KR20140031429A - Item recommend system and method thereof, apparatus supporting the same - Google Patents

Abstract

The present invention relates to a system and a method for recommending an item, and an apparatus supporting the same. Provided are: at least one user terminal accessing an item providing service apparatus, receiving and outputting item posting screen information, and receiving at least one piece of item recommendation information according to an item purchase history from the item providing service apparatus; and an item providing service apparatus generating and storing predefined related rules based on the item purchase histories of the user terminals, generating item recommendation information corresponding to at least a portion of the purchase history of a specific user terminal using the predefined related rules and providing the item recommendation information for the specific user terminal.

Description

Item Recommend System And Method, Apparatus supporting the same}

The present invention relates to an item recommendation, and in particular, an item recommendation system and method for supporting intelligently providing an item recommendation to a specific user terminal based on a purchase history of various user terminals in the process of providing at least one item on a network. And a device supporting the same.

With the advent of various e-commerce systems or shopping malls, the system for purchasing necessary goods or services in the home is becoming more common. However, in the virtual space called the Internet, it is not possible to directly view and compare products, which may cause reliability problems for the products, and also, there is a disadvantage in that appropriate information acquisition for a specific product is not provided. As a result, such a problem has caused a problem of restricting consumers to search only without purchasing a product in an internet shopping mall.

In addition, many consumers want to see and purchase various products through Internet shopping malls, but due to the emergence of internet shopping malls that provide too much information, it has become difficult to search for specific types of products desired by them.

Registered Korea Patent No. 10-1081947, registered on November 03, 2011 (Name: Hybrid recommendation method and system for large data)

Accordingly, the present invention has been proposed to solve the above-described problems of the related art, and provides an item recommendation system and method capable of recommending items highly likely to be purchased by various users, and an apparatus supporting the same.

In addition, an object of the present invention is to provide an item recommendation system and method and an apparatus for supporting the item recommendation, which can be performed quickly and effectively by effectively storing and retrieving a large amount of data through the introduction of a distributed data processing system.

The present invention for achieving the above object is connected to the item providing service device to receive and output the item posting screen information, receiving at least one item recommendation information according to the item purchase history provided by the item providing service device Generate and store predefined association rules based on at least one user terminal and history of purchasing items of the user terminals, and generate item recommendation information corresponding to at least a part of purchase history of a specific user terminal from the association rule. It provides an item recommendation system comprising an item providing service device provided to the user terminal.

The present invention also supports the provision of item posting screen information and signal transmission / reception for item purchase, and provides at least one item recommendation information based on predefined association rules based on history of purchasing items of user terminals and user terminals. And a device controller for generating item recommendation information corresponding to at least a part of a purchase history of a specific user terminal from an association rule and providing the same to the specific user terminal.

Here, the above-described item providing service apparatus may further include a device storage unit for storing the association rules and the purchase history of the user terminals.

Meanwhile, the device controller checks a purchase history of a specific user terminal, searches for association rules corresponding to items included in the purchase history, selects association rules to be used as a predetermined number of preliminary recommendation items based on a predetermined criterion, Items included in a predetermined schedule ranking may be generated as item recommendation information.

The specific user terminal may be at least one of a user terminal connected to the device communication unit and an unconnected user terminal that has performed prior consent for receiving item recommendation information.

In the above description, a certain criterion is at least one of support, reliability, and improvement, and support is a ratio of association rules including two specific products among the total association rules, and reliability is a ratio of all association rules including a specific product. The ratio of the association rules including the specific product and other specific products, and the degree of improvement is the ratio of the association rules generated based on the history of purchasing another specific product among the association rules including the specific product Can be.

Here, the device controller may calculate association rules in which at least one of the predetermined criteria is equal to or greater than a predetermined ratio, and calculate a predefined predetermined number of association rules among the association rules equal to or greater than a predetermined ratio as the preliminary recommendation item.

The device controller may configure the item recommendation information to include the same number of items as the number of purchase history of the user terminal, or configure the item recommendation information to include a predetermined number of predetermined items.

The present invention also provides a method for providing and distributing an association rule having a predetermined rule length based on an item purchase history of a user terminal by an item providing service apparatus, and the item providing service apparatus included in a purchase history of a specific user terminal. Calculating a predetermined number of preliminary recommendation items based on a predetermined number of association rules corresponding to the prepared items, and configuring the item recommendation information items within a predefined schedule rank among the calculated preliminary recommendation items by the item providing service device; And providing, by the item providing service device, the item recommendation information to the user terminal.

The method may include checking a purchase history of a user terminal that has accessed the item providing service apparatus, generating item recommendation information corresponding to a purchase history of the connected user terminal, and transmitting item recommendation information to the connected user terminal. It may further comprise the step of providing.

The method may further include checking a purchase history of a specific user terminal having a history of purchasing an item in the item providing service device, and constructing and providing item recommendation information based on the purchase history of the user terminal.

The generating of the item recommendation information may include at least one of configuring the item recommendation information to include the same number of items as the number of purchase history of the user terminal and configuring the item recommendation information to include a predetermined number of predetermined items. It may include the steps of.

In addition, the present invention provides a computer readable recording medium having recorded thereon a program for executing the above-described supporting method.

