KR101820250B1 - Method and apparatus for curating customized sport convergence contents - Google Patents

Abstract

The present invention relates to a customized sports content recommendation curation system which comprises the steps of: configuring a sports convergence content profile by collecting and storing a profile of a user, a sports facility, and a referee, and collecting and analyzing the user profile by a team unit; finally calculating a preference between teams by calculating and analyzing a preference between teams based on a grade and a preference between teams based on similarity based on the sports convergence content profile when a team matching request is received; and selecting and recommending an opposing team in an order of the preference between teams.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and system for customizing sport content,

The present invention relates to a method and system for customizing sports content, and more particularly, to a method and system for customizing a sports content that enables recommendation of sports content in consideration of preference and inclination of each user of sports.

Recently, in the sports field, there is an increasing interest and research to foster the revitalization of the sports industry by fusing with ICT technology. Research that collects and analyzes physical information of athletes through wearable equipment and maintains the best condition and recommends the appropriate training method; analyzes the flow of the game by analyzing the movement of the player or the movement of the ball by recording the sports game scene And so on.

Especially, in the field of sports industry, there is a great interest in the field of sports for the living, and the TV program 'My Community Arts' is very popular. The revitalization of life sports team can bring about advantages in various aspects such as health promotion of national sports, revitalization of sporting goods industry, activation of private sports facilities, and various national policies and researches are being carried out to activate life sports.

As the number of sports teams in society increases, the market of life sports has been expanded. Now, the importance of service development and research in combination with ICT is increasing. Especially, service system research is actively carried out to match sports between sports teams, which is most important to expand the life sports market. However, current services are provided through web communities or smartphone applications. Due to low quality services, financial and time loss due to sudden withdrawal from the opponent team, and poor performance of the opponent team There are many problems such as difficulty in securing a game place and supplies.

Although a profile based sports content recommendation service has been proposed, a service recommending a sports content based on a conventional profile is not a method of automatically recommending a team suitable for a user based on a user profile, There were only services in the form of finding and playing games. In other words, the service research that automatically recommends sports contents is insufficient, and there is no commercialized service at present.

Design and Implementation of Sports Team Matching System Using Hybrid App-based Heap Sorting Algorithm (Author: Son Soo Ahn, Park Seokcheon, Jonghyun Kim, Andong Hyuk Park) Published by: Internet Society of Korea Fall Conference, 2015.10, 242 (2 pages)

In order to solve the above problems, the present invention provides a user-customized sports content curation method and system that analyzes a sports convergence content profile based on content and automatically recommends a team suitable for a user.

In addition, the present invention provides a user-tailored sports content curation method and system that can perform a team recommendation operation considering the preferences and tendencies of each user constituting a team.

The objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned can be clearly understood by those skilled in the art from the following description.

As a means for solving the above problems, a user-customized sports content curlation method according to an embodiment of the present invention includes the steps of: collecting and storing profiles of users, sports facilities, and referees; collecting and analyzing the user profiles on a team- Thereby configuring a sports convergence content profile; Based on the sports convergence content profile, calculating the preference between the rating-based team and the similarity-based team preference when the team matching is requested;

Based preference of each based on the preference weight based on the preference weight and the preference weight based on the preference weight based on the preference weight based on the score and adjusting the weighting ratio of each preference based on the degree of similarity, ; And selecting and recommending opponent teams in descending order of preference between the teams.

The method may further include searching and analyzing the sports facility and the referee profile based on the situation information of a user who requests team matching, and selecting and recommending at least one sports facility and a referee.

The method may further include modifying the sports convergence content profile by reflecting the user feedback when user feedback on the team matching result is input.

The sports convergence content profile may include at least one of sports facility information, referee information, user information, team information, team weight information, user-team rating information, competition information, and item information.

The user information includes at least one of a user ID (IDentification), a user PW (PassWord), an item ID, a name, a sex, a date of birth, a telephone number, an E-mail, The region, the height, the weight, and the obstacle can be modified.

The team information includes at least one of a team ID, a team name, a team establishment date, a main position, a sex ratio, a sex standard deviation, a failure rate, a failure standard deviation, a competition number, Wherein the information includes at least one of a standard deviation, an average weight, a weight standard deviation, and a number of members, and the at least one of the main position, the sex ratio, the sex standard deviation, The standard deviation, the team rating, the average elongation, the elongation standard deviation, the average weight, the standard deviation of the weight, and the number of members are collected and analyzed on a team basis in each region of the user profile, height, weight, .

