KR20240093293A - Product purchase recommendation system based on user preference - Google Patents

Abstract

One embodiment of the present invention relates to a product purchase recommendation system based on user preference, and can provide more accurate product recommendation by correcting the user's preference.

Description

Product purchase recommendation system based on user preference {PRODUCT PURCHASE RECOMMENDATION SYSTEM BASED ON USER PREFERENCE}

One embodiment of the present invention relates to a product purchase recommendation system based on user preference.

Smart watches released to date usually function independently or as peripheral devices that link with smartphones. Since it is in the form of a wristwatch, the screen size is limited and the input/output environment is bound to be limited. However, since it is a wearable that is always carried in close contact with the wrist, it can always receive biometric information of the human body (heart rate, body temperature, etc.) and provides vibration, etc. It also has the advantage of being able to send signals to the user through haptic output through the sense of touch. Additionally, compared to smartphones, which are fixed on the wrist when carried and require the use of at least one hand to use, smartwatches have the advantage of allowing information to be viewed without using any hands.　However, since humans rely heavily on visual information, the general assessment is that its weaknesses still outweigh its strengths and that it will only be widely used as a full-fledged smart device if there is a groundbreaking development in the user interface or a change in idea.

In addition, since it is an ultra-small device that can be worn on the wrist, hardware limitations such as battery, CPU, and memory must be overcome. In particular, batteries are currently one of the biggest obstacles, and compared to regular wristwatches that last at least a year, they can only be used for a few days at most. Fever is also a big problem. Due to these limitations, smart watches have grown rapidly, but have not yet become popular, and there are many criticisms that they are nothing more than remote controls for operating smartphones. However, it is also a product line with a lot of room for growth along with technological advancements.

Unlike analog watches, smartwatches can freely change the design of the watch, and users can freely change the watch face corresponding to the display part of the smartwatch.

Embodiments of the present invention may provide a purchase recommendation method for a specific product.

The technical challenges to be achieved in the embodiments are not limited to the matters mentioned above, and other technical challenges not mentioned may be considered by those skilled in the art from the various embodiments described below. You can.

Embodiments of the present invention may include a method and device for recommending a purchase for a specific product performed by at least one server.

According to embodiments, one's preference can be measured through natural changes in the body. Therefore, when you discover a preference in a field you are not familiar with, you can use your heart rate to obtain information about your preference that you could not feel in your head.

The effects that can be obtained from the examples are not limited to the effects mentioned above, and other effects not mentioned can be clearly derived and understood by those skilled in the art based on the detailed description below. It can be.

The accompanying drawings, which are included as part of the detailed description to aid understanding of the embodiments, provide various embodiments and together with the detailed description describe technical features of the various embodiments.
1 is a system diagram including a purchase recommendation server for a specific product according to an embodiment of the present invention.
Figure 2 is a block diagram showing the configuration of a purchase recommendation server for a specific product according to an embodiment of the present invention.
Figure 3 is a diagram illustrating an embodiment of a method for recommending purchase of a specific product.

The following embodiments combine elements and features of the embodiments in a predetermined form. Each component or feature may be considered optional unless explicitly stated otherwise. Each component or feature may be implemented in a form that is not combined with other components or features. Additionally, various embodiments may be configured by combining some components and/or features. The order of operations described in various embodiments may change. Some features or features of one embodiment may be included in other embodiments or may be replaced with corresponding features or features of other embodiments.

In the description of the drawings, procedures or steps that may obscure the gist of the various embodiments are not described, and procedures or steps that can be understood at the level of a person with ordinary knowledge in the relevant technical field are not described. did.

Throughout the specification, when a part is said to “comprise or include” a certain element, this means that it does not exclude other elements but may further include other elements, unless specifically stated to the contrary. do. In addition, terms such as "... unit", "... unit", and "module" used in the specification refer to a unit that processes at least one function or operation, which refers to hardware, software, or a combination of hardware and software. It can be implemented as: Additionally, the terms “a or an,” “one,” “the,” and similar related terms are used herein in the context of describing various embodiments (particularly in the context of the claims below). Unless otherwise indicated or clearly contradicted by context, it may be used in both singular and plural terms.

Hereinafter, embodiments according to various embodiments will be described in detail with reference to the attached drawings. The detailed description set forth below in conjunction with the accompanying drawings is intended to illustrate exemplary embodiments of various embodiments and is not intended to represent the only embodiment.

