 401. - In some embodiments, during communication between the
electronic device 100 and themarketing server 402, theelectronic device 100 is not communicatively coupled with one or more of thephoto sharing server 403, thesocial media server 404, the personaldata processing server 405, theprofile generation system 410, and theelectronic device 401. - In some embodiments, during communication between the
electronic device 100 and theelectronic device 401, theelectronic device 100 is not communicatively coupled with one or more of thephoto sharing server 403, thesocial media server 404, the personaldata processing server 405, theprofile generation system 410, and themarketing server 402. - In some embodiments, during communication between the
electronic device 100 and thephoto sharing server 403, theelectronic device 100 is not communicatively coupled with one or more of theelectronic device 401, thesocial media server 404, the personaldata processing server 405, theprofile generation system 410, and themarketing server 402. - In some embodiments, during communication between the
electronic device 100 and thesocial media server 404, theelectronic device 100 is not communicatively coupled with one or more of theelectronic device 401, thephoto sharing server 403, the personaldata processing server 405, theprofile generation system 410, and themarketing server 402. - In some embodiments, during communication between the
electronic device 100 and the personaldata processing server 405, theelectronic device 100 is not communicatively coupled with one or more of theelectronic device 401, thephoto sharing server 403, thesocial media server 404, theprofile generation system 410, and themarketing server 402 - Turning to the
profile generation system 410, the photoprofile generation device 406, the user-generated contentprofile generation device 407, and the personal dataprofile generation device 408 are constructed to communicatively couple with thephoto sharing server 403, thesocial media server 404, and the personaldata processing server 405, respectively, by using a corresponding application programming interface (API). - The photo
profile generation device 406, the user-generated contentprofile generation device 407, and the personal dataprofile generation device 408 are each communicatively coupled with theprofile repository 409. - In some embodiments, the
profile generation system 410 includes one or more of the photoprofile generation device 406, the user-generated contentprofile generation device 407, and the personal dataprofile generation device 408. In some embodiments, theelectronic devices - In some embodiments, the
marketing server 402 includes a profile matching system similar to the profile matching system 400. - The personal
data processing server 405 is constructed to automatically generate personal data. In the example embodiment, personal data includes, for example, one or more of purchase data, user profile data, user preferences data, user recommendation data, customer review data, media consumption data, web browsing data, tax filing data, social network data, legal data, financial data, calendar data, e-mail data, Twitter data, geo-location data, travel history, photo data, medical data, criminal record data, marriage records, birth records, wedding registry data, DNA data, employment data, and the like. - Turning to the architectures of the user-generated content
profile generation device 407, the personal dataprofile generation device 408, theprofile repository 409, the photoprofile generation device 406, and themarketing server 402,FIG. 5 is a detailed block diagram depicting the internal architecture of the user-generated contentprofile generation device 407. - The
bus 501 interfaces with a one ormore processors 502, a random access memory (RAM) 503, a read only memory (ROM) 504, a computer-readable storage medium 505, adisplay device 507, a user input device 508, and anetwork device 509. - The one or
more processors 502 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like. - In the example embodiment, the one or
more processors 502 and the random access memory (RAM) 503 form aprocessing unit 520. In some embodiments, the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions. In some embodiments, the processing unit is an ASIC (Application-Specific Integrated Circuit). In some embodiments, the processing unit is a SoC (System-on-Chip). - The
network device 509 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated contentprofile generation device 407 and other devices. Such wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like. - Machine-executable instructions in software programs and modules (such as an
operating system 512, application programs 513, and device drivers 514) are loaded into the memory 503 (of the processing unit 520) from the computer-readable storage medium 505, theROM 504 or any other storage location. During execution of these software programs, the respective machine-executable instructions are accessed by the CPU 502 (of the processing unit 520) via thebus 501, and then executed by theCPU 502. Data used by the software programs are also stored in thememory 503, and such data is accessed by theCPU 502 during execution of the machine-executable instructions of the software programs and modules. - The computer-