Wherein the team weight information includes at least one of weight information for each attribute, team rating, and preference weight, and the user-team rating information includes at least one of a user ID, a team ID, and a weight for each user, Attribute-based weight information, the similarity-based team preference, and the user-specific weight are modified according to the user feedback.

"에 따라 팀간 선호도를 산출하며, 상기 TS_ij는 거리 기반 팀간 유사도, 상기 TR_ij는 평점 기반 팀간 유사도, 상기 α_i는 TS_ij의 가중치인 것을 특징으로 한다. The inter-team preference is "

, The TS _ij is the distance-based similarity between the teams, the TR _ij is the similarity between the rating-based teams, and the _i is the weight of TS _ij .

"의 식에 따라 산출되며, 상기 FA_ik 및 FA_jk는 팀 i와 j의 k 번째 속성의 평균값, 상기 FSD_ik 및 FSD_jk는 팀 i와 j의 k 번째 속성의 표준 편차, 상기 FW_n는 n번째 속성의 가중치, 상기 k는 속성의 인덱스, 상기 n은 속성의 총 개수인 것을 특징으로 한다. The degree of similarity-based preference between the teams is "

_Wherein FA _ik and FA _jk are average values of kth attributes of teams i and j, FSD _ik and FSD _jk are standard deviations of kth attributes of team i and j, FW _n is n Th attribute, k is an index of the attribute, and n is a total number of attributes.

The score-based preference is calculated by summing and averaging the score of each team member while differentiating the weight of each team member according to the user-specific weight, and comparing the score with the opponent team.

As a means for solving the above problems, a user-customized sports content curation system according to another embodiment of the present invention collects and stores a profile of a user, a sports facility and a referee, collects and analyzes the user profile on a team basis A content infomation providing system for creating and managing a sports convergence content profile; Based on the preference of the sports based on the sports convergence content profile, calculates the preference degree based on the score based on the score and the likelihood based on the similarity based on the sports convergence content profile, Based preference of the team based on the score-based preference and the likelihood between teams based on the degree of similarity based on the consideration of weight, and then selecting and recommending the opponent teams in descending order of preference among the teams . ≪ / RTI >

The user-customized sports content curation method and system according to the present invention can analyze the sports convergence content profile on the basis of content and automatically recommend a team suitable for the user, thereby maximizing user convenience.

In addition, the team recommendation operation considering user 's preference and disposition by allowing the user' s profile to be collected and analyzed on a team basis, constituting a sports convergence content profile, and allowing user feedback on the team matching result to be reflected in the sports convergence content profile .

1 is a diagram for explaining the overall configuration of a user-customized sports content recommendation curation system according to an embodiment of the present invention.
2 is a diagram showing a detailed configuration of a content infomation providing system according to an embodiment of the present invention.
FIG. 3 is a diagram showing a detailed configuration of a content recommendation curation system according to an embodiment of the present invention.
4 is a detailed block diagram of a user terminal according to an embodiment of the present invention.
5 is a view for explaining a method of customizing a sports content according to an embodiment of the present invention.
6 is a diagram for explaining the profile preprocessing step according to an embodiment of the present invention in more detail.
7 is a view for explaining a sports convergence content profile according to an embodiment of the present invention.
8 is a diagram for explaining a step of providing a customized sports content curation service according to an embodiment of the present invention in more detail.
9 is a diagram for explaining the user feedback reflecting step according to an embodiment of the present invention in more detail.

It is noted that the technical terms used in the present invention are used only to describe specific embodiments and are not intended to limit the present invention. In addition, the technical terms used in the present invention should be construed in a sense generally understood by a person having ordinary skill in the art to which the present invention belongs, unless otherwise defined in the present invention, Should not be construed to mean, or be interpreted in an excessively reduced sense. In addition, when a technical term used in the present invention is an erroneous technical term that does not accurately express the concept of the present invention, it should be understood that technical terms can be understood by those skilled in the art. In addition, the general terms used in the present invention should be interpreted according to a predefined or prior context, and should not be construed as being excessively reduced.

Furthermore, the singular expressions used in the present invention include plural expressions unless the context clearly dictates otherwise. In the present invention, terms such as "comprising" or "comprising" and the like should not be construed as encompassing various elements or various steps of the invention, Or may further include additional components or steps.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals refer to the same or similar elements, and redundant description thereof will be omitted.

