KR101346287B1 - Method and apparatus for setting data value - Google Patents

Abstract

Confirming the behavior of the second user on the data uploaded to the network service by the first user, determining the influence index of the second user, determining the behavior index for the behavior of the second user, the impact index and the behavior index A data exponent setting method for determining a data exponent of data based on the above is disclosed.

Description

Method and apparatus for setting data indexes {Method and apparatus for setting data value}

The present invention relates to a method and apparatus for setting the data index, and more particularly, to a method and apparatus for setting the index of the data using the behavior index for the data uploaded from the network service and the impact index in the network service. will be.

At present, due to the increase of the Internet and smart phones, many network services have been developed and used. Recently, network services, especially social network services, are being used by many users. For many users, the amount of data exposed to an individual is very wide. Therefore, the user has a great inconvenience of having to see data that is meaningless to him, which is a problem.

The technical problem to be solved by the present invention is to provide a method and apparatus for setting the index of the data using the behavior index according to the response behavior of other users to the data uploaded to the network service and the user impact index in the network service Furthermore, the present invention provides a method and apparatus for providing data with high data index first.

According to an embodiment of the present invention for solving the technical problem, a method for setting a data index of the data uploaded to the network service by the first user comprises the steps of checking the action of the second user on the data; Extracting a preset value for the action of the second user; Determining a behavior index by adding a probability associated with occurrence of the behavior to the preset value; And determining a data index of the data based on the behavior index.

According to another embodiment of the present invention for solving the technical problem, a method of setting a data index of the data uploaded to the network service by the first user comprises the steps of confirming the behavior of the second user on the data; Extracting a preset value for the action of the second user; Adding a preset weight to the preset value; Determining a behavioral index for the behavior of the second user based on the preset value and a preset weight; And determining a data index of the data based on the behavior index.

According to another embodiment of the present invention for solving the technical problem, a method for setting a data index of the data uploaded to the network service by the first user comprises the steps of confirming the behavior of the second user on the data; Determining an impact index of the second user; Determining a behavioral index for the behavior of the second user; And determining a data index of the data based on the influence index and the behavior index.

Determining the impact index of the second user includes extracting a stored previous impact index of the second user; Determining a data index of data uploaded by the second user up to a predetermined point in time; And determining an influence index of the second user based on a previous influence index of the second user and a data index of data uploaded by the second user.

Determining a behavior index for the behavior of the second user may include extracting a preset value for the behavior of the second user; Adding a preset weight to the preset value; The method may include determining a behavior index for the second user's behavior based on the preset value and the preset weight.

Determining a behavior index for the behavior of the second user may include extracting a preset value for the behavior of the second user; And determining a behavior index by adding a probability related to occurrence of the behavior to the preset value.

The data index setting method may further include determining the rank of the data according to the determined data index.

A data index setting method includes the steps of ranking the data according to the determined data index; And displaying the uploaded data in priority order according to the determined data rank.

According to another embodiment of the present invention for solving the technical problem, the apparatus for setting the data rank of the data uploaded to the network service by the first user is based on the action of the second user on the data from the network service. Communication unit for receiving information about; A storage unit which stores a preset value for the action of the second user; And extracting a preset value for the second user's behavior from the storage, adding a probability associated with the occurrence of the behavior to the preset value, and determining a behavior index, based on the behavior index. And a control unit for determining a data index.

According to another embodiment of the present invention for solving the technical problem, the apparatus for setting the data index of the data uploaded to the network service by the first user is based on the action of the second user on the data from the network service. Communication unit for receiving information about; A storage unit which stores a preset value for the action of the second user; And extracting a preset value from the storage unit with respect to the second user's behavior, and adding a preset weight to the preset value to add the preset weight to the second user's behavior based on the preset value and the preset weight. And a controller configured to determine a behavior index, determine a data index of the data based on the behavior index, and determine the ranking of the data according to the determined data index.