As described above, according to an item recommendation system and method and an apparatus supporting the same, the present invention can quickly provide an item recommendation that a user is likely to purchase, and thus can purchase a user's item. Make it more rational and easy to do.

1 is a view showing an example of a user purchase history for explaining the item recommendation function of the present invention.
2 is a diagram illustrating an example of an association rule calculated for applying an item recommendation function of the present invention.
3 is a block diagram illustrating a configuration of an item recommendation system according to an exemplary embodiment of the present invention.
4 is a block diagram illustrating in more detail the configuration of an item providing service device in the item recommendation system configuration according to an embodiment of the present invention.
FIG. 5 is a block diagram illustrating the configuration of the device controller of FIG. 4 in more detail.
FIG. 6 is a view for explaining distributed rule distribution storage of an item providing service apparatus according to an exemplary embodiment; FIG.
FIG. 7 is a diagram illustrating a user purchase history distributed storage of an item providing service apparatus according to an exemplary embodiment.
8 is a diagram illustrating a preliminary recommendation item search of an item providing service apparatus according to an exemplary embodiment of the present invention.
9 is a diagram illustrating one form of association rules for applying an item recommendation function of the present invention.
FIG. 10 is a diagram illustrating an example of a product purchase history in an item providing service apparatus having the association rules of FIG. 9.
11 is a view showing an item recommendation result according to the first method of the present invention.
12 is a diagram illustrating an item recommendation result according to a second method of the present invention.
13 is a flowchart illustrating the operation of the item providing service apparatus of the present invention.
14 is a view for explaining an example of MapReduce applied to the item recommendation function of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Note that, in the drawings, the same components are denoted by the same reference numerals as possible. Further, the detailed description of known functions and configurations that may obscure the gist of the present invention will be omitted.

It should be noted that the embodiments of the present invention disclosed in the present specification and drawings are only illustrative of the present invention in order to facilitate the understanding of the present invention and are not intended to limit the scope of the present invention. It will be apparent to those skilled in the art that other modifications based on the technical idea of the present invention can be carried out in addition to the embodiments disclosed herein. Hereinafter, each device, terminal, and support method of the purchase support system and system according to an exemplary embodiment of the present invention will be described.

1 and 2 are diagrams for explaining an association rule that may be generated in relation to a user purchase history in an item recommendation function according to an exemplary embodiment of the present invention.

1 and 2, it will be assumed that a plurality of user terminals purchase items as shown in FIG. 1, for example, specific goods as shown in the item providing service apparatus. That is, the first user terminal User 1 may have a history of purchasing Beer, Chicken and Milk, and the second user terminal User 2 may have a history of purchasing Beer and Cheese. In addition, the third user terminal (User 3) is Cheese, Boots, the fourth user terminal (User 4) is Beer, Chicken, Cheese, the fifth user terminal (User 5) is Beer, Chicken, Clothes, Cheese, Milk The sixth user terminal (User 6) may have a history of purchasing Chicken, Clothes, and Milk, and the seventh user terminal (User 7) has purchased Chicken, Milk, and Cloths, respectively.

The item providing service apparatus may then generate an association rule as shown in FIG. 2 based on the purchase history of the user terminals described above. In particular, the item providing service apparatus may generate various types of association rules according to the length of the association rule. For example, the item providing service apparatus may generate (Beer, Chicken), (Beer, Milk), (Chicken, Milk), and the like having a rule length of 2 as shown. Meanwhile, when the length of the rule is 3, the item providing service device may generate (Beer, Chicken, Cheese), (Chicken, Milk, Clothes) and the like as shown. That is, the item providing service apparatus may generate association rules corresponding to various combinations according to a predefined rule length based on a purchase history purchased by each user terminal. Each generated association rule may be distributed and stored in a plurality of distributed processing devices included in an item providing service device or separately managed. In the following description, an item providing service device will be described based on an example of generating and operating an association rule based on the rule length of 2.

Meanwhile, in order to determine the usefulness of the association rule, the item providing service apparatus of the present invention may use three components. That is, the item providing service apparatus supports the determination of the usefulness of the association rule based on at least one of support, confidence, and lift. To this end, the item providing service apparatus may derive each usefulness determination component from the association rules statistical result.

First, when the purchase history for each user is defined as one association rule or a transaction in FIG. 1, the support may correspond to the number of transactions including a specific product A and a product B among all transactions. Here, the goods A and the goods B are for illustrating different kinds of goods and may be any one of the goods shown in FIG. 1.

The aforementioned support degree may be defined by Equation 1 below.

[Equation 1]

s (A => B) = ∥ {T∈D│A∪B⊆T} ∥ / ∥D∥

Where s (A => B) is support, T is the number of transactions including commodity A and commodity B, and D may be the total number of transactions. In addition, A may mean product A and B may mean product B, and goods A and B may be specific products included in a purchase history of user terminals using the item providing service apparatus as described above. Accordingly, the degree of support may be the ratio of the federation rule including both product A and product B among the total association rules.

Reliability may mean a ratio of a transaction including products A and B at the same time to a transaction including product A. That is, the reliability may be a ratio of the association rules including the product A and the product B at the same time to the association rules including the product A. This reliability may be represented by Equation 2.