In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail. It is to be noted that the accompanying drawings are only for the purpose of facilitating understanding of the present invention, and should not be construed as limiting the scope of the present invention with reference to the accompanying drawings.

1 is a diagram for explaining the overall configuration of a user-customized sports content recommendation curation system according to an embodiment of the present invention.

Referring to FIG. 1, the sports sports contents curation system of the present invention may include a content infomatics providing system 100, a content recommendation curation system 200, a user terminal 300, and the like have.

The content infomatics providing system 100 collects and stores profiles of users, sports facilities, and referees, and collects and analyzes user profiles on a team basis to form a sports convergence content profile. Also, user feedback based on the team matching result is received, and the profile can be re-analyzed and re-based on the received feedback. In other words, a learning algorithm that applies dynamic profiling and weighting allows the sports rink content profile to learn user preferences and propensity.

When the team matching is requested by a specific user or team, the content recommendation curation system 200 calculates the preference degree between the rating-based team and the similarity based on the team profile based on the team profile, and then collectively analyzes the two preferences Finalize the preference between teams. Then select the recommended teams in the order of highest preference among the teams and guide them to the users. In addition, when the team recommendation is made, the user situation information is additionally confirmed, so that the sports facility and the referee who are most suitable for the current situation of the user can be recommended together.

The user terminal 300 is a terminal that interworks with the content infomation providing system 100 and the content recommendation curation system 200 to install and execute an application capable of providing a content recommendation curation service. The application can input or output various information related to the content recommendation curation service through a UI (User Interface). In particular, a user profile may be acquired and provided to the content infomation providing system 100, or a user may be recommended to use a matching team that is optimized for the preference or tendency of the user or team to request a team matching, And provides the content information to the content infomation providing system 100 or generates and provides the situation information to guide the user by recommending the sports facility and referee optimized for the user or team situation.

In particular, the present invention collects and analyzes a plurality of user profiles on a team basis in consideration of a team composed of a plurality of users, and performs a relative team recommendation operation based on the collected user profiles, To recommend a similar team.

2 is a diagram showing a detailed configuration of a content infomation providing system according to an embodiment of the present invention.

2, the content infomation providing system 100 of the present invention includes a profile analyzing unit 110, a profile managing unit 120, a feedback reflecting unit 130, a reservation / flat processing unit 140, A content storage unit 160, a communication unit 170, and the like.

The profile analysis unit 110 stores and manages team classification rules, and collects and analyzes a plurality of users on a team basis based on the stored rules.

The profile management unit 120 verifies and prepares each profile of a user, a team, a sports facility, and a referee, and stores the profile, or retrieves and provides a necessary profile in response to a profile providing request.

When the user feedback corresponding to the team matching result is input, the feedback management unit 130 re-analyzes the sports convergence content profile by reflecting the user feedback, thereby allowing the sports convergence content profile to fully reflect the user's preference and inclination.

The reservation / reputation processing unit 140 generates and stores game information corresponding to the team matching result.

The visualization unit 150 performs a user-friendly visualization process based on the sports convergence content profile. That is, visualization information is invoked to generate and provide visualization data.

The content storage unit 160 stores the sports convergence content profile and the communication unit 170 receives the content recommendation information from the content recommendation curation system 200, the user terminal 300, And / or the external server 400 that stores and manages the referee information, so that various information necessary for the content infomation operation can be transmitted and received.

FIG. 3 is a diagram showing a detailed configuration of a content recommendation curation system according to an embodiment of the present invention.

3, the content recommendation and culling system of the present invention includes a content search unit 210, a content recommendation unit 220, a content mashup unit 230, a content adaptation unit 240, and a communication unit 250 . ≪ / RTI >

The content retrieval unit 210 accesses the content infomatics providing system 100 to retrieve and acquire a sports convergence content profile necessary for providing a content recommendation service.

The content recommendation unit 220 extracts the user-customized content based on the sports convergence content profile and recommends the user to the user.

The content mashup unit 230 mashes up the sports convergence content profile according to the user profile.

The content adaptation unit 240 adapts the sports convergence content profile in a form for providing to the user terminal 300 and also determines the priority of the content based on the situation information of the life sports group.

The communication unit 250 forms a communication channel with the content infomation providing system 100 and the user terminal 300, and enables various information necessary for the content recommendation curation operation to be transmitted and received.

