KR20160087698A - System for recommending of seafood selling - Google Patents

Abstract

The present invention provides a seafood selling recommendation system. The seafood selling recommendation system comprises: a first purchaser index calculation portion which calculates a recommender allocation point which corresponds to a purchasing behavior of a first purchaser who is recommended directly by the recommender, and calculates a first purchaser index; a second purchaser index calculation portion which calculates a recommender allocation point which corresponds to the purchasing behavior of a second purchaser who is recommended by the first recommender, and calculates a second purchaser index; and a recommender point calculation portion which calculates the final recommender point by adding the first purchaser index to the second purchaser index.

Description

{SYSTEM FOR RECOMMENDING OF SEAFOOD SELLING}

The present invention relates to a system for recommending a commodity for sale of marine products on the web, and more particularly, to a system for recommending commodities to an acquaintance, .

Recently, the shopping market using various smart devices such as smart phones is spreading actively as well as shopping through the computer web.

Accordingly, there is a growing need for a more convenient and efficient electronic commerce method, and development of various marketing methods for attracting a large number of purchasing actions is required.

Accordingly, various forms of electronic commerce such as smartphone shopping application, social commerce, and auction are commercially available. In such electronic commerce, marketing methods such as recommender system and review point system are utilized, It is necessary to develop an effective marketing system.

In accordance with the above-mentioned demand, Korean Patent Laid-Open Publication No. 2003-008894 describes a marketing method through a recommender system, but as described in the above document, a method of recommending a link URL through e-mail is used It is difficult to recommend easily, and it is difficult to identify a large number of advertising mails.

Accordingly, development of a marketing system capable of continuously inducing recommendation behavior by allowing a recommender to easily recommend an article to an acquaintance and to give appropriate compensation to a recommender when a purchase action for the recommendation action occurs Is required.

Korean Patent Publication No. 2003-008894

SUMMARY OF THE INVENTION Accordingly, the present invention has been made to solve the above problems, and it is an object of the present invention to provide a recommender who can easily recommend an article to an acquaintance through a smart phone message, And provides a marine product sales recommendation system capable of differentiating points according to the expiration date, guiding the recommendation behavior continuously, and facilitating inventory processing with an imminent expiration date.

The fishery product sales recommendation system according to an embodiment of the present invention includes a rating classifying unit for classifying the aquatic products to be sold according to the expiration date, a recommendation assigning point corresponding to the purchasing behavior of the first purchaser, A second buyer index calculating unit for calculating a second buyer index by calculating a recommender allocation point corresponding to a purchase behavior of a second buyer recommended by the first buyer, A weighting point calculating unit for calculating a weighting point by multiplying the purchasers of the first purchaser and the second purchaser by weights according to the rating classification to calculate a weighting point and a weighting point calculating unit for summing the first purchaser index, And a recommender point calculating unit for calculating a final recommender point.

According to an aspect of the present invention, the first buyer's index calculating unit calculates a first buyer's index by calculating an equation according to a price of purchased goods, a number of friends, and a purchased goods classification index.

According to an aspect of the present invention, the second buyer's index calculating unit calculates a second buyer's index by calculating a formula according to the price of the purchased item, the number of friends, and the grade of the purchased product.

According to one aspect of the present invention, the classifying unit classifies the aquatic products sold as a group in which the expiration date is less than or equal to a predetermined time from the point of sale, and a group in which the expiration date exceeds the predetermined time period from the point of sale, The recommender's point calculator calculates a product of a group of the fishery products remaining in the group remaining after the expiration date exceeds a predetermined time from the selling point by multiplying the weighted value by 2 when purchasing aquatic products remaining in a group remaining after the expiration date is less than a predetermined time And a weight 1 is multiplied.

According to an aspect of the present invention, a recommender's point is calculated differently depending on the case where a recommender directly purchases an article and a recommender does not directly recommend the article.

According to an aspect of the present invention, a recommender having a large number of friends can receive more recommender points.

According to an embodiment of the present invention, a recommender can easily recommend an article to an acquaintance through a smart phone message, and when a purchase operation for the recommendation action occurs, a recommender is given appropriate compensation, A point of sale of a fishery product can be provided by differentiating the point according to the recommendation behavior and facilitating the inventory process with an imminent expiration date.