&Quot; (2) "

conf (A => B) = ∥ {T∈D│A∪B⊆T} ∥ / ∥ {T∈D│A⊆T} = s (A∪B) / s (A)

The degree of improvement represents the reliability of product A to product B of the reliability of product B. In other words, the degree of improvement may be the ratio of the transaction in which the purchase of the article B in the situation where the purchase of the article A of the purchase of the article B. Alternatively, the degree of improvement may be the ratio of the association rules for purchasing the commodity B in the context of purchasing the commodity A among the total association rules for purchasing the commodity B. If the improvement is less than 1, it means a negative relationship, and if it is greater than 1, it can be interpreted as a positive relationship. The improvement may be defined by Equation 3.

&Quot; (3) "

Lift (A => B) = conf (A => B) / s (B) = s (A∪B) / s (A) s (B)

In the above, the association rule and the usefulness determination component for item recommendation according to an embodiment of the present invention have been described. Hereinafter, the system configuration, the configuration of the item providing service apparatus, and the item recommendation method of performing the item recommendation on the basis of the above-described association rule and availability determination component will be described in more detail.

3 schematically illustrates an item recommendation system configuration according to an embodiment of the present invention.

Referring to FIG. 3, the item recommendation system 10 of the present invention may include at least one user terminal 100 and an item providing service apparatus 200, and the user terminal 100 and the item providing service apparatus 200. ) May further include a configuration of the communication network 300 for communication connection.

The item recommendation system 10 of the present invention described above may provide an item posting screen including at least one item in order for the item providing service apparatus 200 to guide and sell the at least one item to the user terminal 100. have. In particular, when the user terminal 100 accesses the item providing service apparatus 200, the item providing service apparatus 200 generates and stores an association rule based on the item purchase history of the user terminals 100, and based on this, Item recommendation information may be provided to the user terminal 100. In this case, the item providing service apparatus 200 may extract item recommendation information based on a purchase history of the user terminal 100 and provide the same.

To this end, the communication network 300 may support to establish a communication channel between the user terminal 100 and the item providing service apparatus 200. That is, the communication network 300 may support access to the item providing service apparatus 200 of the user terminal 100, transmission and reception of item posting screens, transmission and reception of item recommendation information, and transmission and reception of signals for item purchase. Here, the communication network 300 may be configured as an internet network device when the user terminal 100 is a terminal such as a desktop. When the user terminal 100 is a terminal supporting a mobile communication function, for example, a mobile communication network device may be used. It may be configured with a base station and a controller.

The user terminal 100 may be connected to the communication network 300 using a communication unit, and may be connected to the item providing service apparatus 200 connected to the communication network 300. The user terminal 100 may receive and output information corresponding to an item posting screen provided by the item providing service apparatus 200. Accordingly, the user terminal 100 may output an item posting screen for viewing and purchasing at least one item on the display unit. In this case, the user terminal 100 may receive and output the item recommendation information provided by the item providing service apparatus 200 together with the item posting screen information. The provided item recommendation information may include at least one recommendation item selected by the association rule and the usefulness determination component described above with respect to a specific item such as a product, a service, or an app purchased by the corresponding user terminal 100.

When an input signal for selecting a specific item from the item recommendation information is generated, the user terminal 100 requests the item providing service apparatus 200 for detailed information of the corresponding item, and receives the item detail information from the item providing service apparatus 200. When received, it can be output to the display. Thereafter, when an input signal for purchasing a specific item is generated according to a user's request, the user terminal 100 transmits a message for purchasing the corresponding item to the item providing service apparatus 200 and performs an item purchase according to a predefined procedure. Can be.

Meanwhile, when the user terminal 100 purchases specific items, the information on purchasing the items may be provided to the item providing service apparatus 200. In this case, the purchase history of the items of the specific user terminal 100 provided may be distributed and stored according to the above-described association rule, thereby contributing to the item recommendation information generated later.

The item providing service apparatus 200 is an apparatus for providing an item posting screen so that the user terminal 100 can view and purchase a specific item, and support to perform a specific item purchase at the request of the user terminal 100. . In particular, the item providing service apparatus 200 according to the present invention generates an association rule based on a purchase history of the user terminals 100, and an item of the specific user terminal 100 based on the association rule and a predefined usability determination component. Recommendation information may be generated. The item providing service apparatus 200 may provide the generated item recommendation information to the corresponding user terminal 100. The item providing service apparatus 200 may support a distributed processing scheme for storing and using an association rule.

In other words, when the specific user terminal 100 is connected, the item providing service apparatus 200 may provide the recommendation item to the user terminal 100 based on the purchase history and association rules of the user terminal 100. It may be configured to include a plurality of data nodes to distribute and store the purchase history of the 100, and to support the storage and retrieval of association rules.

Here, each data node supports the MapReduce function, and based on this, create and store association rules, and evaluate the association rules based on a predefined usability determination component.

The evaluation result evaluated by each data node may be used to select a preliminary recommendation item, and the item providing service apparatus 200 lists the association rules based on the purchase history and the identification information of the user terminal 100 and defines predefined usability. The determination component may be applied to select association rules having a predetermined evaluation value among the association rules.

In addition, when the specific user terminal 100 purchases an item, the item providing service apparatus 200 may generate the item purchase information as a new association rule by applying a predefined association rule length and store it in at least one data node. Can be controlled.

