KR20190142508A - Method and apparatus for providing product information - Google Patents

Abstract

An embodiment of the present invention relates to a method for providing product information and a device thereof. The method for providing product information comprises the steps of: collecting information on products sold in a plurality of shopping malls and selecting a predetermined number of active products for each shopping mall; analyzing a product description natural language for each product and assigning a classification identifier for classifying the features of the product to each product; collecting postings related to each product category and analyzing time, region, site, and propensity to generate trend information for each category; collecting user information to analyze the user information; selecting a plurality of customized products based on the analyzed user information and trend information; and providing product information of the selected customized product. The present invention can provide user-customized product information.

Description

Method and apparatus for providing product information {METHOD AND APPARATUS FOR PROVIDING PRODUCT INFORMATION}

The present invention relates to a method and apparatus for providing product information.

In general, a marketing system based on statistics has a form in which a manager prepares and aggregates a questionnaire, inputs it, and builds a content. A consumer's input is directly searched and inquired by a manager. In addition, the database that performs statistics and analysis also stores and outputs the structure and outputs the results of statistics only, and does not present the appropriate product to the individual or provide the function of consumer demand analysis and fashion analysis. In addition, the fashion field has a large number of emotional differences and a number of cases in terms of personal tastes, inclinations, and situations in which items are used. In some cases, it is simply a database that is prepared for the number of cases by emotion item, but this is very difficult to apply to the prediction of outcomes in the fashion field, where the consumer's tendency is diverse and there is a great possibility of error.

On the other hand, the analysis of individual's purchasing tendency is also very important for the consumer. With the development of internet technology, a lot of service companies are opening up shopping malls and marketing strategies to provide consumers with a huge amount of information. In this situation, in order to purchase a product, a consumer must select a desired product by surfing a number of shopping malls or auction sites. However, because the number of shopping malls that sell various products online or provide purchase information is increasing exponentially, it takes a lot of time for consumers to find what they really want. In addition, since many shopping malls provide only similar information about products, it is difficult for consumers to have accurate criteria.

The product recommendation management system is a personalized information filtering technology that makes it easy for customers to find products that can be purchased by making a list of recommended products. Collaborative filtering is known as the most successful product recommendation technique and is widely used. However, with the rapid increase in the number of products and customers managed in Internet shopping malls, the product recommendation management system based on collaborative filtering is exposed to the problem of sparsity and scalability of input data.

In general, the e-commerce website sales analysis method is performed by providing statistics on the visitors of the site. In the method for analyzing the statistics, the address of a specific website and the page of the address of the website is analyzed so that the user selects a web page and a page called through a user's web browser and selects a link to move to another page. If the web browser also additionally provides a sales analysis method, it may include how the total user viewed and purchased the product. Such an e-commerce site sales analysis method does not include more than the web site's web analytics, Practically, we could not analyze product inquiry purchases and provide tools related to them. The operator who operates the e-commerce website does not consider the efficient placement of products for sale on the e-commerce website, I can't place a product The company was forced to bear additional costs to make up for it, such as events for advertising or sales. In addition, it was forced to suffer adverse effects, such as reduced sales, due to improper placement of product by the e-commerce website operator. The commerce website customer sees a random placement of the product placed by the operator of the e-commerce website, so that the e-commerce website has a negative image or the product required by the customer is properly placed on the main page and main page of the website. There is a problem that can lead to a decrease in sales.

The present specification has been made to solve the problems described above, and to provide a personalized product providing apparatus for each user reflecting the changing tastes and trends of the user without relying on the fragmentary information such as the purchase history in real time.

To this end, according to the first aspect of the present invention, the method for providing product information according to the present invention comprises the steps of: collecting information of products sold in a plurality of shopping malls, selecting a predetermined number of active products for each shopping mall; Analyzing a product description natural language for each product and assigning a classification identifier for classifying the features of the product for each product; Generating trend information for each category by collecting posts related to each product category by analyzing time, region, site, and disposition; Collecting user information and analyzing user information; Selecting a plurality of customized products based on the analyzed user information and trend information; And providing product information of the selected customized product.