readable storage medium 505 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like. The computer-readable storage medium 505 includes anoperating system 512, the software programs 513,device drivers 514, a user-generated contentprofile generation module 515, and user-generatedcontent 516. - In the example embodiment, the
processing unit 520 loads machine-executable instructions of the user-generated contentprofile generation module 515 and executes the instructions to collect user-generatedcontent 516 uploaded by a person (that is identified by a unique identifier) to the social-media server 404. Theprocessing unit 520 collects the user-generatedcontent 516 by using an application programming interface (API) of the social-media server 404. Executing the instructions of the user-generated contentprofile generation module 515, theprocessing unit 520 generates a personal profile of the person by applying one or more of object recognition, voice recognition, character recognition, and textual analysis processing to the user-generatedcontent 516 to generate one or more keywords, the generated personal profile including the one or more keywords. Executing the instructions of the user-generated contentprofile generation module 515, theprocessing unit 520 stores the generated personal profile in a storage medium (705 ofFIG. 7 ) of theprofile repository 409. -
FIG. 6 is a detailed block diagram depicting the internal architecture of the personal dataprofile generation device 408. - The
bus 601 interfaces with a one ormore processors 602, a random access memory (RAM) 603, a read only memory (ROM) 604, a computer-readable storage medium 605, adisplay device 607, a user input device 608, and anetwork device 609. - The one or
more processors 602 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like. - In the example embodiment, the one or
more processors 602 and the random access memory (RAM) 603 form aprocessing unit 620. In some embodiments, the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions. In some embodiments, the processing unit is an ASIC (Application-Specific Integrated Circuit). In some embodiments, the processing unit is a SoC (System-on-Chip). - The
network device 609 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated contentprofile generation device 407 and other devices. Such wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like. - Machine-executable instructions in software programs and modules (such as an
operating system 612, application programs 613, and device drivers 614) are loaded into the memory 603 (of the processing unit 620) from the computer-readable storage medium 605, theROM 604 or any other storage location. During execution of these software programs, the respective machine-executable instructions are accessed by the CPU 602 (of the processing unit 620) via thebus 601, and then executed by theCPU 602. Data used by the software programs are also stored in thememory 603, and such data is accessed by theCPU 602 during execution of the machine-executable instructions of the software programs and modules. - The computer-
readable storage medium 605 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like. The computer-readable storage medium 605 includes anoperating system 612, the software programs 613,device drivers 614, a personal dataprofile generation module 615, andpersonal data 616. - In the example embodiment, the
processing unit 620 loads machine-executable instructions of the personal dataprofile generation module 615 and executes the instructions to collect personal data 616 (for person that is identified by a unique identifier) that is generated by the personaldata processing server 405. Theprocessing unit 620 collects thepersonal data 616 by using an application programming interface (API) of the personaldata processing server 405. Executing the instructions of the personal dataprofile generation module 615, theprocessing unit 620 generate a personal profile of the person by applying big data analytics to the collected personal data to generate one or more keywords to thepersonal data 616 to generate one or more keywords, the generated personal profile including the one or more keywords. Executing the instructions of the personal dataprofile generation module 615, theprocessing unit 620 stores the generated personal profile in a storage medium (705 ofFIG. 7 ) of theprofile repository 409. -
FIG. 7 is a detailed block diagram depicting the internal architecture of theprofile repository 409. - The
bus 701 interfaces with a one ormore processors 702, a random access memory (RAM) 703, a read only memory (ROM) 704, a computer-readable storage medium 705, adisplay device 707, a user input device 708, and anetwork device 709. - The one or
more processors 702 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like. - In the example embodiment, the one or
more processors 702 and the random access memory (RAM) 703 form aprocessing unit 720. In some embodiments, the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions. In some embodiments, the processing unit is an ASIC (Application-Specific Integrated Circuit). In some embodiments, the processing unit is a SoC (System-on-Chip). - The
network device 709 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated contentprofile generation device 407 and other devices. Such wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like. - Machine-executable instructions in software programs and modules (such as an