As described above, the item recommendation system 10 of the present invention classifies and stores the history of purchasing a plurality of user terminals 100 according to a predefined association rule, and stores the association based on a usefulness determination component. After evaluating the rules to extract items above a certain evaluation value, it is possible to support providing a predetermined number of extracted items according to a predefined criterion. Accordingly, the specific user terminal 100 provides more reliable item recommendation information based on the purchase history of other user terminals who purchased the item using the item providing service apparatus 200 while using the item providing service apparatus 200. Can be obtained. The present invention can support the user who purchased a particular item to properly reflect the needs of users who purchased the same item by reflecting the need for other items associated with the item.

Meanwhile, according to an embodiment of the present invention, the item providing service apparatus 200 stores association rules using distributed data nodes together with access to the user terminal 9100 and support for item purchase, and also evaluates them based on the usefulness determination component. Although calculating the result as an example, the present invention is not limited thereto, and the user terminal 100 may be configured by using distributed data nodes and an item service apparatus that supports connection and purchase of an item according to a system design scheme. It may be divided into a distributed processing service device 200 that stores the purchase history of these, checks the association rules and determines the usefulness.

4 is a diagram illustrating in more detail the configuration of the item providing service apparatus 200 according to an embodiment of the present invention.

Referring to FIG. 4, the item providing service apparatus 200 of the present invention may include a configuration of the device communication unit 210, the device storage unit 250, and the device control unit 260.

The item providing service apparatus 200 having such a configuration may support connection of the user terminal 100 based on the device communication unit 210 and provide item posting screen information to the user terminal 100. In this case, the item providing service apparatus 200 may calculate the association rules evaluated based on the usefulness determination component based on the purchase history of the user terminal 100 and provide them as item recommendation information. To this end, the item providing service apparatus 200 may use a distributed processing system for storing and operating an association rule.

The device communication unit 210 supports communication channel establishment with the user terminal 100 through the communication network 300. The device communication unit 210 may provide an item posting screen to the user terminal 100 under the control of the device control unit 260. Thereafter, when the device communication unit 210 requests a purchase of a specific item on the item posting screen, the device communication unit 210 may transmit a corresponding purchase request message to the device controller 260.

In particular, the device communication unit 210 may transmit item recommendation information according to a purchase history of the connected user terminal 100 to the corresponding user terminal 100 under the control of the device control unit 260. The device communication unit 210 may receive the item purchase request information presented through the item recommendation information from the user terminal 100 and provide the received item purchase request information to the device controller 260. In addition, the device communication unit 210 may support data transmission and reception required during the item purchase process.

The device storage unit 250 may store an operation program for operating the item providing service device 200 and information for recommending an item of the present invention. In particular, when storing the association rule in a plurality of data nodes, the device storage unit 250 may include a user log inquiry list 251 to support retrieval of information on the association rules. Here, the user log inquiry list 251 may include address information on which data nodes the purchase history information of the specific user terminal is stored. The device controller 260 may create a search message for searching for related rules based on the information included in the user log inquiry list 251 and control the search message to be transmitted to the data nodes.

The device controller 260 is a component that supports overall operation of the item providing service device 200 for purchasing recommendation support according to the present invention. That is, the device controller 260 may support device connection of the user terminal 100, provision of an item posting screen, inquiry of an item purchase history, provision of item recommendation information, and purchase processing according to an item purchase request. In particular, the device controller 260 checks identification information of the user terminals 100 and checks item purchase history information of the user terminal 100 that is connected or has a connection history. The device controller 260 may collect association rules based on the corresponding item purchase history information and create item recommendation information based on the related rules. The written item recommendation information may be provided to each specific user terminal 100. To this end, the device control unit 260 may include a configuration as shown in FIG.

5 is a diagram illustrating in more detail the configuration of the device controller 260 of the item providing service device 200 configuration of the present invention. Meanwhile, FIG. 6 is a diagram for describing distributed association rule storage, FIG. 7 is a diagram for describing storage of purchase history for each user, and FIG. 8 is a diagram for describing association rule inquiry for each user.

5 to 8, the device controller 260 may include an association rule distributed storage support unit 261, an association rule inquiry unit 263 for each user, and a recommendation information provider 265.

The association rule distributed storage support unit 261 generates an association rule based on the purchase history of the user terminals 100 using the item providing service apparatus 200, and generates the association rule in the data node as shown in FIG. 6. This configuration supports saving. In FIG. 6, if eight result product IDs are provided for eight head product IDs, each of which has specific support, reliability, and improvement levels, the association rules are applied to a plurality of data nodes RDB # 1 to RDB #P. Indicates that it can be stored separately. In this case, association rules composed of the same head product IDs may be stored in each data node, and association rules of the same head product ID may be divided and stored in a plurality of data nodes according to the data amount of the association rule.

The association rule distributed storage support unit 261 may collect information on the purchased items when purchasing items provided by the various user terminals 100, the item providing service apparatus 200. The association rule distributed storage support unit 261 may generate an association rule based on a rule length of, for example, a rule length of 2, based on the relationship between items. In addition, the association rule distributed storage support unit 261 may distribute and store the generated association rules in data nodes in a predefined format or in a specific data node. The association rules stored at this time may be stored in a form including a head product ID, a result product ID, support, reliability, and improvement. Here, the head product ID may correspond to a search item for searching for the result product ID.