According to another embodiment of the present invention for solving the technical problem, the apparatus for setting the data index of the data uploaded to the network service by the first user is based on the action of the second user on the data from the network service. Communication unit for receiving information about; A storage unit to store a previous influence index of the second user; And extracting a previous influence index of the second user stored in the storage unit, and determining a data index of data uploaded by the second user up to a predetermined time point, so as to determine a previous influence index and the first index of the second user. Based on the data index of the data uploaded by the user, determining the influence index of the second user, determining the behavior index for the behavior of the second user, and based on the impact index and the behavior index, And a control unit for determining a data index of the data.

According to the present invention, by setting the data index by using the other party's response to the uploaded data and / or the other party's influence index, it is possible to accurately determine the data that can increase the user's interest. In addition, by providing data with a high data index ranking to the user, the user can be provided with data that all users are interested in, without exposure to meaningless data.

1 is a flowchart illustrating a method of setting a data index of data uploaded to a network service according to an embodiment of the present invention.
2A to 2D are diagrams showing respective histograms for Tables 2 to 5;
3 is a flowchart illustrating a method of setting a data index of data uploaded to a network service according to another embodiment of the present invention.
4 is a diagram illustrating an example of an interface for displaying uploaded data according to a data rank according to an embodiment of the present invention.
5 is a block diagram of an apparatus for setting a data index of data uploaded to a network service according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a flowchart illustrating a method of setting a data index of data uploaded to a network service according to an embodiment of the present invention.

Referring to FIG. 1, in operation 110, an apparatus for performing a method of setting a data index of data uploaded to a network service (hereinafter, referred to as a data index setting apparatus) may be configured to perform data uploading by a first user. 2 Check the user's behavior. The data index setting apparatus confirms the behavior of the second user with respect to the data uploaded by the first user to the network service to which the first user is subscribed or registered. A user signifies or subscribes to at least one network service and uses the service. As an example, the network service may be a social network service. The data index setting device preferably exists separately from the network service subscribed to by the user. Data refers to all the objects that are exchanged between users in network services. For example, the data may be information, news, images, videos, URLs, location information, and the like. The above data are examples only, but are not limited to these. The action of the user refers to the action of the user performed in the network service. Examples of user behavior include, but are not limited to, writing posts on network services such as Facebook, commenting on posts or clicking “Like”, uploading data such as images or videos, sharing on uploaded data, networks like Twitter Tweets from the service, retweets of others' tweets, and so on. The above user behavior is also an example only and is not limited thereto. The action of the first user means that the first user uploads data to the network service. In the example of the above user action, writing, uploading data, and tweeting can be viewed as the action of the first user. The action of the second user means a response action to the action of the first user. That is, the action of the second user is a response action to data uploaded by the first user. In the example of the above user action, a second user may view a comment or a like click on a post, share on uploaded data, or retweet.

The data index setting device may grasp the user's activity, that is, the behavior of the user and the other user's behavior, in the network service using an access token to at least one network service to which the user is subscribed. The data index setting device may use the access token to access resources of the network service to which the user subscribed. The access token is used to request network service APIs on behalf of that user. Data index setting It is possible to obtain various information about the user in the network service. Let's take Facebook as an example of a network service. Facebook provides an Open API based on OAuth. The key to OAuth authentication is to enter a user's ID and password on a Facebook page and, if the ID and password match, issue an access token instead. The issued access token can also be retrieved at any time, if desired by the user. If you do not use the OAuth method, create a linked page to log in to Facebook, enter the user's Facebook ID and password in the network service you want to link to, and use the Server to Server interface provided by Facebook. Use it to check if ID and password are correct. When using this method, the problem is that the user's password can be found in the network service to be interworked. Therefore, a security problem occurs. Therefore, the trust of the interworking service must be based on the authentication service. The method is also not clear. To solve this problem, the user's ID and password are entered on a service page provided by Facebook, and instead, an encrypted token is issued to use the Open API. The access token contains information about the APIs that can be accessed, along with information that the user has been authenticated, and in some cases, the token can be set to invalid and can no longer be used. If the user enters his / her ID and password on the page in Facebook and authenticates with the issued access token, the following information can be accessed. Examples of information you can access on Facebook include 'accounts', which is the page information your account has, 'activities', which is profile information about your activity, 'adaccounts', which is your ad management account information, and 'albums', which is album information. , 'Apprequests' (app request information), 'books' (profile information) for the book, 'checkins' (region-based check-in information), 'cover' (pictures) used by the cover, and 'events' (events) Information, 'family' information about family, activity information I did to my friend, 'feed' information about posts I posted, 'friendlists' information about List, 'friendrequests' information about friend requests, 'friends' information, 'games' information about the game profile, 'groups' information on the Facebook group, 'home' information on the postings in my network, 'inbox' information on the inbox , Tube "Interests" information, likes, pages, apps, profile information "likes" information, shared link information "links" information, movie information "movies" information, music profile information 'Music' information, 'mutualfriends' information for common friends, 'notes' information for notes, 'notifications' for notification information, 'outbox' information for sent messages, 'payments' information for payment information, current access 'Permissions' information that is allowed to be accessed by tokens, 'photos' information that is tagged photo information, 'picture' information that is profile photo information, 'posts' information that I have written, and 'score information' posted by game apps 'scores' information, 'statuses' information I posted on the wall, 'tagged' information tagged, 'television' information related to TV, 'updates' information updated, and 'videos' information related to video Have information etc. All. The apparatus for setting a data index may identify the behavior of the first user and the behavior of the second user by using some or all of the information accessible using the access token as described above. The data index setting apparatus may access the network service periodically or non-periodically to receive information, check the user's behavior based on this, and obtain the influence index and the data index to be described below.