1 is a block diagram showing a configuration of a marine product sales recommendation system according to an embodiment of the present invention.
FIG. 2 is a diagram illustrating a process of calculating a point to a recommender in accordance with a purchase behavior of a first purchaser and a second purchaser according to an embodiment of the present invention.
FIG. 3 is a diagram illustrating a screen displayed on a smartphone of a marine product sales recommendation system according to an embodiment of the present invention.
4 is a flowchart illustrating an operation of a marine product sales recommendation system according to an embodiment of the present invention.

The above and other objects, features and advantages of the present invention will be more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which: FIG. BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention and the manner of achieving them will become apparent by reference to an embodiment which will be described in detail below with reference to the accompanying drawings.

1 is a block diagram showing a configuration of a marine product sales recommendation system 100 according to an embodiment of the present invention.

1, a fish sales promotion recommendation system 100 according to an embodiment of the present invention includes a first buyer index calculating unit 10, a second buyer index calculating unit 20, a recommendation point calculating unit 30, A classifying unit 31, and a weighting point calculating unit 32. [

First, the first buyer's index calculating unit 10 may calculate a first buyer's index by calculating a recommendation point corresponding to a purchasing behavior of the first purchaser 50 recommended by the recommender 40 directly.

Here, the first buyer's index calculating unit 10 may calculate the first buyer's index as shown in Equation (1) below.

[Equation 1]

은 제 1구매자 지수, 변수

는 구매물품의 가격, 변수

는 친구의수(95), 변수

는 구매물품분류지수를 각각 의미한다.Here,

Is the first buyer index, variable

The price of the purchased item, the variable

(95), the number of friends

Quot; refers to the purchase item classification index.

Also, the second buyer's index calculating unit 20 may calculate a second buyer's index by calculating a recommender's allocation point corresponding to a purchase behavior of the second buyer 60 recommended by the first buyer 50. [

Here, the second buyer's index calculating unit 20 may calculate the second buyer's index as shown in Equation (2) below.

&Quot; (2) "

는 제 2구매자 지수, 변수

는 구매물품의 가격, 변수

는 친구의수(95), 변수

는 구매물품분류지수를 각각 의미한다.Here,

Is the second buyer index, variable

The price of the purchased item, the variable

(95), the number of friends

Quot; refers to the purchase item classification index.

That is, for the purchasing behavior of the first purchaser 50 directly recommended by the recommender 40, points are calculated as in Equation (1), and the second purchaser 60 through the direct recommendation of the first purchaser 50 , The recommender's point can be calculated differently from Equation (2).

는 추천인(40)이 특정 물품을 후속 구매자에게 추천 했을 때, 상기 특정 물품을 그대로 구매한 경우와, 상기 특정 물품을 구매하지 않았지만 상기 추천인(40)의 추천과정을 통해 관련 물품을 구매한 경우에 대해 구매물품분류지수를 주고 이에 따라 상이하게 포인트가 계산될 수 있도록 하는 것을 특징으로 한다. Further, when referring to the above-mentioned equations (1) and (2)

In the case where the recommender 40 recommends a specific article to a subsequent purchaser and the related article is purchased as it is and when the related article is purchased through the recommendation process of the recommender 40 without purchasing the specific article So that points can be calculated differently depending on the purchased article classification index.

에는 상수값 1이 대입되며, 이에 따라 아래와 같이 [수학식 3]을 통해 제1 구매자 지수가 산출될 수 있다.For example, when the first purchaser 50 purchases a recommended article recommended by the recommender 40,

The first buyer's index can be calculated through Equation (3) as follows.

&Quot; (3) "

에는 상수 2가 대입되며, 이에 따라 아래와 같이 [수학식 4]을 통해 제2 구매자 지수가 산출 될 수 있다.Here, when the first purchaser 50 does not purchase the recommended article recommended by the recommender 40 but purchases the related article through the recommendation process of the recommender 40,

The second buyer's index can be calculated through Equation (4) as follows.