4 is a detailed block diagram of a user terminal according to an embodiment of the present invention.

4, the user terminal of the present invention includes a main control unit 310, an application 320, a communication unit 330, and the like. The application 320 further includes a profile providing unit 321, A content information providing unit 322, a situation information providing unit 323, and a content cueing unit 324.

The main control unit 310 controls the overall operation of the user terminal. In particular, when the user selects and executes the application 320, the application 320 is activated.

As described above, the application 320 is an application for providing a user with customized contents, and has functions such as visualization of information, profile collection, user feedback, situation information collection, and the like.

More specifically, the profile providing unit 321 provides a user with a user or a team profile input window, collects input information, generates a user or a team profile, and provides it to the content infomatics providing system 100 .

The feedback providing unit 322 requests the user to input user feedback corresponding to the team matching result, and provides the input information to the content infomation providing system 100 in response thereto.

The situation information providing unit 333 grasps information such as a user's location and weather through a sensor built in the user terminal, generates situation information including the information, and provides the generated information to the content recommendation curation system 200 .

The contents curation unit 324 customizes the contents provided from the contents recommendation curation system 200, and then makes the contents to be audiovisualized and provided to the user.

The communication unit 330 forms a communication channel with the content infomation providing system 100 and the content recommendation curation system 200, and enables various information necessary for the content recommendation curation operation to be transmitted and received.

5 is a view for explaining a method of customizing a sports content according to an embodiment of the present invention.

Referring to FIG. 5, the method for customizing sport content for the user of the present invention includes a profile preprocessing step S10, a customized sports content curation service providing step S20, and a user feedback reflecting step S30 .

Hereinafter, the operation method of each step will be described in more detail.

6 is a diagram for explaining the profile preprocessing step according to an embodiment of the present invention in more detail.

First, the content infomation providing system 100 acquires a user or a team profile through communication with a plurality of user terminals 100, and communicates with a user, a team, a sports facility, Thereby obtaining a profile (S11).

Then, the content infomatics providing system 100 classifies and collects a plurality of pieces of user information on a team basis based on a predefined team classification rule (S12), and transmits the analysis result to the profile obtained through step S11 Thereby generating a sports convergence content profile (S13).

FIG. 7 is a view showing an example of a sports convergence content profile according to an embodiment of the present invention. Referring to FIG. 7, the sports convergence content profile of the present invention includes sports facility information 131, referee information 132, 133, team information 134, team weight information 135, user-team rating information 136, competition information 137, item information 138, and the like.

The sports facility information 131 may include information on the sports facility ID, facility location, rental fee, size, capacity, reservation schedule, and the like.

The referee information 132 may include information on the referee ID, the item ID, the location, the sex, the referee price, and the like.

The user information 133 may include information on the user ID, the user PW, the item ID, the name, the sex, the date of birth, the telephone number, the E-mail, the area, the height,

The team information 134 includes team ID, team name, team establishment date, team main position, sex ratio, gender standard deviation, failure ratio, failure standard deviation, number of matches, number of victories, average age, , Height standard deviation, average weight, weight standard deviation, number of members, and the like.

At this time, the user who belongs to the team, the sex ratio, the sex standard deviation, the disability rate, the standard deviation of the disability, the number of matches, the number of victories, the average age, the standard deviation, It is the value obtained by collecting and statistics of the attribute values of the information. Particularly, in the present invention, it is possible to dynamically change some attributes (for example, region, height, weight, disability, etc.) of user information at the time of a subsequent user request. To be dynamically variable depending on the user modification value.

Etc. team rating information 136 is the user ID, a team ID, a user-specific weight-side weight information 135 team ID, attribute by weight (FW _n), preference weights (α _i), and include information on the user And the like.

At this time, the attribute weight FW _n , the user weight MW _u , and the preference weight α _i have offset values at the time of initial creation of the sports convergence content profile, but the user feedback So that the value can be modified. For example, the attribute-specific weight (FW _1, FW _2, FW ₃₎ is 1 / n has the (n is the total number of attributes that are considered to timgan affinity calculation) as an offset value, the user-specific weights (MW _u) 1 / u (where u is the total number of team members).

This is to reflect user feedback on the result of team matching and to adjust the value of the parameter necessary for calculating the preference of the team so that the tendency and preference of each user can be reflected in the result of calculating the preference between the team.

