Patent Publication Number: US-2019191206-A1

Title: Method and system of generating a user influenced recommendation list

Description:
FIELD 
     The invention relates generally to a method and system of generating a list of recommended content, more particularly, a method and system of generating a user influenced recommendation list. 
     BACKGROUND 
     The statements in this section merely provide background information related to the present disclosure and may or may not constitute prior art. 
     Recommendation lists of contents for a specific content user are commonly generated by service providers for the recommendation of consumer contents such as songs, movies, consumer products, restaurants, etc. Service providers use recommendation engines to generate recommendation lists based on: a particular artist or genre, when the contents were last accessed, the frequency of access to the contents, and/or random selection of previously accessed contents. Service providers also use recommendation engines based on proprietary methods for generating recommendation lists based on a user&#39;s historical usage of the contents. 
     The conventional methods for generating a recommendation list does not take into account the preferences of multiple content users. The qualities that make a recommendation list interesting to a particular user may not be interesting for another particular user. This is especially true in media content, such as music content, shared in a vehicle between two or more passengers. Thus, while current recommendation engines achieve their intended purpose, there is a need for a new and improved method and system for generating a preference list based on the preferences of multiple users. 
     SUMMARY 
     According to several aspects, a method of generating a user influenced recommendation list is disclosed herein. The method includes the steps of coupling a first user device and a second user device to a recommendation engine; uploading a first preference list of contents from the first user device to the recommendation engine; uploading a second preference list of contents from the second user device to the recommendation engine; and generating a third preference list of recommended contents by analyzing a user selected ratio of the contents from the first and second preference lists. The contents from the first and second preference lists may include, but not limited to media files such as music and movies; navigation data; favorite lists including favorite places, restaurants, artist; and recommendation lists. 
     In an additional aspect of the present disclosure, the user selected ratio of contents from the first and second preference list is selected by the user by sliding a lever along a continuum of ratios. 
     In another aspect of the present disclosure, the continuum is displayed on a Graphic User Interface (GUI), and the lever is a graphical pointer slideable between a first end of the continuum and a second end of the continuum. 
     In another aspect of the present disclosure, a first end of the continuum represents 100 percent of contents from the first preference list and 0 percent of contents form the second preference list, and a second end of the continuum represents 0 percent of content from the first preference list and 100 percent of contents from the second preference list. 
     In another aspect of the present disclosure, the first, second, and third preference lists are displayed on the GUI. The contents in each of the first, second, and third preference lists are selectable by the user. 
     In another aspect of the present disclosure, the step of generating the third preference list of recommended contents further includes combining the first and second preference list, and removing redundant contents. 
     In another aspect of the present disclosure, the step of generating the third preference list of recommended contents further includes generating at least one recommended content. 
     In another aspect of the present disclosure, the step of generating the third preference list of recommended contents further includes adding the least one recommended content into the combined first and second preference lists. 
     In another aspect of the present disclosure, the step of generating the third preference list of recommended contents further includes, filtering the combined contents into genres; identifying a first group of genres having contents originated solely from the first preference list; identifying a second group of genres having contents originated solely from the second preference list; identifying a third group of genres having contents originated from both the first and second preference list, and the recommended content; and displaying the combined preference list in a spectrum, wherein the first group of genres is displayed adjacent one end of the spectrum, the second group of genres is displayed adjacent the opposite end of the spectrum, and the third group of genres is displayed adjacent the center of the spectrum. 
     In another aspect of the present disclosure, the method further includes the steps of determining whether the first user device and second user device are both within a predetermined zone, and enabling user access to a Human Machine Interface (HMI) located within the predetermined zone. The HMI is configured to enable the user to select the ratio of the contents from the first and second preference list. 
     According to several aspects, a method of generating a user influenced recommendation list displayable on a graphic user interface (GUI) in a vehicle is disclosed. The method includes the steps of detecting a first user device and detecting a second user device within a predetermined zone within a compartment of the vehicle; coupling the first user device and the second user device to a recommendation engine; uploading a first preference list of contents from the first user device and a second preference list of contents from the second user device to the recommendation engine; selecting a ratio of contents from the first preference list and second preference list; generating a third preference list of recommended contents, by the recommendation engine, by analyzing the selected ratio of contents from the first and second preference lists; and displaying the third preference list on the GUI located within the predetermined zone. 
     In an additional aspect of the present disclosure, the recommendation engine is located remote from the vehicle. 
     In another aspect of the present disclosure, the GUI is located on one of the first user or second user devices. 
     In another aspect of the present disclosure, the ratio input of media contents from the first and second preference lists is selectable by a user by sliding a lever along a continuum on the GUI. 
     In another aspect of the present disclosure, the step of analyzing the selected ratio of contents includes identifying contents that are within a common genre in the first and second preference lists. The method further includes the step of generating the third preference list based on the common genre. 
     According to several aspects, a system for generating a user influenced recommendation list is disclosed. The system includes a receiver configured to receive an upload of a plurality of preference lists from a plurality of user devices; a human machine interface (HMI) configured to receive a user selected ratio of the contents from the first and second preference lists; and a recommendation engine in communication with the receiver and HMI. The recommendation engine is configured to generate a third preference list of recommended contents by analyzing the user selected ratio of the contents from the first and second preference lists. 