In operation 120, the data index setting apparatus determines a behavior index for the behavior of the second user. The behavior index refers to a value set for a response behavior to a user's behavior. Equation 1 is an expression for calculating the behavior index.

In Equation 1, SA () represents the behavior index, and x represents the second user who performed the behavior. In addition, r represents the number of times the comment is made, l represents 'like', i represents the first action start time of the second user and s represents whether or not to share. The response behavior to the user's behavior expressed in Equation 1 is only an example, and is not limited thereto. Depending on the service aspect of the network service, it can be applied to various response actions.

According to an embodiment of the present invention, the behavior index may be obtained based on a preset value according to the aspect of the response behavior. The equation for calculating the behavior index is as shown in Equation 2 below.

In Equation 2, the behavior index is a sum of preset values according to aspects of the response behavior. The use of the sum in the behavioral index is just one example, and the calculation may vary from case to case. Referring to Equation 2, for example, a preset value may include r = n if there are n comments, r = 0 if there are no comments, and l = 1 if the likes L = 0 if no, i = 1 if there is an action of a second user within a given time, i = 0 if no, s = 1 if there is a share, s = 0 if there is no share Can be set. The preset value is only an example, and other settings can be made according to the behavior index provider. In this case, for example, if the second user's behavior on the uploaded data of the first user is only 'like' and share, the behavior index is 2 (1 + 1).

According to another embodiment of the present invention, the behavior index may be obtained by adding weights to preset values according to aspects of the response behavior. The equation for calculating the behavior index is as shown in Equation 3 below.

Equation 3 adds a weight to a preset value in Equation 2. Referring to Equation 3, a, b, c, and d are weight coefficients. The weight may be determined differently according to the setting of the provider providing the behavior index. For example, for a preset value, for example, r = n if there are n comments, r = 0 if there are no comments, l = 1 if there are likes, l = 1 if no likes l = 0, i = 1 if there is an action of the second user within a predetermined time, i = 0 otherwise, s = 1 if there is sharing, s = 0 if no sharing, If the weights a = 2, b = 0.5, c = 1, d = 2, the behavior index is 2.5 (if the second user's behavior on the uploaded data of the first user is only like and share) 0.5 × 1 + 2 × 1).

According to another embodiment of the present invention, the behavior index may be obtained by adding a probability related to the occurrence of the behavior to a preset value according to the aspect of the response behavior. The equation for calculating the behavior index is as shown in Equation 4.