The analyzing of the user information may include: identifying a user by obtaining login information of the user; Providing a user interface for inputting unstructured data including shopping purpose, current mood, and style; And querying the database for the structured data including the user's personal information and the shopping history information.

Selecting the active products, assigning the classification identifier, and generating the trend information for each category are repeatedly performed at predetermined intervals.

The post includes one or more of a product review, a customer's SNS, and a blog.

The step of selecting the active products is selected based on the number of inquiry, the length of equipment and the number of purchases for the product.

The analyzing of the user information may further include selecting an indifferent item based on the presence or absence of a click on the active goods provided at the previous login and a purchase result.

The selecting of the plurality of customized products based on the analyzed user information and the trend information may include selecting a customized product by applying a negative weight to the selected indifferent item.

According to a first aspect of the present invention, the product information providing apparatus according to the present invention, receiving information of goods sold in a plurality of shopping malls, receives a post related to each product category, and receives the user's information Communication unit; And selecting a predetermined number of active products for each shopping mall based on the received information of the received products, and analyzing a product description natural language for each product to give a classification identifier for classifying the characteristics of the product for each product. The trend information for each category is generated by analyzing time, region, site, and propensity based on the collected postings, and the user information is analyzed based on the collected and unstructured data information. And selecting a plurality of customized products to provide product information of the selected products.

The control unit may provide a user interface for inputting the atypical data when identifying a user by obtaining login information of the user and selecting a customized product of the identified user, wherein the structured data may include personal information of the user, login information, and the like. It includes shopping history information, wherein the atypical data is characterized by including the shopping purpose, current mood and style.

The control unit is characterized in that the selection based on the number of inquiry, the number of equipment carry, and the number of purchases for the active product.

The controller selects an indifferent item based on the presence or absence of a click on the active products provided at the previous login and a purchase result, and applies a negative weight to the selected indifferent item to select a customized product.

According to the present invention, it is possible to provide customized product information of a user by reflecting a changing shopping purpose and mood of a user without relying on fragmented information such as a purchase history in real time.

By providing the product information accurately reflecting the trend, even if the user's purchase history information is not much, it is possible to provide information of products that suit the user's taste relatively.

Buyers can easily and quickly search for products that meet the latest trends, improving user convenience.

According to the present invention, the supplier can be expected to increase the sales easily and easily by simple information linkage.

1 is a block diagram schematically illustrating a configuration of a product information system used for online electronic commerce according to an embodiment of the present invention.
2 is a block diagram schematically illustrating a configuration of a merchandise information device according to an embodiment of the present invention.
3 is a block diagram schematically illustrating a configuration of a customer terminal according to an exemplary embodiment of the present invention.
4 is a flowchart illustrating a product information providing method of a product information providing apparatus according to an exemplary embodiment.
5 is an exemplary view for explaining a method of analyzing natural language from a product description according to an embodiment of the present invention.
6 is a flowchart illustrating a user analysis process of step S240 of FIG. 4 according to an embodiment of the present invention.
7 is a flowchart illustrating a user analysis process of step S240 of FIG. 4 according to another embodiment of the present invention.
8 is an exemplary view of an input screen provided by an input interface according to an embodiment of the present invention.

It is to be noted that the technical terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In addition, the technical terms used in the present specification should be interpreted as meanings generally understood by those skilled in the art unless they are specifically defined in this specification, and are overly inclusive. It should not be interpreted in the sense of or in the sense of being excessively reduced. In addition, when the technical terms used herein are incorrect technical terms that do not accurately represent the spirit of the present invention, it should be replaced with technical terms that can be understood correctly by those skilled in the art. In addition, the general terms used in the present invention should be interpreted as defined in the dictionary or according to the context before and after, and should not be interpreted in an excessively reduced sense.