operating system 712, application programs 713, and device drivers 714) are loaded into the memory 703 (of the processing unit 720) from the computer-readable storage medium 705, theROM 704 or any other storage location. During execution of these software programs, the respective machine-executable instructions are accessed by the CPU 702 (of the processing unit 720) via thebus 701, and then executed by theCPU 702. Data used by the software programs are also stored in thememory 703, and such data is accessed by theCPU 702 during execution of the machine-executable instructions of the software programs and modules. - The computer-
readable storage medium 705 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like. The computer-readable storage medium 705 includes anoperating system 712, the software programs 713,device drivers 714, anauthentication module 715 and aprofile data store 716. - In the example embodiment, the
processing unit 720 loads machine-executable instructions of theauthentication module 715 and executes the instructions to authenticate a unique identifier provided by an electronic device (e.g., theelectronic device 100 or 401) that is requesting a personal profile for a person identified by the unique identifier. Responsive to a determination that the unique identifier has been authenticated, theprocessing unit 720 executes loads and executes instructions of theprofile data store 716 to access one or more profiles that correspond to the authenticated unique identifier and to provide the one or more profiles to the electronic device that has requested the personal profile (e.g., theelectronic device 100 or 401). - In the example embodiment, the
processing unit 720 executes loads and executes instructions of theprofile data store 716 to store one or more personal profiles received from one or more of the photoprofile generation device 406, the user-generated contentprofile generation device 407, and the personal dataprofile generation device 408 in thestorage medium 705 in association with a corresponding unique identifier. - In some embodiments, the
processing unit 720 executes loads and executes instructions of theprofile data store 716 to combine profiles associated with the same unique identifier. For example, theprocessing unit 720 can combine a profile generated for a person by each of photoprofile generation device 406, the user-generated contentprofile generation device 407, and the personal dataprofile generation device 408 into a single profile for the person, the profile being associated with a single unique identifier. -
FIG. 8 is a detailed block diagram depicting the internal architecture of the photoprofile generation device 406. - The
bus 801 interfaces with a one ormore processors 802, a random access memory (RAM) 803, a read only memory (ROM) 804, a computer-readable storage medium 805, adisplay device 807, a user input device 808, and anetwork device 809. - The one or
more processors 802 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like. - In the example embodiment, the one or
more processors 802 and the random access memory (RAM) 803 form aprocessing unit 820. In some embodiments, the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions. In some embodiments, the processing unit is an ASIC (Application-Specific Integrated Circuit). In some embodiments, the processing unit is a SoC (System-on-Chip). - The
network device 809 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated contentprofile generation device 407 and other devices. Such wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like. - Machine-executable instructions in software programs and modules (such as an
operating system 812,application programs 813, and device drivers 814) are loaded into the memory 803 (of the processing unit 820) from the computer-readable storage medium 805, theROM 804 or any other storage location. During execution of these software programs, the respective machine-executable instructions are accessed by the CPU 802 (of the processing unit 820) via thebus 801, and then executed by theCPU 802. Data used by the software programs are also stored in thememory 803, and such data is accessed by theCPU 802 during execution of the machine-executable instructions of the software programs and modules. - The computer-
readable storage medium 805 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like. The computer-readable storage medium 805 includes anoperating system 812, thesoftware programs 813,device drivers 814, a photoprofile generation module 815, andphotos 816. - In the example embodiment, the
processing unit 820 loads machine-executable instructions of the photoprofile generation module 815 and executes the instructions to collectphotos 816 uploaded by a person (that is identified by a unique identifier) to thephoto sharing server 403. Theprocessing unit 820 collects thephotos 816 by using an application programming interface (API) of thephoto sharing server 403. Executing the instructions of the photoprofile generation module 815, theprocessing unit 820 generates a personal profile of the person by applying one or more of object recognition and character recognition to thephotos 816 to generate one or more keywords, the generated personal profile including the one or more keywords. Executing the instructions of the photoprofile generation module 815, theprocessing unit 820 stores the generated personal profile in a storage medium (705 ofFIG. 7 ) of theprofile repository 409. -