In Equation 4, K ₁ to k ₄ are weights for each probability item. The weight for this probability item can also be changed according to the setting of the setter. E _RE (r) represents the probability that the comment will run more than a predetermined number, E _LK (l) represents the probability of 'like', E _RT (t) represents the probability that there is a second user's action within a predetermined time E _SH (s) represents the probability of sharing. The above equation is only an example, and is not limited thereto. In addition, Equation 4 does not consider when there is no action of the second user. For example, if the second user only liked the comment and not shared it, the function related to the comment and share is not considered, and SA (x) = f _LK (l) = (1-k ₂ × E _LK ( l)). Like Equation 3, Equation 4 may further add weights according to each aspect of the behavior. In another embodiment of the present invention, if there is no access token for the user who wants to obtain the behavior index, information cannot be obtained from the network service, and thus the behavior index cannot be calculated. In this case, the data index setting device calculates a value obtained by averaging the probability of the user having the access token as the behavior index.

In one embodiment of the present invention, the probability is obtained by using normal distribution after extracting information about the behavior. Normal distribution is only an example of obtaining a probability, and there is no limit to the method of obtaining the probability. If the user's action is more than a certain number of times, the probability distribution to perform the action is normally distributed. The probability density function can be assumed to be a Gaussian function. Then, when the mean value and the standard deviation or variance are found, the probability of any behavior can be estimated. Equation 5 is a Gaussian function that is a probability density function.

In Equation 5, f _x () represents a Gaussian function, x represents a random variable, and μ represents an average σ ² variance.

According to another embodiment of the present invention, the behavior index may be obtained by using the highest probability among the probability and the probability related to the occurrence of the behavior at a preset value according to the aspect of the response behavior. The equation for calculating the behavior index is as shown in Equation 6.

Referring to Equation 6, if the number of comments made by the second user in f _RE (r) is the highest in the probability of commenting, r _{m ,} and if the comment is less than _max , k ₁ × E _{RE (r)} Otherwise, k ₁ x (M _RE (r) + M _RE (r)-E _RE (r)). M _RE (r) represents the highest probability of the number of comment months. Also, _{m i,} if fast commented than _max, the ₃ × k (M + M _{RT RT RT} -E (i)) in the case of _RT f (i) the second user with the highest probability from the time of commenting Otherwise, k ₃ × E _RT (i). M _RT represents the highest probability of the time probability of commenting. f _LK (l) and f _SH (s) are the same as in Equation 4.

In the following, an example of the probability required to determine the behavior index will be described. Table 1 is a table | surface which shows the number of actions which the 2nd user A, B, C, D made a comment which is a response action with respect to the upload data of a 1st user.

Comments from A B comments Comments on C Comments from D 2 2 2 One 0 0 2 0 One One 3 0 One One 0 0 0 0 2 One 0 0 0 One 2 0 3 0 0 One One One 0 One 0 One One 0 2 0 0 0 2 0 0 One 3 One 0 0 2 One One 0 2 One 0 0 2 One 0 One 2 One 0 0 2 0 0 One 2 0 0 0 2 0 0 0 3 0 One 0 One 2 One One 2 0 0 One 2 One 0 0 2 0 0 0 2 0 0 One 2 One 0 One 2 0 0 0 2 0 One One 2 0 One 0 2 0 0 0 0 One 0 One 0 0 0 0 0 0 0 0 0 0 0 0 2 0 One One 0 0 One 0 2 0 0 0 2 One 0 One 2 One 0 0 2 0 One 0 3 0 One 0 2 0 0 0 2 0 One 0 2 One 0 0 2 0 0 One 2 0 0 0 2 One 0 0 2 0 2 One One 0 0 0 2 0 0 One 2 0 0 0 2 0 0 0 2 One 0 0 3 0 0 One 3 0 0 One 2 0 One 0 2 0 0 0 2 0 One 0 2 0 0 0 2 0

Tables 2 to 5 are tables of comment probabilities of A, B, C, and D based on Table 1. Referring to Tables 2 to 5, probability densities according to the number of times, the frequency, and the number of actions of users A, B, C, and D are shown.

Number of times frequency Probability density 0 42 0.57820441 One 15 0.365736157 2 3 0.010918535 3 0 1.53841E-05 4 0 1.02303E-09 5 0 3.2108E-15 Etc 0

Table 2 shows the probability density for the behavior of A. Referring to Table 1, the average number of A behaviors is 0.35, and the standard deviation is 0.5722762. Accordingly, probability density is calculated as shown in Table 2. Referring to Table 2, the probability that A writes two comments about the behavior of the first user is 1.09%.