The game information 137 includes information on a user ID, a team ID, a game date, a sports facility ID, a team matching information, a score for each team, a winning team, a rating for the opponent team, , Team ID, team loyalty, and the like.

FIG. 8 is a diagram for explaining a step of providing a customized sports content curation service according to an embodiment of the present invention in more detail.

If the user logs in the content recommendation curation system 200 through the user terminal 300 and requests team matching (S21), the user is identified based on the user login information, (Step S22). The profile related to the user is retrieved and acquired.

Based on the rating-based team preference and the similarity-based team preference based on the profile (e.g., team information, team weight information, user-team rating information, game information, ).

The preference among the rating-based teams can be grasped by calculating the score for each team through the combination of Average Without Misery Strategy and Weighted Strategy, and then obtaining the difference between the teams. At this time, the preference among the score-based teams will have a higher value as the score difference between the teams becomes smaller.

The weighted strategy is a weighted strategy based on user weights. The weighted strategy is used to calculate the score of each team by summing and averaging all the attribute values in the user information of each team member. (Average Without Misery Strategy). This is an example of a rating calculation method for each team. In addition to the above-described method, the present invention can also calculate a score for each team by using various methods.

Similarity-based team preference can be calculated through the following procedure.

First, calculate the distance between the teams based on the center values (FA, FSD) for each team member attribute stored in the team information. (TD _ij ) based on the center value for each team member attribute can be calculated using the Euclidian distance calculation method as shown in Equation (1).

[Equation 1]

Where FW _n is the weight of the nth attribute, FA _ik and FA _jk are the mean values of the kth attributes of teams i and j, FSD _ik and FSD _jk are the standard deviation of the kth attribute of team i and j, , and n is the total number of attributes. At this time, the total value of FW _n should be 1. This allows for refinement of the attributes of each team. The offset value is set to 1 / n so that it can be continuously changed according to the user feedback.

(TS _ij ) based on the center-value-based distance (TD _ij ) of each team member attribute as shown in Equation (2).

 &Quot; (2) "

Based on the point-based inter-team preference and the degree-of-similarity based on the degree of similarity, the inter-team preference based on the score-based preference and the degree-of-similarity based on the degree of similarity based on Equation (3) is finally calculated at step S24.

 &Quot; (3) "

At this time,? _I is a preference weight.

In step S25, a recommended team list is created in the order of the highest preference among the teams, and is provided to the user terminal 300 so that the user can select a desired opponent team with reference to the recommended team list.

Also, when the user terminal provides the situation information such as the user's location and the weather, the sports facility information 131 and the judgment information 132 stored and managed in the content infomation providing system 100 are searched and analyzed , And a sports facility and referee matching the user situation are searched and recommended (S26).

If the user selects a specific opponent team and the opponent team accepts the team match with the user team (S27), the sports facility and the referee reservation procedure are automatically performed, and the reservation result is presented to the user and the opponent team (S27).

The content infomation providing system 100 notifies the reservation result to the content infomation providing system 100 so that continuous information management can be performed by generating and storing corresponding game information (S28) .

9 is a diagram for explaining the user feedback reflecting step according to an embodiment of the present invention in more detail.

If the game corresponding to the team matching has actually been performed, the content infomatics providing system 100 requests the user terminal 300 to input user feedback, and receives user feedback corresponding to the team matching result (S31). At this time, the user feedback may include information about an attribute selection value to be used in team matching, a team contribution per user, and the like.

Then, the content infomatics providing system 100 re-calculates and stores the attribute-specific weight FW _n , the user-specific weight MW _u , and the preference weight α _i based on the user feedback (S 33) .

In step S33, the property weighting value FW _n is calculated according to equation (4).

 &Quot; (4) "

In this case, C _n is the number of times of selecting and matching categories for the n-th attribute of users.

In step S33, the weight per user MW _u is calculated according to the equation (5).

 &Quot; (5) "

At this time, RC _u is the number of ratings input for the matching of user u, and U _alpha is a weight for the user position (e.g., leader, manager, etc.). The normalized value is used as a weight value of each user.

In step S33, and the preference weight [alpha] _i is calculated according to equation (6).

 &Quot; (6) "

When α _i is the preference weight, MC _i is the total number of matches of team i, and C _n is the number of times of selecting and matching categories for the nth attribute of users.