In addition, specific terms used in various embodiments are provided to aid understanding of the various embodiments, and the use of such specific terms may be changed to other forms without departing from the technical spirit of the various embodiments. .

Referring to FIG. 1, the method of recommending the purchase of a specific product according to an embodiment of the present invention is performed on a computing device that has storage space and can be connected to the Internet, such as a PC (Personal Computer), and is not easily portable, or is performed on a smartphone. It can be performed on a portable terminal, etc. At this time, the purchase recommendation method for a specific product may be executed after an application implementing the purchase recommendation method for a specific product is downloaded from the App Store or the like and installed on the portable terminal.

In addition, the method of recommending the purchase of a specific product is recorded on a recording medium such as CD (Compact Disc) or USB (Universal Serial Bus) memory, inserted into a computing device such as a PC, and performed through an access operation of the computing device. It may be stored from the recording medium in the storage space of the computing device and then performed through an access operation of the computing device.

Meanwhile, if the computing device or portable terminal can connect to a server connected to the Internet, the method of recommending purchase of a specific product can also be executed on the server at the request of the computing device or portable terminal.

Hereinafter, a computing device, portable terminal, or server that executes the method of recommending a purchase for a specific product may be collectively referred to as a purchase recommendation device for a specific product.

The purchase recommendation device for a specific product may have the same configuration as the device for providing a shopping preference measurement service using a smartwatch illustrated in FIG. 2, and the device for recommending a purchase for a specific product may have the same configuration as the device for recommending a purchase for a specific product shown in FIG. 1. It may not be limited to purchase recommendation devices.

The system according to one embodiment may include user terminals 100, 110, 120, and 130, and a purchase recommendation server 200 for a specific product (hereinafter, server 200). The network may include an Internet portal site server, an SNS server, and a server that operates a blog.

User terminals 100, 110, 120, and 130 include smartphones, tablet PCs, PCs, smart TVs, mobile phones, personal digital assistants (PDAs), laptops, media players, micro servers, global positioning system (GPS) devices, and electronic devices. It may be, but is not limited to, book terminals, digital broadcasting terminals, navigation devices, kiosks, MP3 players, digital cameras, home appliances, devices equipped with cameras, and other mobile or non-mobile computing devices. Additionally, the user terminals 100, 110, 120, and 130 may be wearable devices equipped with communication functions and data processing functions. However, it is not limited to this.

The server 200 may be implemented as a computer device or a plurality of computer devices that communicate with the user terminals 100, 110, 120, and 130 over a network to provide commands, codes, files, content, services, etc.

For example, the server 200 may provide files for installing an application to user terminals 100, 110, 120, and 130 connected through a network. In this case, the user terminals 100, 110, 120, and 130 can install the application using files provided from the server 200.

In addition, the user terminals 100, 110, 120, and 130 connect to the server 200 under the control of an operating system (OS) and at least one program (for example, a browser or an installed application), and the server 200 You can receive services or content provided by .

As another example, the server 200 may establish a communication session for data transmission and reception, and route data transmission and reception between user terminals 100, 110, 120, and 130 through the established communication session.

The user terminals 100, 110, 120, and 130 and the server 200 may communicate using a network. For example, networks include Local Area Network (LAN), Wide Area Network (WAN), Value Added Network (VAN), mobile radio communication network, satellite communication network, and their It is a comprehensive data communication network that includes mutual combinations and allows each network constituent shown in Figure 1 to communicate smoothly with each other, and may include wired Internet, wireless Internet, and mobile wireless communication networks. Additionally, wireless communications include, for example, wireless LAN (Wi-Fi), Bluetooth, Bluetooth low energy, ZigBee, WFD (Wi-Fi Direct), UWB (ultra wideband), and infrared communication (IrDA). Data Association), NFC (Near Field Communication), etc., but are not limited to these.

Figure 2 is a block diagram showing the configuration of a purchase recommendation server for a specific product according to an embodiment of the present invention.

Referring to FIG. 2, a server 200 (hereinafter referred to as server 200) that provides a shopping preference measurement service using a smartwatch may include a communication unit 210, a processor 220, and a DB 230. The server 200 may also be referred to as a purchase recommendation server for a specific product. In the server 200 of FIG. 2, only components related to the embodiment are shown. Accordingly, those skilled in the art can understand that other general-purpose components may be included in addition to the components shown in FIG. 2.