Number of times frequency Probability density 0 39 0.601029655 One 20 0.363781068 2 One 0.0050976 3 0 1.65376E-06 4 0 1.24211E-11 5 0 2.15989E-18 Etc 0

Table 3 is a table of probability densities for B's behavior. Referring to Table 1, the average number of B behaviors is 0.3666667, and the standard deviation is 0.5153208. Accordingly, probability density is calculated as shown in Table 3. Referring to Table 3, the probability that B makes one comment on the first user's behavior is 36.37%.

Number of times frequency Probability density 0 8 0.042183494 One 3 0.302392542 2 42 0.476406479 3 7 0.16495379 4 0 0.012552349 5 0 0.000209926 Etc 0

Table 4 shows the probability density for the behavior of C. Referring to Table 1, the average number of C behaviors is 1.8, and the standard deviation is 0.8124038. Accordingly, probability density is obtained as shown in Table 4. Referring to Table 4, the probability that C writes three comments about the behavior of the first user is 16.49%.

Number of times frequency Probability density 0 41 0.634973438 One 18 0.330765365 2 One 0.0034442479 3 0 7.15829E-07 4 0 2.97395E-12 5 0 2.46857E-19 Etc 0

Table 5 shows the probability density for the behavior of D. Referring to Table 1, the average number of D behaviors is 0.3333333, and the standard deviation is 0.505525. Accordingly, probability density is calculated as shown in Table 5. Referring to Table 5, the probability that D makes one comment on the first user's behavior is 33.07%.

2A to 2D are diagrams showing respective histograms for Tables 2 to 5;

FIG. 2A is a histogram 210 of probability densities for actions of second user A, FIG. 2B is a histogram 220 of probability densities for actions of second user B, and FIG. Histogram 230 for probability density for behaviors, and FIG. 2D is histogram 240 for probability density for behaviors of second user D. FIG. 2A to 2D, Freq 201 indicates the frequency of comments, and probability density 202 indicates the probability density according to the frequency and frequency. The vertical axis on the left is the axis of probability density, and the vertical axis on the right is the axis according to the frequency.

Hereinafter, an example of obtaining the behavior index according to Equations 4 and 6 will be described.

Table 6 is a table of other user's response to the data uploaded by the user during a predetermined interval, that is, comments. In Table 6, it is assumed that all of the users A, B, C, and D upload 20 data.

Upload data of A Upload data of B Upload data in C Upload data of D One B B D B C One A D D A C One A One A C C C 2 C C 2 C C 2 B A 2 A C C 3 B C C C 3 D A C C 3 B 3 C C 4 B 4 C A C 4 D 4 C A C 5 C D C 5 C C 5 5 C C 6 D 6 D C C 6 B 6 B C C 7 C C C 7 A A C C 7 D B 7 C C 8 B C D 8 C C 8 8 C C 9 B D 9 C C 9 A B 9 B C A A 10 C C 10 A C C 10 A 10 C C 11 C C 11 D 11 11 B C C 12 B D C C C 12 12 B 12 C C 13 D C C 13 13 D 13 C C 14 D C C 14 A 14 14 C C C 15 D C C 15 C C 15 15 B C C C 16 B D C C 16 16 A B 16 B C C 17 C C 17 C C 17 A 17 A C C 18 B C C 18 D C C 18 18 C C 19 C C 19 D C C 19 B 19 C C A C 20 C C C 20 C C 20 20 C C

In Table 6, the numbers indicate the data uploaded by the user, and indicate other users who have commented on the uploaded data. The second user who commented on the data 1 uploaded by B has A, C, and D. A has two comments, C has one comment, and D has two comments. In the example below, only the case of commenting is assumed and other actions are not considered. In addition, it is assumed that K ₁ is 1 in equations (4) and (6). In the following, subscript 1 in E _RE1 (), SA ₁ means that it is related to data 1. Referring to Table 2, the probability density E for A to comment two times on one data E _RE1 (A, 2) is 0.010918535, and referring to Table 4, the probability density E for C to comment one data once _RE1 (C, 1) is 0.302392542, and referring to Table 5, the probability density E _RE1 (D, 2) where D replies to one data twice is 0.003442479.