Also, the singular forms used herein include the plural forms unless the context clearly indicates otherwise. In the present application, terms such as “consisting of” or “comprising” should not be construed as necessarily including all of the various components, or various steps described in the specification, wherein some of the components or some of the steps It should be construed that it may not be included or may further include additional components or steps.

In addition, the suffixes "module" and "unit" for the components used herein are given or mixed in consideration of ease of specification, and do not have meanings or roles that are distinguished from each other.

In addition, terms including ordinal numbers, such as first and second, as used herein may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as the second component, and similarly, the second component may also be referred to as the first component.

The natural language described in the present invention is a language commonly used by humans, and refers to a language for distinguishing a programming language, a job control language, and the like.

1 is a block diagram schematically illustrating a configuration of a product information system used for online electronic commerce according to an embodiment of the present invention.

As shown in FIG. 1, the product information providing system of the present invention may include a customer terminal 100, a product information providing apparatus 200, and a shopping mall server 300. In addition, the SNS server 400 may further include. The customer terminal 100 is a terminal that performs a payment to purchase a product of a supplier through an open market.

The customer terminal 100 may be a mobile phone terminal capable of internet, or may be a computer device such as a laptop or a desktop, or a mobile terminal capable of communicating, such as a personal digital assistant (PDA), tablet PC, smartphone, or portable multimedia player (PMP). It may be. However, the present invention is not limited thereto, and communication and information input / output can be applied regardless of the type.

The product information providing apparatus 200 collects the product information of the pre-contracted online shopping mall and analyzes the latest trend to provide the customized product information desired by the user.

The product information providing apparatus 200 provides an input interface for inputting user information to the customer terminal 100 connected through a communication network so that the user may receive customized product information.

More specifically, the product information providing apparatus 200 selects only active products of a corresponding shopping mall through sales information acquired from each shopping mall, acquires data of SNS and various communities, analyzes the latest trend, and then stores information of the consumer. Provides customized product information matching with.

The product information providing apparatus 200 provides a user input interface to the customer terminal 100 to collect information of the consumer to help the user input information.

The shopping mall server 300 is a server that manages an online shopping mall. The online shopping mall is an electronic commerce which allows a buyer to purchase a product directly or through a product information providing apparatus 200 through a store opened by an individual or a small company online. Generic site.

The shopping mall server 300 preferably provides the product information and the shopping mall information of the shopping mall to the product information providing apparatus 200 every time a product of the shopping mall is updated or at regular intervals. The shopping mall information may include a shopping mall ID and scale information, and the scale information may include any one or more of the number of members of the shopping mall, the monthly sales amount of the shopping mall, and the number of products sold.

The shopping mall server 300 manages product sales and delivery, and provides a payment interface to help the consumer proceed with payment.

A detailed operation method of the product information system of FIG. 1 will be described later with reference to FIGS. 2 to 8.

2 is a block diagram schematically illustrating a configuration of a merchandise information device according to an embodiment of the present invention.

2, the product information providing apparatus 200 according to an exemplary embodiment of the present specification may include a communication unit 210, a control unit 230, and a database unit 250.

The communication unit 210 transmits and receives a signal necessary for the operation of the product information device 200. The communication unit 210 may receive at least some of the customer information, for example, from the customer terminal 100. In addition, the communication unit 210 may receive at least some of the product information from the shopping mall server 300. In addition, the communication unit 210 may receive at least some of the trend information from the SNS server 400.

The communication unit 210 may provide a user input interface to the customer terminal according to the instruction of the control unit 220, and deliver a response message to the product inquiry request message of the subscriber to the customer terminal.

The controller 230 controls each component for the operation of the product information device 200.

The control unit 230 stores the information received by the communication unit 210 in the database unit 230, and obtains the necessary information from the database unit 250 according to the request message received by the communication unit to generate a response to the product inquiry request do.