The communication unit 210 may include one or more components that enable wired/wireless communication between terminals. For example, the communication unit 210 may include at least one of a short-range communication unit (not shown), a mobile communication unit (not shown), and a broadcast receiver (not shown).

For example, a request generated according to a program code stored in a recording device such as the DB 230 may be transmitted to the terminal through the network under the control of the communication unit 210. Conversely, control signals, commands, content, files, etc. provided according to control of the processor of the terminal may be received by the server 200 through the communication unit 210 via the network. For example, control signals, commands, content, files, etc. of the server 200 received through the communication unit 210 may be transmitted to the processor 220 or transmitted to the DB 230 and stored.

DB 230 is hardware that stores various data processed within the server 200, and can store programs for processing and control of the processor 220.

The DB 230 includes random access memory (RAM) such as dynamic random access memory (DRAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), CD- It may include ROM, Blu-ray or other optical disk storage, a hard disk drive (HDD), a solid state drive (SSD), or flash memory. DB 230 may also be referred to as memory.

The processor 220 controls the overall operation of the server 200. For example, the processor 220 can generally control the input unit (not shown), display (not shown), communication unit 210, DB 230, etc. by executing programs stored in the DB 230. The processor 220 can control the operation of the external server 200 by executing programs stored in the DB 230.

The communication unit 210 may include one or more components that allow the server 200 to communicate with other devices (not shown) and servers (not shown). The other device (not shown) may be a computing device such as the server 200 or a sensing device, but is not limited thereto. The communication unit 210 may receive a user input from another electronic device or receive data stored in an external device from an external device through a network.

DB 230 may store programs for processing and control of processor 220. For example, the DB 230 may store instructions for providing services. Additionally, the DB 230 may store data generated by the processor 220. For example, the DB 230 may store information related to a shopping preference measurement service using a smartwatch provided by the processor 220. DB 230 may store information input to or output from the server 200.

The processor 220 includes application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, and microcontrollers. It may be implemented using at least one of micro-controllers, microprocessors, and other electrical units for performing functions.

DB 230 may store at least one command executed through processor 220. At least one command includes a command for obtaining the user's shopping heart rate information from the user terminal, a command for determining the user's preference for a specific product based on the shopping heart rate information, and a command for determining the user's preference for a specific product based on the user's preference. A command for generating a purchase recommendation index and a command for determining whether to recommend a purchase for the specific product based on the purchase recommendation index, wherein the shopping heart rate information is provided on a purchase page related to the first smartwatch face purchased by the user. A first average heart rate while accessed, a second average heart rate while accessed to a purchase page for a second smartwatch face that the user registered in the wish list but did not purchase, and the first smartwatch among preset categories A third average heart rate while accessing a purchase page for a third smartwatch face or a third smartwatch face included in the same category as the second smartwatch face, and the first smartwatch face and the second smart watch face among the preset categories It may include a fourth average heart rate while accessing a purchase page for a fourth smartwatch face included in a different category from the watch face.

For example, an instruction for determining the user's preference for a specific product based on the shopping heart rate information is an instruction for deriving the user's average heart rate for the specific product while accessing a purchase page for the specific product. , a command for deriving an average heart rate that is closest to the average heart rate for the specific product among the first average heart rate, the second average heart rate, the third average heart rate, and the fourth average heart rate, and a preference regarding the closest average heart rate. and instructions for determining the user's preference based on, wherein the preference regarding the first average heart rate is a first preference, the preference regarding the second average heart rate is a second preference, and the preference regarding the third average heart rate is a second preference. The preference is a third preference, the fourth preference regarding average heart rate is a fourth preference, the first preference represents a higher preference than the second preference, and the second preference represents a higher preference than the third preference. , and the third preference may indicate a higher preference tendency than the fourth preference.

For example, a command for determining the user's preference for a specific product based on the shopping heart rate information may be applied to the purchase page for the specific product when the user accesses the purchase page for the specific product multiple times. A command for deriving the most recent average heart rate while connected at the time of the most recent connection and the last average heart rate while connected at the time of the previous connection, and a command for calculating a heart rate gradient based on the most recent average heart rate and the last average heart rate. A command for determining the user's preference based on the preference for the nearest average heart rate is to preset the preference for the nearest average heart rate when the heart rate gradient is greater than a preset positive threshold. A command to correct by a positive correction value and, if the heart rate gradient is less than a preset negative threshold, to correct the preference regarding the nearest average heart rate by a preset negative correction value, and the corrected closest average It may include a command for determining heart rate preferences as the user's preferences.