For example, when a specific user terminal 100 has a history of purchasing a specific product, the purchased product may correspond to a head product ID. The resulting product ID may be an item that is included in the item recommendation information to be provided to the user terminal 100 as a stored product paired with the head product ID. The degree of support, reliability, and improvement may be a determining component that determines whether a specific result product ID is included in the item recommendation information. In particular, according to an item providing service design scheme, at least one of support, reliability, and improvement may determine whether to use the resultant product ID as item recommendation information. That is, the item recommendation information may be determined based on any one of three usability determination components, two of three usability determination components, and one of three usability determination components according to an item providing service design scheme. For example, according to an item providing service design scheme, it may be determined to include the searched result product ID in the item recommendation information using only reliability.

When the user terminal 100 accesses the item providing service apparatus 200, the user-specific association rule inquiry unit 263 may check the purchase history of the user terminal 100 from a specific data node. For this, the user-specific association rule inquiry unit 263 may control to store the item purchase history of the user terminals 100 using the item providing service apparatus 200 in specific data nodes, as shown in FIG. 7. .

Meanwhile, the association rule inquiry unit 263 for each user extracts preliminary recommendation items having a usability determination component having a predetermined value or more based on the purchase history of the specific user terminal 100. In this case, the association rule inquiry unit 263 for each user may search for an RDB, that is, a data node, to bring the actual association rule based on the hash value of the purchase item ID for each user as illustrated in FIG. 8. Referring to FIG. 8, the items included in the purchase histories of user ID 1 stored in the data node # 1 are stored in the association rules stored in the plurality of data nodes RDB # 1 to RDB #P, respectively. Items which become a key value to be used and whose at least one of the usefulness determining components among the association rules stored in the respective data nodes are equal to or greater than a predetermined value may be provided as preliminary recommendation items.

In this case, the association rule inquiry unit 263 for each user may provide preliminary recommendation items corresponding to the specific item according to the purchase history to the recommendation information provider 265. In this process, the user-specific association rule inquiry unit 263 defines only a predetermined number of purchase histories as a valid purchase history when the purchase history of the user terminal 100 is greater than or equal to a certain number, and the association according to the corresponding purchase history. You can query the rules. Alternatively, the association rule inquiry unit 263 for each user may define a certain period when the purchase history is more than a certain number, and define only the items purchased within the latest or predefined corresponding period as a valid purchase history. The association rule inquiry unit 263 for each user may define all items as a valid purchase history when the number of items included in the purchase history is less than or equal to a certain number, and support to search for preliminary recommended items for each item.

When the preliminary recommendation items are delivered from the association rule inquiry unit 263 for each user, the recommendation information providing unit 265 applies the usability determination component to the delivered preliminary recommendation items and selects the recommendation items. For example, the recommendation information providing unit 265 may sort the delivered preliminary recommendation items in the order of reliability, and determine the preliminary recommendation items that fall into a predetermined rank in the order of high reliability as the recommendation item. In this process, when there are preliminary recommendation items having the same rank, the recommendation information provider 265 may set higher priority of the preliminary recommendation items of the recent purchase history item.

Meanwhile, in the item recommendation function method, the first method is a method of generating a recommendation product proportional to the number of purchased products for each user. For each user, P number of B_u purchased product IDs and each purchased product ID of the user are Head. You have an association rule. Here, the recommendation item extraction criterion among the P association rules provided as the preliminary recommendation items may be used at least one of the usability determination component. For example, the item recommendation criteria may use all of the support, the reliability, and the improvement, or some of the reliability and some of the improvement.

In the following description, a description will be made based on an example of extracting a recommendation item based on reliability. First, the first method is to generate B_u recommended products for a user who has purchased B_u. The following process is repeated from the B_u first products to the B_uth products (i = 1, 2, ..., B_u). In this process, the order of all purchased products may be simply sorted by the order of the purchased product ID, or when the B_u of the purchased product history is too large. Alternatively, the association rule may be sorted in the order of purchase product ID based on user preference.

Meanwhile, the item providing service apparatus 200 selects a rule having the highest confidence value from the association rule of which the product ID of the head is B_i (i = 1, 2, ..., B_u) and stores the consequent product ID. In addition, the item providing service apparatus 200 searches an association rule of which the product ID of the head is B_i from the next purchased product, selects a rule having the highest confidence value, and brings the Consequent product ID of the corresponding rule. The device 200 checks whether the imported goods ID already exists in the recommended goods generated from the previous purchased goods. If the corresponding recommended product already exists, the item providing service apparatus 200 obtains the Consequent product ID of the next higher-trust rule from the association rule of which the product ID of the head is B_i and repeats the existence of the same recommended product. do. On the other hand, if the association rules P extracted for each purchase history are significantly smaller than B_u or there are too many B_u, the consequent product ID does not overlap with the previous recommendation result even if all P association rules with the product ID of Head are B_i. May not be obtained. Accordingly, P to be applied to the association rules for each purchase history may be experimentally adjusted in consideration of a decrease in computation speed according to system load and the number of recommended items to be provided.