FIG. 9 is a detailed block diagram depicting the internal architecture of themarketing server 402. - The
bus 901 interfaces with a one ormore processors 902, a random access memory (RAM) 903, a read only memory (ROM) 904, a computer-readable storage medium 905, adisplay device 907, a user input device 908, and anetwork device 909. - The one or
more processors 902 may take many forms, such as, but not limited to: a central processing unit (CPU); a multi-processor unit (MPU); an ARM processor; or the like. - In the example embodiment, the one or
more processors 902 and the random access memory (RAM) 903 form aprocessing unit 920. In some embodiments, the processing unit includes one or more processors communicatively coupled to one or more of a RAM, ROM, and machine-readable storage medium; the one or more processors of the processing unit receive instructions stored by the one or more of a RAM, ROM, and machine-readable storage medium via a bus; and the one or more processors execute the received instructions. In some embodiments, the processing unit is an ASIC (Application-Specific Integrated Circuit). In some embodiments, the processing unit is a SoC (System-on-Chip). - The
network device 909 provides one or more wired or wireless interfaces for exchanging data and commands between the user-generated contentprofile generation device 407 and other devices. Such wired and wireless interfaces include, for example, a Universal Serial Bus (USB) interface, blue tooth interface, Wi-Fi interface, Ethernet interface, Near Field Communication (NFC) interface, and the like. - Machine-executable instructions in software programs and modules (such as an
operating system 912, application programs 913, and device drivers 914) are loaded into the memory 903 (of the processing unit 920) from the computer-readable storage medium 905, theROM 904 or any other storage location. During execution of these software programs, the respective machine-executable instructions are accessed by the CPU 902 (of the processing unit 920) via thebus 901, and then executed by theCPU 902. Data used by the software programs are also stored in thememory 903, and such data is accessed by theCPU 902 during execution of the machine-executable instructions of the software programs and modules. - The computer-
readable storage medium 905 is one of a (or a combination of two or more of) a hard drive, a flash drive, a DVD, a CD, a flash storage, a solid state drive, a ROM, an EEPROM, and the like. The computer-readable storage medium 905 includes anoperating system 912, the software programs 913,device drivers 914, a targetprofile management module 915, targetpersonal profiles 916, andmarketer information 917. - In the example embodiment, the
processing unit 920 loads machine-executable instructions of the targetprofile management module 915 and executes the instructions to provide an electronic device (e.g., theelectronic device 100 ofFIG. 1 ) with one or more targetpersonal profiles 916. - In some embodiments, executing the instructions of the target
profile management module 915, the marketingserver processing unit 920 provides at least one targetpersonal profile 916 to an electronic device (e.g., the electronic device 100) responsive to a request received from the electronic device. - In some embodiments, the
marketing server 402 receives location information for one or more electronic devices, and executing the instructions of the targetprofile management module 915, the marketingserver processing unit 920 provides targetpersonal profiles 916 to electronic devices (e.g., the electronic device 100) based on the received location information. For example, a retail location can contain a retail electronic device that is associated with the marketing server, the retail electronic device can receive location information of electronic devices, and themarketing server 402 can provide one or more target profiles to one or more electronic devices (via the retail electronic device) based on proximity of the electronic devices to the retail electronic device. - In some embodiments, executing the instructions of the target
profile management module 915, the marketingserver processing unit 920 provides at least one targetpersonal profile 916 to an electronic device (e.g., the electronic device 100) based on proximity of the electronic device to an electronic device associated with themarketing server 402. - In some embodiments, executing the instructions of the target
profile management module 915, the marketingserver processing unit 920 provides at least one targetpersonal profile 916 to an electronic device (e.g., the electronic device 100) based on physical contact between the electronic device and an electronic device associated with themarketing server 402. - In some embodiments, location information identifying a location of an electronic device associated with the