&Quot; (4) "

는 친구목록(94)에 등록된 친구의 수(95)를 나타내는 변수로, 추천인(40)이 자신의 친구목록(94)에 많은 친구를 보유 하고 있을 경우, 이에 따라 추가적으로 추천인 포인트를 할당 받을 수 있도록 하는 것을 특징으로 한다. Further, when referring to the above equations (1) and (2)

Is a variable indicating the number 95 of friends registered in the friend list 94. When the recommender 40 has many friends in his friend list 94, .

가 정해지고, 추천인(40)의 친구목록(95)의 친구의수(96)가 200명인 경우,For example, as shown in Equation (3)

And the number of friends 96 in the friend list 95 of the recommender 40 is 200,

에 상수 200을 대입하여

이므로, 하기 [수학식 5]와 같이 산출 될 수 있다.The variable

By assigning a constant of 200 to

, It can be calculated as the following equation (5).

&Quot; (5) "

Accordingly, the recommender 40 can calculate a point of 3.6% of the purchased item amount with respect to the purchase action.

The weight classifying unit 31 classifies the aquatic products to be sold according to the expiration date, and the weighting point calculating unit 32 multiplies the purchases of the first buyer and the second buyer by a weight based on the class classification, And calculate weighted points.

In one embodiment, the classifying section 31 classifies the marine products sold as a group in which the shelf life has remained below a predetermined time from the point of sale, and a group in which the shelf life exceeds the predetermined time from the sale point , The recommendation point calculating unit 32 multiplies the weighted value 2 by the weighting factor when the aquatic products remaining in the group remaining after the expiration date is less than a predetermined time from the selling point, If you buy aquatic products, you can multiply by a weight of 1. Through this, it is possible to smoothly proceed with inventory processing by inducing recommendation and sales for items with an imminent expiration date.

The recommender point calculating unit 30 may calculate a final recommender point through the sum of the first buyer index, the second buyer index, and the weighted points calculated in the same manner as described above.

Herein, the first buyer index and the second buyer index are defined only for a single purchase behavior, and a recommendation point can be calculated for a plurality of buyers and a plurality of purchase activities, respectively.

2 is a diagram illustrating a process of calculating a point to a recommender 40 in response to a purchase action of a first purchaser 50 and a second purchaser 60 according to an embodiment of the present invention.

2, the purchase behavior of the first purchaser 50 generated through the direct recommendation of the recommender 40 and the purchase behavior of the second purchaser 60 generated through the direct recommendation of the first purchaser 50 It shows the process in which recommender points are calculated.

More specifically, the first buyer 50 can be a plurality of members belonging to the first buyer group 70, wherein a first buyer's index is calculated for each of the plurality of first buyers 50, . ≪ / RTI >

Also, the second buyer 60 may be a plurality of members belonging to the second buyer group 80, and a second buyer's index may be calculated for each of the plurality of second buyers 60, .

FIG. 3 is a diagram illustrating a screen displayed on a smartphone of a marine product sales recommendation system according to an embodiment of the present invention.

Referring to FIG. 3, menus that can be displayed when the marine product sales recommendation system 100 is displayed on the screen in using a shopping mall using a smartphone are shown.

More specifically, as shown in FIG. 3, the marine product sales recommendation system display 90 includes the member information 91, point details 92, purchase details 93, and friend list 94 of the recommender 40 As shown in FIG. 3, one of the menus can be activated by clicking, and the activated menu can be displayed on the display screen in more detail.

In FIG. 3, the friend list 94 menu is activated and the friend list 94 is displayed in detail. When the friend list 94 is displayed in detail, the number of registered friends 95, the name of the registered friend, the registered friend is the Facebook interlocked friend 96, and the friend who is the cacao talk interlocked friend 97 can be expressed.

4 is a flowchart illustrating an operation of the marine product sales recommendation system 100 according to an embodiment of the present invention.

Referring to FIG. 4, in step 10, the recommender 40 can synchronously register the friend list 94 and provide it to the next step.

Here, the friend list 94 can be registered by synchronizing the SNS friend list. For example, a friend list of a cacao talk or a Facebook can be registered as a friend list 94 in a shopping mall where a purchase item can be recommended .

In step 20, the recommender 40 may select a particular item and recommend purchasing to one or more of the friends in the friend list 94. [

In step 30, the recommender 40 may recommend the purchase of the subsequent purchaser.