For example, a command for generating a purchase recommendation index for the specific product based on the user's preference may include the user's preference, the total number of accesses to the purchase page for the specific product, and the purchase page for the specific product. It may include a command for calculating the purchase recommendation index based on the number of corresponding reviews and the rating corresponding to the purchase page for the specific product.

Figure 3 is a diagram illustrating an embodiment of a method for recommending purchase of a specific product.

Referring to FIG. 3, in step S300, the server may obtain the user's shopping heart rate information from the user terminal. Here, the shopping heart rate information may be information obtained through a smartwatch worn by the user, and the shopping heart rate information may be transmitted from the smartwatch to the server or from the smartwatch to the user terminal and then from the user terminal to the server. there is.

For example, the shopping heart rate information may include a first average heart rate while accessing a purchase page for a first smartwatch face that the user purchased, a second smartwatch face that the user registered to a wish list but did not purchase, The second average heart rate while accessing the purchase page, the first smartwatch face among preset categories, or the third smartwatch face included in the same category as the second smartwatch face while accessing the purchase page A third average heart rate and a fourth average heart rate while accessing a purchase page for a fourth smartwatch face included in a different category than the first smartwatch face and the second smartwatch face among the preset categories. can do.

In step S310, the server may determine the user's preference for a specific product based on shopping heart rate information. For example, the server may derive the user's average heart rate for the specific product while accessing the purchase page for the specific product, the first average heart rate, the second average heart rate, and the third average. Among the heart rate and the fourth average heart rate, the average heart rate that is closest to the average heart rate for the specific product may be derived, and may be determined as the user's preference based on the preference regarding the closest average heart rate.

Here, the preference regarding the first average heart rate may be expressed as a first preference, the preference regarding the second average heart rate may be expressed as a second preference, and the preference regarding the third average heart rate may be expressed as a third preference. and the preference regarding the fourth average heart rate may be expressed as the fourth preference. The first preference may indicate a higher preference than the second preference, the second preference may indicate a higher preference than the third preference, and the third preference may indicate a higher preference than the fourth preference.

Also, for example, if the user accesses the purchase page for the specific product multiple times, the server records the most recent average heart rate during the most recent access to the purchase page for the specific product and the last access time. The last average heart rate while connected can be derived, and the heart rate gradient can be calculated based on the most recent average heart rate and the last average heart rate.

In this case, if the heart rate gradient exceeds a preset positive threshold, the server corrects the preference regarding the nearest average heart rate by a preset positive correction value, and the heart rate gradient exceeds the preset negative threshold. If it is less than this, the preference regarding the nearest average heart rate may be corrected by a preset negative correction value, and the preference regarding the corrected nearest average heart rate may be determined as the user's preference.

In step S320, the server may generate a purchase recommendation index for a specific product based on the user's preference. For example, the server may base the user's preference, the total number of accesses to the purchase page for the specific product, the number of reviews corresponding to the purchase page for the specific product, and the rating corresponding to the purchase page for the specific product. The purchase recommendation index can be calculated.

For example, the purchase recommendation index can be calculated based on Equation 1 below.

Referring to Equation 1, I _p may represent the user's purchase recommendation index regarding the specific product, P may represent the user's preference regarding the specific product, and a may represent the user's preference regarding the specific product. The user's correction value can be displayed. N _v may represent the total number of accesses of the user to the purchase page for the specific product, N _r may represent the number of reviews corresponding to the purchase page for the specific product, and S _r may represent the number of reviews corresponding to the purchase page for the specific product. It may represent the current rating corresponding to the purchase page for the specific product, and S _m may represent the median value of inputtable ratings corresponding to the purchase page for the specific product. Additionally, w ₁ and w ₂ may represent weights related to the total number of accesses and the number of reviews, respectively, which may be set in advance and may be changed by the administrator.

For example, P may be determined as 5 for the first preference, 4 for the second preference, 3 for the third preference, and 1 for the fourth preference. can be decided. Also, for example, a may be determined to be 0.5 as a positive correction value when the heart rate gradient is greater than a preset positive threshold, and as a negative correction value when the heart rate gradient is less than a preset negative threshold. The value can be determined as -0.5.

In step S330, the server may decide whether to recommend a purchase for a specific product based on the purchase recommendation index. For example, when the purchase recommendation index exceeds a preset purchase threshold, the server may deliver purchase recommendation information to the user terminal.