The controller 230 provides a user interface to the customer terminal 100 and provides customized product information based on input information and pre-stored customer related information according to the interface. The controller 230 may further perform user authentication to provide such a service.

The controller 230 selects a plurality of customized products according to a user's request to the collected information, and provides product information of the selected product to the customer terminal.

The controller 230 may guide or induce access to a purchase page of a shopping mall that sells the selected product in order to assist the customer in purchasing the selected product.

The controller 230 may include a product analysis module 232, a trend analysis module 234, a user information analysis module 236, and a product matching module 238.

The product information analysis module 232 selects the active products of each shopping mall based on the information of the products obtained from the shopping mall. Active products are popular items that customers are likely to buy. The number of selected active products may be determined differently depending on the size of the shopping mall. The selected active product information is stored in the product information DB 252.

The trend information analysis module 234 generates trend information for each category based on posts collected from the SNS server 400. The trend information analysis module 234 may generate trend information by analyzing time, region, site, and propensity by collecting posts such as evaluation articles, reviews, and related SNSs and blogs. The generated trend information is stored in the trend information DB 253 of the database unit.

The user information analysis module 236 analyzes user preferences (flavors) based on the user's structured data and unstructured data.

The formal data includes the user's personal information, login information, and shopping history information input from the customer terminal at the time of customer registration. Personal information may include age, gender, address, occupation, hobbies, and the like. The login information is information for confirming that the user is qualified to receive the service, and may include a user ID and a password. The shopping history information includes not only the user's purchase information and shopping cart information, but also a record of the object clicked on by the user, the path the user has traveled on the web or the network, and the like.

Atypical data includes shopping objectives, current mood, and styles that were entered when a product inquiry was requested. The user information analysis module 236 stores the analyzed result in the user information DB 254 of the database unit 250.

The user information analysis module 236 selects an indifferent item based on the user's structured data and unstructured data. An indifferent item may mean items that are outside the user's interest, and may include items that have not been purchased or are not clicked by the user after being exposed to the user as an active product. It is possible to provide negative weights (or addition points) for indifferent items.

The product matching module 238 selects a customized product suitable for a user's taste based on the information stored by the product information analysis module 232, the trend information analysis module 234, and the user information analysis module 236. The information of the purchased product. The product matching module 238 stores the analyzed result in the product matching information DB 255.

The database unit 250 may store information and program codes necessary for an operation of providing product information.

The database unit 250 may include a shopping mall DB 251, a product information DB 252, a trend DB 253, a user information DB 254, and a product matching information DB 255.

The shopping mall DB 251 stores information such as an ID of the shopping mall, an address, a business type, the number of members of the shopping mall, the average daily access number of the shopping mall, and the average daily selling price information.

The product DB 252 stores the ID of the product, the shopping mall ID of the product, the classifier identifier of the product, the product description, and the like. The classification identification information of the goods may be given by the controller 200.

 The trend DB 253 may include a post, a posting time, a posting area, a site propensity, product metadata (trademark and category), evaluation information, and the like.

The user information DB 254 stores the personal information of the customer, including the customer ID, customer authentication means, address, social security number, preferred merchant, and the like.

The product matching information DB 255 stores information of products matching for each user.

Information in each database may be stored in association with each other.

Each module of the controller 200 is illustrated as a separate component. These are functionally divided for convenience of description, and the present invention is not limited thereto, and it is apparent that the modules shown above may be implemented in combination with each other according to the intention of those skilled in the art.

3 is a block diagram schematically illustrating a configuration of a customer terminal according to an exemplary embodiment of the present invention.

The customer terminal 100 may include a communication unit 110, an input unit 120, a display unit 130, a controller 140, and a storage unit 150.

The communication unit 110 transmits a user's command to the product information providing apparatus 200 and receives data provided by the product information providing apparatus 200. The communication unit 110 may be implemented using at least some of, for example, an internet protocol, long term evolution (LTE), and other wired / wireless communication schemes.