On the other hand, if there are too many B_u, for example, a user who purchases 10,000 items may be difficult to use even if they generate as many recommended products. Therefore, the item providing service apparatus 200 may designate and use the number K of products to be created at the maximum for each user. In this case, the item providing service apparatus 200 may generate as many as K pieces when K is smaller than B_u and B_u pieces in order when K is larger than B_u, and may not generate a recommendation product for subsequent products. Through this process, the item providing service apparatus 200 may generate as many K items as the number of B_u items or B_u items for each user.

The second method in the item recommendation function method is a method of generating a specific number of recommended products regardless of the number of purchased products for each user. The item providing service apparatus 200 may collect P association rules including B_u purchase goods IDs and corresponding purchase goods IDs of the corresponding user for each user. Similarly to the first method, in the second method, the item providing service apparatus 200 may extract association rules to be used as a preliminary recommendation item based on at least one of support, reliability, and improvement included in the usefulness determining component. The second method is to generate K recommended products for a user who purchased B_u.

Here, K is a value determined in terms of applied services and products. To select K recommended items, do the following: First, the item providing service apparatus 200 prepares a storage for storing up to K recommended product IDs. The item providing service apparatus 200 sorts the total (B_u X p) association rules in at least one of the usability determining components, for example, in order of reliability. The item providing service apparatus 200 starts with the association rule with the highest confidence level and repeats the following process until K pieces are added.

The item providing service apparatus 200 checks whether a Consequent product ID of the current rule exists in a store storing existing K pieces, and adds it to the recommended product if it does not exist. When there are a plurality of association rules having the same reliability and different Head product, Consequent product ID, and the total number of stored products does not exceed K, the item providing service apparatus 200 may use all the Consequent product IDs of each association rule. . In the process of adding all the association rules having the same reliability to the recommended product store at a specific confidence value, if the number of the association rules exceeds K, the item providing service apparatus 200 selects the number to be arbitrarily K.

For example, if K = 100 and 98 are stored in order of reliability, and there are 4 associative rules with the next highest confidence value of 0.56, and the consequent product ID of each associative rule is different, the item providing service The apparatus 200 may arbitrarily select two of the four product IDs and add them to the recommended product. Here, the item providing service apparatus 200 does not select a recommendation product randomly in the recommendation product addition process, records the appearance frequency of the head product ID of the association rule used to generate the recommendation product, and has the lowest head product ID. Can be used in order of association rule. Through such an option, the item providing service apparatus 200 may prevent a case where a large number of Consequent products of the association rule in which the corresponding head product exists are recommended as a recommendation product because the reliability value of the association rule in which the specific product is the Head product is high. .

On the other hand, if the total sum of P, the number of association rules for each product in each purchase history, is significantly smaller than K, it is difficult to generate K recommended products, so P may be designated as a multiple of K.

This ratio may be appropriately adjusted according to the K value and the type of service. For example, an item such as a book may have an average number of purchased products per user, while an item such as music content may be differentially adjusted according to a service type such as tens / day.

In addition, the number of association rules generated may vary according to the support, reliability, and improvement values, which are the usefulness judgment components that are specified when creating the association rule. When the number of association rules generated is too small, the K value is also changed. If you specify a large, too large value for P as a multiple of K, you may not get P association rules for each product. Accordingly, the designer who designs the item providing service apparatus 200 may experimentally adjust the usability determining component and the P value. Through the above-described process, the item providing service apparatus 200 may generate K recommendation products for each user.

In the above-described first and second methods, the item providing service apparatus 200 may apply the first method of providing three recommended products to a user who has purchased three items, or the association rule may be applied even if three items have been purchased. One of the second methods of recommending K products as long as they exist may be selectively operated, or the two methods may be used in combination according to the system designer's intention.

9 to 12 are data arbitrarily created for the application of the association rule of the present invention, and show association rules arranged based on reliability among the usability determination components. 9 described above shows association rules generated based on a purchase history in a specific item providing service apparatus 200. Meanwhile, when the user of the user terminal 100 purchases a certain number of goods as shown in FIG. 10, the item providing service apparatus 200 provides the recommendation result as shown in FIG. 11 by the first method or the second method. Can be applied to provide a recommendation result as in FIG. 12. K = 5.

As described above, the present invention can recommend products that are most statistically related based on their purchase history for each user. In particular, the present invention may generate and support a recommendation product having a high relation in proportion to the number of purchases per user, or generate and support the number required by the service device regardless of the number of purchases per user. Such an item recommendation method of the present invention may provide a required number of recommendation results for users who do not have a recommendation result or a desired number of recommendation results by other collaborative filtering methods in combination with other recommendation methods.

FIG. 13 is a diagram illustrating a method of operating an item providing service apparatus 200 according to an exemplary embodiment.

Referring to FIG. 13, the item providing service apparatus 200 may have a standby state in step 1301. That is, the item providing service apparatus 200 may activate the device communication unit 210 so that the user terminals 100 can access and prepare for providing a service page according to the connection of the user terminals 100. In addition, the item providing service apparatus 200 may support performing a procedure for registering a member of each user terminal 100. In operation 1303, the item providing service apparatus 200 confirms the connection of the specific user terminal 100. If there is no connection of the user terminal 100 in this step, the process may branch to step 1301 to maintain the standby state.