In step 40, it may be determined whether the purchased item is a specific article recommended by the recommender 40 or a related article other than the specific article, and may be provided to the next step.

는 1이 될 수 있다.In step 41, when the purchase item that has made the purchasing purchase is a purchase of the specific article recommended by the recommender 40, the variable indicating the purchase article classification index

Can be one.

는 2가 될 수 있다.If it is determined in step 42 that the purchased item is not related to the specific item recommended by the recommender 40,

Can be two.

에 대입하여 친구의 수(95)에 따라 상이하게 추천인 포인트를 산출하여 다음 단계로 제공할 수 있다.At step 50, the number of friends (95) of the synchronously registered friend list (94)

To calculate the recommendation point differently according to the number of friends 95 and to provide it to the next step.

에 구입물품의 가격이 대입되어, 최종적으로 추천인 포인트를 산출할 수 있다.In step 60, the price variable of the article

The price of the item to be purchased is substituted, and finally the recommender's point can be calculated.

As described above, according to the embodiment of the present invention, in the recommender system in the electronic commerce, it is possible to easily recommend the article to the acquaintance through the smart phone message, and when the follow- Compensation is given so that the recommendation behavior can be continuously induced.

As described above, it is to be understood that the technical structure of the present invention can be embodied in other specific forms without departing from the spirit and essential characteristics of the present invention.

While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. Therefore, the embodiments disclosed in the present specification are intended to illustrate rather than limit the present invention, and the scope and spirit of the present invention are not limited by these embodiments. The scope of the present invention should be construed according to the following claims, and all the techniques within the scope of the present invention should be construed as being included in the scope of the present invention.

100: Aquatic products recommendation system
10: First Buyer Index Calculation Section
20: Second Buyer Index Calculation Section
30: Referrer point calculation unit
31: Classification Division
32: weight point calculating unit
40: Referrer
50: 1st buyer
60: 2nd buyer
70: First Buyer Group
80: 2nd buyer group
90: Seafood sales recommendation system display
91: Member Information
92: Points History
93: Purchase history
94: Friends list
95: Number of Friends
96: Friends with Facebook
97: Friends of KakaoTalk interlocking
98: Smartphone

Claims (6)

A classification section for classifying the aquatic products sold according to the expiration date;
A first buyer index calculating unit for calculating a recommender allocation point corresponding to a purchasing behavior of a first purchaser directly recommended by a recommender to calculate a first buyer index;
A second buyer index calculating unit for calculating a recommender allocation point corresponding to a purchase behavior of a second buyer recommended by the first buyer and calculating a second buyer index;
A weighting point calculating unit for calculating a weighting point by multiplying purchased articles of the first purchaser and the second purchaser by weights according to the rating classification; And
A recommender point calculating unit for calculating a final recommender point by summing the first buyer index, the second buyer index, and the weighted points;
Aquatic product recommendation system. The method according to claim 1,
Wherein the first buyer's index calculating section calculates the first buyer's index by the following equation (1).
[Equation 1]

here,
variable

The first buyer index,
variable

The price of the purchased item,
variable

The number of friends,
variable

The purchase item classification index
Respectively. The method according to claim 1,
And the second buyer's index calculating section calculates the second buyer's index by the following equation (2).
&Quot; (2) "

here,
variable

The second buyer index,
variable

The price of the purchased item,
variable

The number of friends,
variable

The purchase item classification index
Respectively. The method according to claim 1,
Wherein the classifying unit comprises:
A group in which the expiration date of the aquatic products to be sold remains at a predetermined time or less from the point of sale, and a group in which the expiration date exceeds the predetermined time from the point of sale,
The recommender point calculation unit calculates,
When a fishery product of a group remaining after the expiration date is less than a preset time is purchased, a weighting factor is multiplied by 2. In the case where a fishery product of a group remaining after the expiration date exceeds a preset time from the selling point is purchased, And a sales promotion system for aquatic products. The method according to claim 2 or 3,
When a subsequent purchaser purchases an article recommended by the recommender,

Is defined as a constant 1, and when a related article is purchased, which is not a directly recommended article by the first recommender,

Is defined as a constant 2. The method according to claim 2 or 3,
The variable

Wherein the number of friends is the number of friends registered in the friend list to receive recommendation of the recommender.

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