According to Equation 4, the behavioral index of A's two comments becomes 0.989081465 according to SA ₁ (A, 2) = (1-K ₁ × E _RE1 (A, 2)), and C's one comment. According to SA ₁ (C, 1) = (1-K ₁ × E _RE1 (C, 1)), it becomes 0.697607458, and the index of D's two comments is SA ₁ (D, 2) = ( According to 1-K ₁ x E _RE1 (D, 2)).

According to Equation 6, since A has two comments, more than 0, which is the highest probability of A's comment, and D has two comments, so D has the highest number of comments More than 0, the probability of high probability. However, since C has made one comment, he has made fewer than two of the highest probability of C's commenting. Thus, the behavioral index of A's two comments is obtained according to SA ₁ (A, 2) = K ₁ × ((M _RE (A) + M _RE (A) -E _RE1 (A, 2)). Referring to Table 2, M _RE (A) = 0.57820441, and E _RE1 (A, 2) = 0.01010918535. Thus, SA ₁ (A, 2) = K ₁ × ((M _RE (A) + M _RE (A) -E _RE1 (A, 2)) = (0.57820441 + 0.57820441-0.010918535) = 1.145490285 Index of conducting C's comment SA ₁ (C, 1) = K ₁ × E _RE1 (C And 1) Referring to Table 4, E _RE1 (C, 1) = 0.302392542, thus SA ₁ (C, 1) = K ₁ × E _RE1 (C, 1) = 0.302392542. The behavioral index of D's two comments is obtained according to SA ₁ (D, 2) = K ₁ × ((M _RE (D) + M _RE (D) -E _RE1 (D, 2)). Referring to 5, M _RE (D) = 0.634973438, and E _RE1 (D, 2) = 0.003442479. Thus, SA ₁ (D, 2) = K ₁ × ((M _RE (D) + M _RE (D) -E _RE1 (D, 2)) = (0.634973438 + 0.634973438-0.003442479) = 1.266504397

In operation 130, the data index setting apparatus determines the data index of the uploaded data based on the behavior index. The data index setting device substitutes the behavior index into a predetermined expression to obtain a data index (value). Equation 7 is an example of a formula for obtaining a data index.

In Equation 7, DV (N) represents a data index in DV (N), and N represents data created by the first user. x means a set of users responding to N data. In Equation 7, it can be seen that the data index is calculated as the sum of the behavior indexes of the response behavior of the second user to the behavior of the first user.

In Table 6, an example of calculating a data index for data 1 uploaded by B according to Equation 7 is given. In the following, subscript 1 in DV ₁ , B ₁ , E _RE1 (), SA ₁ means that data 1 is related. According to equation (7), DV ₁ (B ₁ ) = f _DV (SA ₁ (A, 2)) + f _DV (SA ₁ (C, 1)) + f _DV (SA ₁ (D, 2)) . Substituting Equation 4, f _DV (SA ₁ (A, 2)) = (1-K ₁ × E _RE1 (A, 2)) = 0.989081465, f _DV (SA ₁ (C, 1)) = (1 -K ₁ × E _RE1 (C, 1)) = 0.697607458 f _DV (SA ₁ (D, 2)) = (2-K ₁ × E _RE1 (D, 2)) = 0.996557521, so DV ₁ (B ₁ ) = 0.989081465 + 0.697607458 + 0.996557521 = 2.683246444. Substituting Equation 6, f _DV (SA ₁ (A, 2)) = K ₁ × ((M _RE (A) + M _RE (A) -E _RE1 (A, 2)) = 1.145490285, f _DV (SA ₁ (C, 1)) = K ₁ × E _RE1 (C, 1) = 0.330392542, f _DV (SA ₁ (D, 2)) = K ₁ × ((M _RE (D) + M _RE (D) -E _RE1 (D, 2)) = 1.266504397, thus DV ₁ (B ₁ ) = 1.145490285 + 0.302392542 + 1.266504397 = 2.714387224.