When the specific user terminal 100 accesses in step 1303, the item providing service apparatus 200 may perform authentication of the corresponding user terminal 100. Meanwhile, the item providing service apparatus 200 may check the purchase history of the corresponding user terminal 100 based on the unique identification information of the user terminal 100. To this end, the item providing service apparatus 200 may control to store the purchase history in a specific data node in the process of purchasing an item for each user terminal 100 in advance. The item providing service apparatus 200 may check the purchase history of the user terminal 100 stored in the specific data node based on the identification information of the user terminal 100. If the purchase history is confirmed, the item providing service apparatus 200 generates item recommendation information by using at least one of the above-described first and second methods based on the corresponding purchase history in step 1305, and the user terminal may generate the item recommendation information. 100 may be provided.

Next, the item providing service apparatus 200 checks whether the corresponding user terminal 100 purchases the product in step 1307, and when the product is purchased, branches to step 1309 and generates an association rule for the product purchase according to the association rule. It can support saving to data node. That is, when the specific user terminal 100 purchases an item, the item providing service apparatus 200 may support to generate an association rule based on the corresponding item purchase history and apply it to the previously generated association rule.

Next, the item providing service apparatus 200 checks whether the user terminal 100 is released in step 1311, and when the user terminal 100 is released from connection, returns to step 1301 to support the following processes to be performed again and to maintain the connection. Branches can be branched back to step 1305 to assist in re-processing.

The above-described item providing service apparatus 200 of the present invention may use at least one distributed data node in the process of storing the association rule for the product purchase history, and especially when the user's data is large, It can be distributed and stored on multiple devices. The item providing service apparatus 200 according to the present invention may effectively operate an item recommendation procedure for each user in a distributed environment when there are distributed association rules and a large user purchase history.

The present invention described above may be implemented on a MapReduce distributed framework. However, the present invention may obtain the same result by applying the same technology when there is the same data even in a distributed environment. MapReduce is a software framework designed by Google to support distributed computing. This framework was developed to support parallel processing in large clusters of petabytes of large data in untrusted computers. This framework consists primarily of a functional base called Map and Reduce, which is commonly used in functional programming. Hadoop is open source, supporting distributed applications that run on large clusters of computers that can handle large amounts of data. The distributed processing system of the present invention implements Hadoop Distributed File System (HDFS) and MapReduce (HDFS), which can replace the Google file system. In the form of HDFS file storage, Hadoop's large files are stored on multiple computers. A datanode corresponding to each computer may be a unit for actually storing and processing a file. And for fault tolerant, Hadoop can store the same file for up to X replications. That is, even if a file (information) stored in one data node disappears, it can be recovered by using a file stored in another data node. From the user's point of view, the file appears to be in one place, but internally it exists for as many replications. The default is usually set to 3.

Input data present in HDFS is split into smaller units through input splits. A central coordination process called Job Tracker assigns each input split to a Map task for a particular data node, taking into account the physical location of the file. The task tracker for each data node receives and processes each map task. The (key, value) values generated by a map or combiner at a particular data node are passed through the network to the reducer at a particular data node if necessary. The Reduce task sorts the (key, values) sent as the result of the map task by key, executes the reduce function, and stores the result in HDFS. The function that performs the Map function is called mapper (), and the function that performs the Reduce function is called reducer (). A single data node can run any number of mapper or reducers simultaneously.

14 illustrates Word Count as an example of a process of applying a usefulness determining component of an association rule of the present invention.

In FIG. 14, it is assumed that three lines as inputs exist on the HDFS, and each row exists in one data node or is divided into multiple data nodes. The data node storage method may vary substantially depending on the file size. Split allocates a certain amount of data from each row or all input data to a specific mapper of a specific data node. In the figure, a total of three mapper are executed, and each mapper receives one row of data as input. The mapper reads one row, separates the data with commas (,), and outputs each word as a Key and the number of occurrences of each word (= 1) as a Value. The output (Key, Value) values are arranged so that the value for the same key can be read from the same data node. The Reducer of each data node performs the desired function by reading the incoming Value value (repeat of 1 in this example) for a particular key (word in this example). In the case illustrated in the drawings, a simple summation is illustrated. For Beer, two values of '1,1' come in, and they are simply summed up and then the data (key, value) = (Beer, 2) is output to HDFS. When all reducers have finished running, when you look at HDFS, you can see the full result.

In the above description, the related rules and the usefulness determination component are used to provide the item recommendation information to the user terminal 100 connected to the item providing service apparatus 200 as an example. However, the present invention is not limited thereto. no. That is, the item providing service apparatus 200 may generate item recommendation information based on a purchase history of user terminals not connected according to a designer or an administrator policy, and may generate the specific item recommendation information to specific user terminals that are not connected. Method For example, it may be provided through e-mail or text. In this case, the item providing service apparatus 200 may obtain prior consent of the user terminals 100 to provide a corresponding email or text.

Meanwhile, the item recommendation method according to the embodiment of the present invention described above may be implemented in the form of program instructions that can be executed by various computer means and recorded in a computer-readable recording medium. At this time, the computer-readable recording medium may include program commands, data files, data structures, and the like, alone or in combination. On the other hand, the program instructions recorded on the recording medium may be those specially designed and configured for the present invention or may be available to those skilled in the art of computer software.