marketing server 402 is determined, executing the instructions of the targetprofile management module 915, the marketingserver processing unit 920 provides at least one targetpersonal profile 916 to an electronic device (e.g., the electronic device 100) having a location within an area determined by the determined location information. In some embodiments, the location information describes a place, and the marketingserver processing unit 920 provides at least one targetpersonal profile 916 to an electronic device (e.g., the electronic device 100) located in the place described by the location information. In some embodiments, the location information describes an event, and the marketingserver processing unit 920 provides at least one targetpersonal profile 916 to an electronic device (e.g., the electronic device 100) located at the event described by the location information. In some embodiments, the location information describes location coordinates, and the marketingserver processing unit 920 provides at least one targetpersonal profile 916 to an electronic device (e.g., the electronic device 100) located within a specified distance from the location coordinates described by the location information. - In the example embodiment, the
processing unit 920 loads machine-executable instructions of the targetprofile management module 915 and executes the instructions to provide an electronic device (e.g., theelectronic device 100 ofFIG. 1 ) withmarketer information 917 responsive. In the example embodiment, executing the instructions of the targetprofile management module 915, the marketingserver processing unit 920 provides the electronic device withmarketer information 917 responsive to a request for marketer information from the electronic device, the request indicting that the electronicdevice processing unit 220 has executed the instructions of thematching module 216 and has determined a match between a target personal profile 916 (received by the electronic device from the marketing server 402) and a personal profile for a user that is associated with a unique identifier (e.g., a scanned fingerprint data received at theelectronic device 100 via the fingerprint scanner 102) received by the electronic device. - In some embodiments, executing the instructions of the target
profile management module 915, the marketingserver processing unit 920 provides the electronic device withmarketer information 917 responsive to a request for marketer information from the electronic device, the request including a personal profile for a user that is associated with a unique identifier (e.g., a scanned fingerprint data received at theelectronic device 100 via the fingerprint scanner 102) received by the electronic device. The marketingserver processing unit 920 determines a match between a targetpersonal profile 916 and the received personal profile, and responsive to a determination of a match, the marketingserver processing unit 920 provides the electronic device withmarketer information 917. - In the example embodiment, the
marketer information 917 includes at least one of advertising information and reward information. In the example embodiment, the reward information includes information related to at least one of a coupon, a prize, a credit, a monetary reward, information for a marketing promotion, and the like. - Responsive to the
marketer information 917, the electronic device displays a visual representation of the received marketer information. -
FIG. 10 is a flow diagram for explaining processing performed by theelectronic device 100 ofFIG. 1 according to an example embodiment. - Responsive to the user of
device 100 scanning their finger on thefingerprint scanner 102 ofdevice 100, at 1001, theelectronic device 100 is controlled to acquire the personal profile for the user (from the profile generation system 400), who is identified by the scanned fingerprint data received at theelectronic device 100 via thefingerprint scanner 102. - At 1002, the electronic
device processing unit 220 of the electronic device determines whether theelectronic device 100 has received a target personal profile from themarketing server 402, as described above with respect toFIG. 9 . If a target personal profile has not been received (“NO” at 1002) processing returns to 1002. If a target personal profile has been received (“YES” at 1002) processing proceeds to 1003. At 1003, theelectronic device 100 is controlled to perform a match between the personal profile of the user and the target personal profile. The target personal profile is a profile that specifies a marketer's target consumer. - If a match has been identified (“YES” at 1003), then processing proceeds to 1004 and the
processing unit 220 executes instructions of thematching module 216 to provide themarketing server 402 with a request for marketer information from theelectronic device 100, the request indicting that the electronicdevice processing unit 220 has executed the instructions of thematching module 216 and has determined a match between the target personal profile 916 (received by the electronic device from the marketing server 402) and the personal profile received by the electronic device at the process S1001. Theprocessing unit 220 executes instructions of thematching module 216 to control thedisplay device 207 to display a visual representation of the received marketer information on thetouch screen display 101 of theelectronic device 100. - If a match has not been identified (“NO” at 1003), then processing returns to 1002.
- This disclosure has provided a detailed description with respect to particular representative embodiments. It is understood that the scope of the appended claims is not limited to the above-described embodiments and that various changes and modifications may be made without departing from the scope of the claims.