Operations according to embodiments of the present specification can be implemented as a computer-readable program or code on a computer-readable recording medium. Computer-readable recording media include all types of recording devices that store data that can be read by a computer system. Additionally, computer-readable recording media can be distributed across networked computer systems so that computer-readable programs or codes can be stored and executed in a distributed manner.

When the embodiment is implemented in software, the above-described techniques may be implemented as modules (processes, functions, etc.) that perform the above-described functions. Modules are stored in memory and can be executed by a processor. Memory may be internal or external to the processor and may be connected to the processor by a variety of well-known means.

Additionally, computer-readable recording media may include hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Program instructions may include not only machine language code such as that created by a compiler, but also high-level language code that can be executed by a computer using an interpreter, etc.

Although some aspects of the invention have been described in the context of an apparatus, it may also refer to a corresponding method description, where a block or device corresponds to a method step or feature of a method step. Similarly, aspects described in the context of a method may also be represented by corresponding blocks or items or features of a corresponding device. Some or all of the method steps may be performed by (or using) a hardware device, such as a microprocessor, programmable computer, or electronic circuit, for example. In some embodiments, one or more of the most important method steps may be performed by such an apparatus.

In embodiments, a programmable logic device (e.g., a field programmable gate array) may be used to perform some or all of the functionality of the methods described herein. In embodiments, a field programmable gate array may operate in conjunction with a microprocessor to perform one of the methods described herein. In general, the methods are preferably performed by some hardware device.

The various embodiments described above may be embodied in other specific forms without departing from the technical idea and essential features. Accordingly, the above detailed description should not be construed as restrictive in all respects and should be considered illustrative. The scope of the various embodiments should be determined by a reasonable interpretation of the appended claims, and all changes within the equivalent scope of the various embodiments are included in the scope of the various embodiments. In addition, claims that do not have an explicit reference relationship in the patent claims can be combined to form an embodiment or included as a new claim through amendment after filing.

Claims (1)

In a method of recommending product purchase based on user preference performed by at least one server,
Obtaining the user's shopping heart rate information from the user terminal;
determining the user's preference for a specific product based on the shopping heart rate information;
generating a purchase recommendation index for the specific product based on the user's preference; and
A step of determining whether to recommend a purchase for the specific product based on the purchase recommendation index,
The shopping heart rate information includes a plurality of average heart rates of the user while accessing a plurality of purchase pages related to a smartwatch face, and the plurality of average heart rates include whether the user makes a purchase among the plurality of purchase pages and a wish list. Includes a first average heart rate, a second average heart rate, a third average heart rate, and a fourth average heart rate classified according to whether or not they are included in,
The step of determining the user's preference for a specific product based on the shopping heart rate information,
deriving an average heart rate for the specific product of the user while accessing a purchase page for the specific product;
determining a preference for the specific product based on the plurality of average heart rates of the user while accessing the plurality of purchase pages and the average heart rate for the specific product;
Deriving an average heart rate that is closest to the average heart rate for the specific product among the first average heart rate, the second average heart rate, the third average heart rate, and the fourth average heart rate; and
determining the user's preference based on the preference regarding the nearest average heart rate;
The preference regarding the first average heart rate is a first preference, the preference regarding the second average heart rate is a second preference indicating a lower preference tendency than the first preference, and the preference regarding the third average heart rate is the second preference. It is a third preference indicating a preference tendency lower than the preference, and the preference regarding the fourth average heart rate is a fourth preference indicating a preference tendency lower than the third preference,
The step of determining the user's preference for a specific product based on the shopping heart rate information,
If the user accesses the purchase page for the specific product multiple times, the most recent average heart rate during the most recent access to the purchase page for the specific product and the most recent average heart rate during the last access. A step of deriving; and
Further comprising calculating a heart rate gradient based on the most recent average heart rate and the previous average heart rate,
The step of determining the user's preference based on the preference regarding the nearest average heart rate,
If the heart rate gradient is greater than a preset positive threshold, the preference for the nearest average heart rate is corrected by a preset positive correction value, and if the heart rate gradient is less than a preset negative threshold, the preference for the nearest average heart rate is corrected by the preset positive correction value. Correcting the preference regarding the nearest average heart rate by a preset negative correction value; and
And determining a preference regarding the corrected closest average heart rate as the user's preference,
A method for recommending product purchase based on user preference, wherein the preset positive correction value is determined to be 0.5, and the preset negative correction value is determined to be -0.5.