The computer-readable recording medium includes a magnetic recording medium such as a magnetic medium such as a hard disk, a floppy disk and a magnetic tape, an optical medium such as a CD-ROM and a DVD, a magnetic disk such as a floppy disk, A magneto-optical media, and a hardware device specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. The program instructions also include machine language code, such as those generated by the compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the present invention.

In the above description of the preferred embodiments through the specification and drawings for the item recommendation operation according to an embodiment of the present invention, although specific terms have been used, it is only easy to explain the technical details of the present invention and to help the understanding of the invention. It is only used in a general sense for this purpose, the present invention is not limited to the above-described embodiment. That is, it is apparent to those skilled in the art that various embodiments based on the technical idea of the present invention are possible.

The present invention relates to an item recommendation system and method and an apparatus supporting the same, and the present invention can support a user to reduce the time required for searching for an item by intelligently providing items that are likely to be purchased by users.

In addition, the present invention can support to optimize the item purchase by effectively supporting the appropriate item purchase through intelligent item recommendation.

10: Item Recommendation System
100: user terminal
200: item providing service device
210: device communication unit 250: device storage unit
260: Device control unit 300:

Claims (15)

At least one user terminal connected to an item providing service apparatus to receive and output item posting screen information, and receiving at least one item recommendation information according to an item purchase history provided by the item providing service apparatus;
Generate and store predefined association rules based on history of purchasing items of the user terminals, and generate item recommendation information corresponding to at least a part of purchase history of a specific user terminal from the association rule to provide to the specific user terminal. An item providing service apparatus;
Item recommendation system comprising a. A device communication unit supporting item posting screen information and signal transmission / reception for item purchase, and providing the at least one item recommendation information;
An apparatus for generating predefined association rules based on history of purchasing items of user terminals, and generating item recommendation information corresponding to at least a part of purchase history of a specific user terminal from the association rule and providing the same to the specific user terminal. Control unit;
Item providing service apparatus comprising a. 3. The method of claim 2,
A device storage unit for storing the association rules and purchase history of the user terminals;
Item providing service device further comprises. 3. The method of claim 2,
The device control unit
After checking the purchase history of the specific user terminal, searching for association rules corresponding to items included in the purchase history, selecting association rules to be used as a predetermined number of preliminary recommendation items based on a predetermined criterion, and then predefined Item providing service device, characterized in that for generating items recommended information items included in a certain rank. 5. The method of claim 4,
The specific user terminal
And at least one of a user terminal connected to the device communication unit and a non-connected user terminal that has performed prior consent for receiving the item recommendation information. 5. The method of claim 4,
The schedule criteria
At least one of support, reliability,
The support rate is a ratio of association rules including two specific products among the total association rules, the reliability is a ratio of association rules including the specific product and other specific products among all association rules including a specific product, The improvement degree is an item providing service apparatus, characterized in that the ratio of the association rules generated based on the history of the purchase of the particular product and the other specific product among the association rules including the specific product. The method according to claim 6,
The device control unit
And calculating association rules of at least one of the schedule criteria equal to or greater than a predetermined ratio, and calculating a predetermined number of association rules of the association rules of the predetermined ratio or more as the preliminary recommendation item. 5. The method of claim 4,
The device control unit
And configuring the item recommendation information to include the same number of items as the number of purchase history of the user terminal. 5. The method of claim 4,
The device control unit
And a predetermined number of predetermined items in the process of configuring the item recommendation information. Generating and distributing, by the item providing service device, association rules having a predetermined rule length based on an item purchase history of user terminals;
Calculating, by the item providing service device, a predetermined number of preliminary recommended items based on a predetermined number of association rules corresponding to items included in a purchase history of a specific user terminal;
Configuring, by the item providing service apparatus, items within a predetermined predetermined rank among the preliminary recommended items calculated as item recommendation information;
Providing, by the item providing service device, the item recommendation information to the user terminal;
Item recommendation method comprising a. 11. The method of claim 10,
Confirming, by the item providing service device, a purchase history of a user terminal which has accessed the item providing service device;
Generating, by the item providing service device, the item recommendation information corresponding to a purchase history of the connected user terminal;
Providing, by the item providing service device, the item recommendation information to the connected user terminal;
Item recommendation method characterized in that it further comprises. 11. The method of claim 10,
Confirming, by the item providing service device, a purchase history of a specific user terminal having a history of purchasing an item in the item providing service device;
Providing, by the item providing service apparatus, the item recommendation information based on a purchase history of the user terminal;
Item recommendation method characterized in that it further comprises. 11. The method of claim 10,
The schedule criteria
At least one of support, reliability,
The support is the ratio of association rules that include two specific products of the overall association rules,
The reliability is a ratio of association rules including the specific product and other specific products among all the association rules including the specific product,
The degree of improvement is an item recommendation method, characterized in that the ratio of the association rules generated based on the history of the purchase of the particular product and the other specific product among the association rules including the specific product. 11. The method of claim 10,
Generating the item recommendation information
Configuring the item providing service device to include the same number of items as the number of purchase history of the user terminal in the process of configuring the item recommendation information;
Configuring the item providing service device to include a predetermined number of predetermined items in the process of configuring the item recommendation information;
And at least one step of the item recommendation method. The computer-readable recording medium which recorded the program which performs the item recommendation method of any one of Claims 10-14.

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