The input unit 120 receives information from a user through an input interface provided from the product information providing apparatus 200 and transmits the information to the controller 140.

The input unit 120 may include a touch sensor of a touch screen, a keyboard, a keypad, a mouse, and other input devices known to be developed or developed in the future. For example, the touch sensor detects a user's touch input. The touch sensor detects a user's touch input, generates a detection signal, and transmits the detected signal to the controller 140. The sensing signal includes coordinate data input by a user. When the user inputs the touch position movement operation, the touch sensor generates a detection signal including the coordinate data of the touch position movement path and transmits the detected signal to the controller 140.

When the input unit 120 supports a key input method (key input unit), the input unit 120 receives a key operation of a user for controlling the customer terminal 100, generates an input signal, and transmits the generated input signal to the controller 140. The key input unit may be configured as a keypad including a numeric key and a direction key, and may be formed as a predetermined function key on one surface of the customer terminal 100. According to the exemplary embodiment of the present specification, in the case of the security device capable of all operations using only the touch screen, the key input unit is omitted.

Since the input method of the input unit 120 as described above is already widely known, a detailed description thereof will be omitted.

The display unit 130 displays an operation screen of the customer terminal 100.

The display unit 130 may be formed of a liquid crystal display (LCD), organic light emitting diodes (OLEDs), active matrix organic light emitting diodes (AMOLEDs), and the like. A menu, input data, function setting information, and various other information of the terminal 100 are visually provided to the user. In particular, the display unit 130 may display an input interface and product information provided from the upper wind information providing apparatus 200.

The controller 140 controls the overall operation of each component of the customer terminal 100. In particular, the control unit 140 displays an input interface provided from the product information providing apparatus 200, transfers information input through the input interface to the product information providing apparatus 200, and receives it from the product information providing apparatus 200. It can control the function to output the customized product information.

The storage unit 150 stores a program and data necessary for the operation of the customer terminal 100 and may be divided into a program area and a data area. The program area includes a program for controlling the overall operation of the customer terminal 100, an operating system (OS) for booting the customer terminal 100, an application program necessary for outputting product information, other optional functions of the customer terminal 100, For example, an application program required for a camera function, a sound reproduction function, an image or a video reproduction function, and the like can be stored. The data area is an area in which data generated according to the use of the customer terminal 100 is stored, and may store product information, shopping mall information, payment information, and the like.

4 is a flowchart of a method of providing product information of a product information providing apparatus according to an embodiment of the present invention, and FIG. 5 is an exemplary view for explaining a method of analyzing natural language from a product description according to an embodiment of the present invention. .

First, by collecting information on products sold in a plurality of subscribed shopping malls, a predetermined number of active products are selected for each shopping mall (S210).

The collected data used for product analysis divides the products of the existing shopping mall into respective categories, and selects a predetermined number of active products in the same category. In order to select an active product, the number of product views, the number in a shopping cart, and the number of purchases are used.

The predetermined number may be different for each shopping mall. The predetermined number may vary depending on the size of the shopping mall. The size of the shopping mall may be determined based on the number of members of the shopping mall, the monthly sales amount of the shopping mall, and the number of products sold. For example, the level of the shopping mall is given according to whether or not the number of members satisfies any one of three conditions in which the number of members is at least a certain number, the average sales amount in the last three months is at least a predetermined amount, and the number is at least a predetermined number. The larger the shopping mall, the higher the level. More active products are selected for shopping malls that are assigned high levels, that is, larger shopping malls, and fewer active products are selected for shopping malls that are assigned levels, that is, smaller shopping malls.