     In an additional aspect of the present disclosure, the HMI is a graphic user interface (GUI) configured to display a continuum having a pointer slideable between a first end of the continuum and a second end of the continuum. The first end represents a 100 percent ratio of contents from a first user device and the second end represents a 100 percent ratio of contents from the second user device. 
     In another aspect of the present disclosure, the recommendation engine is further configured to determine whether the first user device and the second user device are both within a predetermined zone within a vehicle; and enable user access to the GUI if the first user device and the second user device are both within the predetermine zone. 
     In another aspect of the present disclosure, the GUI is located on one of the user devices. 
     In another aspect of the present disclosure, the recommendation engine is located remote from the vehicle. 
     Further areas of applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way. 
         FIG. 1  is a schematic illustration of a system for generating a user influenced recommendation list, according to an exemplary embodiment; 
         FIG. 2  is an illustration of a top view of a passenger compartment of a vehicle having the system of generating a user influenced recommendation list of  FIG. 1 , according to an exemplary embodiment; 
         FIG. 3  is a block flow diagram showing a method of generating a user influenced recommendation list, according to an exemplary embodiment; 
         FIG. 4  is an illustration of a user influenced recommendation list generated by the system of  FIG. 1 , according to an exemplary embodiment; and 
         FIG. 5  is an illustration of a control panel display for generating a user influenced recommendation list, according to an exemplary embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses. 
       FIG. 1  shows a schematic of a system  100  for generating a user influenced recommendation list for a vehicle. The system  100  includes occupant detection sensors  102 , near field communication (NFC) receivers/transmitters  104 , vehicle-to-everything (V2X) receivers/transmitters  106 , and a human machine interface (HMI)  108 , all of which are in electronic communications with a recommendation engine  110 . 
     The occupant detection sensors  102  are configured to detect whether there is an occupant in the vehicle. The occupant detection sensors  102  may include infrared sensors, motion sensors, range sensors, pressure sensors, image sensors, or pressure sensors. The occupant sensors  102  are placed in strategic locations within the passenger compartment of the vehicle such that the location of a detected occupant can be determined. For example, a pressure sensor or motion sensor may be placed adjacent a seating area to detect whether that particular seating area is occupied. Each of the occupant detection sensors  102  may include dedicated application-specific integrated circuit (ASIC) for detecting and locating an occupant within the vehicle. Alternatively, the occupant detection sensors  102  may send a signal containing information gathered by the occupant detection sensors  102  to a vehicle controller (not shown) for processing to detect and locate the occupant. 
     The NFC receiver/transmitters  104  are configured to communicate with personal electronic devices in the possession of the occupants within the vehicle. The personal electronic devices may include smart phones, tablets, computers, key fobs, NFC enable cards, and/or any other electronic devices capable of utilizing NFC. The NFC receivers/transmitters  104  are placed in strategic locations within the vehicle to determine the locations of the electronic devices within the passenger compartment. The NFC receivers/transmitters  104  are further configured to upload user content and/or user preference lists from the personal electronic device to the recommendation engine  110 . 
     The HMI  108  may include mechanical knobs, dials, and/or levers located within the vehicle as part of the infotainment system. The HMI  108  may be that of a display monitor configured to display the preference list uploaded from the individual user devices and/or the recommendation list, also known as a preference list, generated by the recommendation engine  110 . It is preferable that the HMI is a graphic user interface (GUI) configured to allow the users to interact with the recommendation engine  110  through graphical icons and visual indicators. The GUI may be displayed on a touch screen display such as a resistive, capacitive, surface acoustic wave, infrared, and/or optical imaging touchscreen. 
     The recommendation engine  110  may be located on board the vehicle or remote from the vehicle. If the recommendation engine  110  is remote from the vehicle, information obtained by the NFC receiver/transmitters  104  may be communicated to the remote recommendation engine  110  by using the vehicle-to-everything (V2X) receiver/transmitters  106  located on the vehicle. It is understood that that V2X receivers/transmitters  106  include vehicle-to-vehicle (V2V) and vehicle-to-infrastructure communication (V2I) systems. 
     The recommendation engine  110  includes a processor  112  and a memory device  114 . The processor  112  may be any conventional processor, such as commercially available CPUs or other hardware-based processor. The memory device  114  includes a database  116  and stored algorithms  118  for generating a recommendation list based on at least two separate preference lists. The database  116  and algorithms  118  are accessible by the processor  112 . The memory device  114  may be any computing device readable medium such as hard-drives, solid state memory, ROM, RAM, DVD or any other medium that is capable of storing information that is accessible by the processor  112 . 
     Although only one recommendation engine  110  is shown, it is understood that the vehicle may contain multiple recommendation engines  110 . Each of the recommendation engines  110  may include more than one processor and memory, and the plurality of processors and memories do not necessary have to be housed within the respective controllers. Accordingly, references to a recommendation engine, processor, and memory devices include references to a collection of such recommendation engines, processors, and memory devices that may or may not operate in parallel. 