Claims (1)
1. A method comprising:
for each of a plurality of users, a trusted third party server generating an anonymous user-generated content profile for the user by: collecting user-generated content for the user and generating a plurality of keywords from the collected user-generated content;
the trusted third party server storing each anonymous user-generated content profile in association with the respective user;
a first user profile module included in an electronic device providing a request for an anonymous user-generated content profile of a user of the electronic device to the trusted third party server;
the trusted third party server accessing the anonymous user-generated content profile stored in association with the user of the request provided by the first user profile module and providing the accessed anonymous user-generated content profile to the first user profile module;
the first user profile module receiving the anonymous user-generated content profile from the trusted third party server;
a marketing server providing a target personal profile to a first user matching module included in the electronic device;
the first user matching module receiving the target personal profile from the marketing server, wherein the target personal profile specifies a target consumer of a marketer;
the first user matching module determining a match between the received anonymous user-generated content profile and the target personal profile;
responsive to the first user matching module determining a match between the anonymous user-generated content profile and the target personal profile, the first user matching module providing the marketing server with a request for marketer information, the request indicting that the first user matching module has determined the match between the target personal profile and the anonymous user-generated content profile provided by the trusted third party server;
the marketing server providing the marketer information to the first user matching module as a response to the request indicting that the first user matching module has determined the match between the target personal profile and the anonymous user-generated content profile;
the first user matching module receiving the marketer information as a response to the request for marketer information, wherein the marketer information includes at least one of advertising information and reward information; and
responsive to the marketer information, the first user matching module controlling a display device included in the electronic device of the user to display a visual representation of the marketer information.
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US16/423,160 US20190279255A1 (en) | 2013-10-21 | 2019-05-28 | Device, method and non-transitory computer readable storage medium for determining a match between profiles |
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US201361893857P | 2013-10-21 | 2013-10-21 | |
US14/520,302 US10332154B2 (en) | 2013-10-21 | 2014-10-21 | Device, method and non-transitory computer readable storage medium for determining a match between profiles |
US16/423,160 US20190279255A1 (en) | 2013-10-21 | 2019-05-28 | Device, method and non-transitory computer readable storage medium for determining a match between profiles |
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US10489566B2 (en) * | 2017-03-13 | 2019-11-26 | Microsoft Technology Licensing, Llc | Automated user profile generation and authentication |
US11055371B2 (en) * | 2017-12-06 | 2021-07-06 | Bank Of America Corporation | Using smart data filters to create multi-threaded profiles |
US20220329554A1 (en) * | 2021-04-13 | 2022-10-13 | At&T Intellectual Property I, L.P. | Methods, systems and devices for blocking messages generated from events based on keywords |
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US7065550B2 (en) * | 2001-02-14 | 2006-06-20 | International Business Machines Corporation | Information provision over a network based on a user's profile |
US11283885B2 (en) * | 2004-10-19 | 2022-03-22 | Verizon Patent And Licensing Inc. | System and method for location based matching and promotion |
US20110276570A1 (en) * | 2009-01-29 | 2011-11-10 | Telefonaktiebolaget Lm Ericsson (Publ) | Methods, Apparatuses, and Computer Program Products for Adding Profile Data |
US20120046995A1 (en) * | 2009-04-29 | 2012-02-23 | Waldeck Technology, Llc | Anonymous crowd comparison |
US20130166643A1 (en) * | 2011-12-22 | 2013-06-27 | Joseph Essas | Systems and Methods for Online Ad Hoc Matching |
US20130332848A1 (en) * | 2012-06-06 | 2013-12-12 | Wilfred Lam | Creating new connections on social networks using gestures |
US9881011B2 (en) * | 2012-11-29 | 2018-01-30 | Ricoh Company, Ltd. | System and method for generating user profiles for human resources |
US20140288999A1 (en) * | 2013-03-12 | 2014-09-25 | Correlor Technologies Ltd | Social character recognition (scr) system |
DE102013009958A1 (en) * | 2013-06-14 | 2014-12-18 | Sogidia AG | A social networking system and method of exercising it using a computing device that correlates to a user profile |
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