Subsequent to the assumption, the category of all products of the shopping mall of the clothing industry includes the top, the bottom, the outer, etc., and each of the places where the size of the shopping mall of the clothing industry has a level 3 selects one active product, and the shopping mall If b is the level 2, each active product is selected by b, and if the size of the shopping mall is 1 level, each of the c is selected, a is greater than b and b is greater than c. For example, a is 30, b is 20, and c is 10. For each of the tops, bottoms, and outers included in each category of an apparel shopping mall at level 3, the number of product views and shopping carts is included. 30 active products are selected based on the number, the number of purchases, etc., 20 active products are selected for the products included in each category of any clothing industry shopping mall of level 2, and any clothing industry shopping mall of level 1 is selected. Selects 10 active products for each product included in each category.

In one embodiment of the present invention, the same number of active items is set for each category, but is not limited thereto. In another variation, a predetermined number of active products may be selected for all the products of the shopping mall, not for each category.

The product description natural language for each of the selected active products is analyzed and a classification identifier is assigned to each product (S220). This classifier can be used to determine the characteristics of the product.

As illustrated in FIG. 5, natural language is analyzed from a product description of a product selected as an active product, and words that describe the product are extracted. In the example of FIG. 5, 'feminine', 'tweed jacket', 'color', 'daily', 'mix', 'pattern', 'black background', 'fresh', 'diminent', 'casual', 'feminine Words such as 'short', 'chic' and 'looking young' are extracted.

The extracted words are grouped according to a predefined classification. Each group is assigned a classifier. For example, feminine, feminine, and the like may be grouped into one group and given the same classifier.

Collecting posts related to each category of the product, by analyzing the time, region, site, propensity to generate trend information for each category (S230).

In order to collect the latest trend information, feeds of various SNS and community data (feed) to collect corpus associated with fashion, analyze and generate purified data. Table 1 below is an example of data purified according to an embodiment of the present invention.

 No. Post posting
Time Posting Area Site orientation Product metadata evaluation One Nike socks are not good. summer Seoul male Nike socks not really 2 Nike socks are good winter Seoul male Nike socks Good 3 Nike socks are good summer Busan male Nike socks Good 4 Nike socks are not good winter Busan male Nike socks not really 5 Nike socks are good summer Seoul female Nike socks Good 6 Nike socks are not good winter Seoul female Nike socks not really 7 Nike socks are not good summer Busan female Nike socks not really 8 Nike socks are good winter Busan female Nike socks Good

From each post collected, the publication time, posting area, site propensity, product metadata (trademark and category), and evaluation information can be extracted.

To refine the data from the post, stemming and key word dictionaries can be used. A key word dictionary is a set of words that appear or are expected to appear overlapping product ratings in a post.

A typo word dictionary is a set of examples of typos, for misleading results through STT or for the stemmer to recognize them as nouns.

For example, the typo word dictionary enables the recognition of 'peck' and 'zoa' as 'likes'. Accordingly, it is possible to analyze trend information for each purchase type according to buyer gender, location, and time of year (seasonal). Based on the extracted information, trend products according to purchase types may be selected.

To classify means to classify the object of classification into categories, that is, classes, that is, it is clear that what has a characteristic belongs to which class. If you don't, you may be wondering what to do, for example, should a person who is 180 cm tall be classified as a 'woman' or a 'male' class? In this case, statistical-based machine learning algorithms, such as the Naive Bayes classifier, look at observations. For example, a series of training data shows that No. 1 is 160 cm tall, No. 2 is 165 cm tall, No. 3 is 157 cm tall, No. 4 is 168 cm tall, and no. Assuming that the height is 180cm, the number 2 is 177cm, the number 3 is 181cm, and the number 4 is 172cm, these observations calculate the probability that a person 180cm tall is a woman and a man is You can compare the two. Which probability is more important than the probability value itself? If the output indicates that the probability of being male is higher than the probability of being female, it would be reasonable to classify this person as a class of men. Therefore, the naive Bayes classifier calculates which class the probability is that the object having the feature belongs according to the observed feature. To do this, the Naive Bayes classifier can leverage Bayes' Theorem, one of the basic theorems widely used in probability and statistics.