       FIG. 2  is a top view of an exemplary vehicle  200  showing a cutaway view of the passenger compartment  202 . Adjacent a forward section of the passenger compartment  202  is a driver seating area  204  and an adjacent passenger seating area  206 . A third passenger seating area  208  and an adjacent fourth passenger seating area  210  are located immediately behind the driver seating area  204  and the passenger seating area  206 , respectively. The seating areas  204 ,  206 ,  208 ,  210  may each have an occupant detection sensor  102 , such as a pressure sensor  102 , to detect whether the seating areas  204 ,  206 ,  208 ,  210  are occupied. Located adjacent each of the seating areas  204 ,  206 ,  208 ,  210  is a NFC transmitter/receiver  104 . The NFC transmitter/receivers are configured to detect and communicate with an electronic personal device located within the respective seating areas  204 ,  206 ,  208 ,  210 . Provided between adjacent seating areas is a HMI  108 , such as a GUI. 
       FIG. 3  is a block flow diagram of a method for generating a user influenced recommendation list  300 , also known as a user influenced preference list  300 . The method starts at block  302 . In block  304 , a first and second user devices are detected within the passenger compartment of the vehicle. A determination is made as to whether the first user device and second user device are both within a predetermined zone, such as adjacent seating areas. If the first and second user devices are within the same predetermined zone, then the access to a Human Machine Interface (HMI) within the predetermined zone is enabled. 
     In block  306 , the first and second user devices are coupled to a recommendation engine, which may be part of the infotainment system or located remote from the vehicle on a site or cloud server. In block  308 , a first preference list of contents from the first user device and a second preference list of contents from the second user device are uploaded to the recommendation engine. 
     In block  310 , a user selects a ratio of contents from the first and second preference list. The HMI is configured to enable the user to select a ratio of the contents from the first and second preference list. For example, if a ratio of 20/80 is selected, then 20 percent of content is selected from the first preference list and 80 percent of content is selected from the second preference list. The ratio may be selected by sliding a lever along a continuum of ratios. The lever may be an actual hardware lever or a graphical representation of a lever using a graphic user interface (GUI) as part of the infotainment system. The continuum may be displayed on the GUI and the lever may be represented by graphical pointer slideable between a first end of the continuum and a second end of the continuum. 
     In block  312 , the uploaded first and second preference lists of contents are analyzed in accordance with the ratio selected by the user. The contents may be analyzed by first combining the first and second preference lists and removing redundant contents. Then followed by filtering the combined contents into genres, identifying a first group of genres having contents originated solely from the first preference list, identifying a second group of genres having contents originated solely from the second preference list, and identifying a third group of genres having contents originated from both the first and second preference list. 
     In block  314 , a third preference list of recommended contents is generated by analyzing the identified first, second, and third groups of genres to generate recommended contents. The routine for the analysis of the groups of genres may reside in the recommendation engine or provided by a service provider. The third preference list is displayed on a spectrum on the GUI. The first group of genres is displayed adjacent one end of the spectrum, the second group of genres is displayed adjacent the opposite end of the spectrum, and the third group of genres together with the generated recommended contents is displayed adjacent the center of the spectrum. The method ends in block  316 . 
       FIG. 4  is an exemplary depiction  400  of a user influenced recommendation list generated by the system of  FIG. 1 .  FIG. 4  shows a first preference list of contents  402  from the first user device and a second preference list of contents from the second user device. The individual contents from the first and second preference lists  402 ,  404  are displayed on a GUI as thumbnails on a scrollable continuum for each of the respected first and second preference lists  402 ,  404 . The recommendation engine generated recommendation list  406 , or third preference list  406 , is shown beneath the first and second preference lists  402 ,  404 . The individual contents from the recommendation lists  406  are displayed as thumbnails on a scrollable continuum in a spectrum  408 . The contents from the first preference lists  402  are displayed adjacent one end of the spectrum  408   a , the contents from the second preference lists  404  are displayed adjacent the opposite end of the spectrum  408   b , and the content common to both the first and second preference lists are displayed adjacent the center of the spectrum  408   c.    
       FIG. 5  is an illustration of a control panel display  500  on a GUI for generating the user influenced recommendation list, according to an exemplary embodiment. The display includes a continuum  502  having a pointer  504  slideable between a first end of the continuum  506  and a second end of the continuum  508 . The first end represents a 100 percent ratio of contents from a first user device  214   a  and the second end represents a 100 percent ratio of contents from the second user device  214   b . A user slides the pointer  504  along the continuum  506  for selecting a ratio of contents from the first preference list and second preference list. Recommended contents are generated, by the recommendation engine, by analyzing the selected ratio of contents from the first and second preference lists. 
     The disclosure has described certain preferred embodiments and modifications thereto. Further modifications and alterations may occur to others upon reading and understanding the specification. Therefore, it is intended that the disclosure not be limited to the particular embodiment(s) disclosed as the best mode contemplated for carrying out this disclosure, but that the disclosure will include all embodiments falling within the scope of the appended claims.