The features, structures, effects and the like described in the foregoing embodiments are included in at least one embodiment of the present invention and are not necessarily limited to one embodiment. Further, the features, structures, effects, and the like illustrated in the embodiments may be combined or modified in other embodiments by those skilled in the art to which the embodiments belong.

Therefore, it should be understood that the present invention is not limited to these combinations and modifications. While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is clearly understood that the same is by way of illustration and example only and is not to be construed as limiting the scope of the present invention. It can be seen that various modifications and applications are possible. For example, each component specifically shown in the embodiments may be modified and implemented. It is to be understood that the present invention may be embodied in many other specific forms without departing from the spirit or essential characteristics thereof.

Claims (11)

Setting and storing a preference weight having an offset value;
Collecting and storing profiles of users, sports facilities and referees, and assembling and analyzing the user profiles on a team basis to form a sports convergence content profile;
Based on the sports convergence content profile, calculating the preference between the rating-based team and the similarity-based team preference when the team matching is requested;
Based preference of each of the similarity based on the preference weight based on the preference weight and finally calculating the preference of the team based on the score-based preference based on the score and the similarity based on the preference weight;
Selecting and recommending opponent teams in descending order of preference among the teams; And
And modifying the preference weight by reflecting user feedback when user feedback on the team matching result is input,
The inter-team preference
"

, Wherein TS _ij is distance-based inter-team similarity, TR _ij is a rating-based inter-team similarity, and _i is the preference weight. The method according to claim 1,
And searching and analyzing the sports facility and the referee profile based on the situation information of the user who requested the team matching, and selecting and recommending at least one sports facility and referee. Way. The method of claim 1, wherein modifying the preference weight by reflecting the user feedback comprises:
Further comprising the step of: modifying weight and weight for each user based on user feedback on the team matching result. The method of claim 1, wherein the sports convergence content profile
Wherein the information includes at least one of sports facility information, referee information, user information, team information, team weight information, user-team rating information, competition information, and stock information. 5. The method of claim 4,
Information on at least one of a user ID (IDentification), a user PW (PassWord), an item ID, a name, a sex, a date of birth, a telephone number, an E-mail,
Wherein the region, the height, the weight, and the obstacle are modifiable. 6. The method of claim 5,
The team information includes at least one of a team ID, a team name, a team establishment date, a main position, a sex ratio, a sex standard deviation, a failure rate, a failure standard deviation, a competition number, Standard deviation, average weight, weight standard deviation, and number of members,
The method of claim 1, wherein the weight, the sex ratio, the sex standard deviation, the impairment ratio, the impairment standard deviation, the mean age, the age standard deviation, the team rating, the average height, Standard deviation, and the number of the members are calculated by collecting and analyzing the region, height, weight, and disorder of each of the user profiles on a team basis. 5. The method of claim 4,
Wherein the team weight information includes at least one of weight information, a team score, and a preference weight for each attribute,
Wherein the user-team rating information includes at least one of a user ID, a team ID, and a user-specific weight,
Wherein the attribute-based weight information, the similarity-based team preference, and the user-specific weight are modified according to the user feedback. delete 2. The method of claim 1, wherein the similarity-based team preference is
"

"And "
_Wherein FA _ik and FA _jk are average values of kth attributes of teams i and j, FSD _ik and FSD _jk are standard deviations of kth attributes of team i and j, FW _n is weight of nth attribute, Attribute index, and n is the total number of attributes. ≪ RTI ID = 0.0 > 8. < / RTI > The method of claim 1, wherein the rating-based team preference is
Wherein the score is calculated by summing and averaging the scores of the team members while differentiating the weight of each team member according to the weight per user, and then comparing and analyzing the scores with the opponent team. A content infomation provision system for collecting and storing profiles of users, sports facilities, and referees, and creating and managing a sports convergence content profile by collecting and analyzing the user profiles on a team basis; And
Based on the sports convergence content profile, the preference degree based on the score-based preference and the degree of similarity based on the preference weight based on the preference weight based on the score, Based preference of the team based on the score-based preference and the likelihood between similarity based on the above-mentioned weighted proportion, and then selecting and recommending the opponent teams in descending order of preference among the teams, And a content recommendation curation system for modifying the preference weight based on user feedback,
The content recommendation curation system
"

, Wherein TS _ij is distance-based inter-team similarity, TR _ij is a score-based inter-team similarity, and _i is the preference weight. .

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