Next, the user information is collected and analyzed (S240).

The user's preference (or taste) is analyzed by collecting the structured data including the user's personal information, login information, and shopping history information, and the unstructured data including the shopping purpose, current mood, and style.

Based on the analyzed user information and trend information, a plurality of customized products are selected (S250).

The mapped product information is extracted based on the analyzed product information, the trend information, and the user information according to the steps S220, S230, and S240.

The mapped product is a product that is likely to meet the user's preference or taste, and the extracted product information is stored.

Provides product information of the selected customized product (S260).

When providing product information, not only the detailed information of the product, but also the shopping mall information may be provided together or linked to a purchase page.

6 is a flowchart illustrating a user analysis process of step S240 of FIG. 4 according to an embodiment of the present invention.

Acquire the user's login information to identify the user (S241).

For example, if the user enters the ID and password in step S241, the product information providing apparatus checks whether the customer is eligible to receive the service through any user authentication procedure, and identifies the user. Since the user authentication procedure is a general technology, a detailed description thereof will be omitted.

Next, a user interface for inputting unstructured data including shopping purpose, current mood, and style is provided (S242).

Informed data including personal information of the user and shopping history information is searched from the database (S243).

The user may input 'exercise' and 'socks' through an input interface provided from the product information providing apparatus, and may obtain customized information about socks worn during exercise. The user's address and gender can be confirmed through pre-stored user information. Assuming that the user's address is Seoul and the gender is male, and the product information providing device stores the trend information as shown in Table 1 and the user input time is 'winter', 'exercise', 'socks', 'male' By combining information such as 'winter' and 'seoul', 'Nike' socks can be selected first among active products of each shopping mall.

 By providing the product information by accurately reflecting the trend through the product information providing method according to an embodiment of the present invention, even if the purchase history information of the user is not much, it is possible to provide information of products that suit the user's taste relatively.

7 is a flowchart illustrating a user analysis process of step S240 of FIG. 4 according to another embodiment of the present invention. Since the same reference numerals as in FIG. 6 denote the same processes, detailed descriptions of the same processes will be omitted.

Acquire the user's login information to identify the user (S241).

A user interface for inputting unstructured data including shopping purpose, current mood, and style is provided (S242).

Informed data including personal information of the user and shopping history information is searched from the database (S243).

The shopping history information of the user selects the indifferent item of the user (S244).

The user's indifferent item may be provided only to the user who used the user-customized product information providing service provided in an embodiment of the present invention more than once.

The user selects indifferent items among items that the user does not click on and items that have not been purchased, among the active products exposed to the user through a customized product information service.

When the indifference item is selected as described above, a negative weight may be applied to the indifference item when the customized product is selected later. Items that have not been clicked may have different weights for items that have not been purchased. An item that is not clicked may have a higher negative weight than an item that is clicked but not purchased.

By providing the product information by accurately reflecting the trend through the product information providing method according to another embodiment of the present invention, it is possible to select the item of indifference of the user to provide information of the products that best meet the taste of the user.

8 is an exemplary view of an input screen provided by an input interface according to an embodiment of the present invention.

When the user is identified, the product information providing apparatus may search for personal information of the user and provide an input interface. For example, the product information providing apparatus may provide a first information item in order to obtain unstructured data to the user, and when the user answers, provide a second information item associated with the first information item. In this way, the user may go to the desired information.

For example, as shown in FIG. 8, when the user inputs or selects 'femininity' and 'blind date' as keywords, the products matching the trend are given priority among the active products of shopping malls matching femininity and blind date. Can be displayed as

Through the product information providing method according to an embodiment of the present invention, a buyer can easily and quickly search for a product that meets the latest trend, thereby improving user convenience.

The aforementioned method can be implemented through various means. For example, embodiments of the present invention may be implemented by hardware, firmware, software, or a combination thereof.

In the case of a hardware implementation, a method according to embodiments of the present invention may include one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), and Programmable Logic Devices (PLDs). And field programmable gate arrays (FPGAs), processors, controllers, microcontrollers and microprocessors.

In the case of an implementation by firmware or software, the method according to the embodiments of the present invention may be implemented in the form of a module, a procedure, or a function that performs the functions or operations described above. The software code may be stored in a memory unit and driven by a processor. The memory unit may be located inside or outside the processor, and may exchange data with the processor by various known means.

Embodiments disclosed herein have been described with reference to the accompanying drawings. As described above, the embodiments shown in each drawing should not be construed as limiting, but may be combined with each other by those skilled in the art, and some components may be omitted.

Here, the terms or words used in the present specification and claims should not be construed as being limited to the ordinary or dictionary meanings, but should be interpreted as meanings and concepts corresponding to the technical spirit disclosed in the present specification.

Therefore, the embodiments described in the present specification and the configuration shown in the drawings are merely exemplary embodiments disclosed herein, and do not represent all of the technical ideas disclosed herein, and various equivalents may be substituted for them at the time of the present application. It should be understood that there may be water and variations.

100: customer terminal
200: product information providing device
210: communication unit
230: control unit
232: Product Analysis Module
234: Trend Analysis Module
236: user information analysis module
238: Product Matching Module
250: database
300: shopping mall server

Claims (10)

Collecting information on products sold in the plurality of shopping malls and selecting a predetermined number of active products for each shopping mall;
Analyzing a product description natural language for each product and assigning a classification identifier for classifying the features of the product for each product;
Generating trend information for each category by collecting posts related to each product category by analyzing time, region, site, and disposition;
Collecting user information and analyzing user information;
Selecting a plurality of customized products based on the analyzed user information and trend information; And
Providing product information of the selected customized product;
Product information providing method comprising a. The method of claim 1, wherein analyzing the user information comprises:
Identifying a user by obtaining login information of the user;
Providing a user interface for inputting unstructured data including shopping purpose, current mood, and style; And
Retrieving structured data including personal information of the user and shopping history information from a database;
Product information providing method comprising a further. The method of claim 1,
Selecting the active products, giving the classification identifier, and generating the trend information for each category are repeatedly performed at predetermined intervals. The method of claim 1,
The article is a product information providing method comprising any one or more of the product reviews, the customer's SNS and blog. The method of claim 1, wherein selecting the active products comprises:
The product information providing method, characterized in that the selection based on the number of inquiry, the number of equipment and the number of purchases for the product. The method of claim 1,
Analyzing the user information,
Selecting an item of indifference based on the presence or absence of a click on the active items provided at the time of the previous login and the purchase result;
Selecting a plurality of customized products based on the analyzed user information and trend information,
The product information providing method characterized in that for applying a negative weight to the selected indifferent item, selecting a customized product. A communication unit configured to receive information of products sold in a plurality of shopping malls, receive posts related to each product category, and receive user information; And
Based on the received product information, a predetermined number of active products are selected for each shopping mall, a product identification natural language is analyzed for each product, and a classification identifier for classifying product features is provided for each product. Based on the collected posts, the trend information for each category is generated by analyzing the time, region, site, and propensity, and the user information is analyzed based on the collected and unstructured data information of the collected user. Control unit that selects a customized product and provides product information of the selected product
Product information providing device comprising a. The method of claim 7, wherein
The controller provides a user interface for inputting the atypical data when identifying a user by obtaining login information of a user and selecting a customized product of the identified user.
The atypical data includes personal information, login information and shopping history information of the user, and the atypical data includes a shopping purpose, a current mood and a style. The method of claim 7, wherein
The article is a product information providing device, characterized in that it comprises any one or more of the product reviews, the customer's SNS and blog. The method of claim 7, wherein
The control unit, when selecting the active product, product information providing apparatus, characterized in that the selection based on the number of purchases, the number of equipment and the number of purchases.

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