In operation 140, the data index setting apparatus determines the data rank according to the data index of the uploaded data among the at least one data index determined. Preferably, the higher the data index, the higher the ranking.

3 is a flowchart illustrating a method of setting a rank in data uploaded to a network service according to another exemplary embodiment of the present invention.

Referring to FIG. 3, since step 310 is the same as step 110 of FIG. 1, a description thereof will be omitted to avoid duplicate description.

In operation 320, the data index setting apparatus determines the influence index of the second user. Influence index refers to the influence that is calculated according to the activity of a user's network service or other user's response to the activity, that is, the degree of response of the other user. Responses to socially famous people's actions or those of famous people's actions have a greater impact or influence on network services than ordinary people's actions. The data index setting device calculates the user's influence index by analyzing a user's behavior in the network service, that is, another user's behavior on the uploaded data. In one embodiment of the present invention, the data index setting apparatus calculates the impact index based on the data index for the data created by the user for a predetermined period. Equation 8 is an expression for calculating the influence index.

In SV _t (A), SV _t () represents the influence index of the interval t, A represents the user of the calculation of the influence index, and DV _t (n) DV _t () represents the data index for A in the interval t N represents a set of data created by A.

For example, the influence index SV ₂ (A) = DV ₂ (A1) + DV ₂ (A2) +. + DV ₂ (AN). Here, A1 to AN refer to the number of data uploaded by the user A during two sections. Each of DV ₂ (A1) to DV ₂ (AN) can be obtained by using Equation 7.

Also, in another embodiment of the present invention, the data index setting device adds an impact index calculated to a point in time or a section immediately before a time for calculating a current impact index to a data index for data created by a user during a predetermined section. The index can also be calculated. Equation 9 is another equation for calculating the influence index.

The difference from Equation 8 in Equation 9 may be calculated by further using the influence index at t-1, the time point or interval before t. The influence index can be obtained by adding all of the data indexes obtained by the user in a predetermined section and adding all of them, and adding the influence index of the previous section to this value. For example, the influence index SV ₂ (A) = SV ₁ (A) + DV ₂ (A1) + DV ₂ (A2) +. + DV ₂ (AN). Here, A1 to AN refer to the number of data uploaded by the user A during two sections. The value of the raw influence index SV ₀ (A) can be set by the operator of the data index setting device.

Since step 330 is the same as step 120 of FIG. 1, a description thereof will be omitted to avoid duplicate description.

In operation 340, the data index setting apparatus determines the data index of the uploaded data based on the influence index and the behavior index of the second user. Step 340 is to add an impact index to the behavioral index to determine the data index when compared to step 130 of FIG. 1. The data index setting device calculates the data index (value) of the extracted index of influence and behavior of the second user according to a predetermined formula. Equation 10 is an example of a formula for obtaining a data index.

Referring to Equation 10, DV (n) represents a data index, and N represents data created by the first user. x means a set of users responding to N data. In addition, SV (x) represents the influence index of x at the previous time point or the interval of the time point or interval to obtain the data index as described above. In Equation 10, it can be seen that the data index is obtained based on the influence index and the behavior index. (11) shows an example of f _DV (SV (x), SA (x)).

Referring to Equation 11, a and b are weights. The weight can be set by the provider of the data index setting method.

In Table 6, the data index for the data 1 uploaded by B is calculated according to Equations 10 and 11 as an example. According to Equation 10, DV ₁ (B ₁ ) = f _DV (SV ₀ (A), SA ₁ (A, 2)) + f _DV (SV ₀ (C), SA ₁ (C, 1)) + f _DV (SV ₀ (D), SA ₁ (D, 2)). In the above example, it is assumed that the weights a, b and the influence indexes SV ₀ (A), SV ₀ (C), and SV ₀ (D) of the previous time point or interval of the second user, respectively, are 1. Referring to Equation 4, f _DV (SA ₁ (A, 2)) = (1-K ₁ × E _RE1 (A, 2)) = 0.989081465, f _DV (SA ₁ (C, 1)) = (1 -K ₁ × E _RE1 (C, 1)) = 0.697607458, f _DV (SA ₁ (D, 2)) = (1-K ₁ × E _RE1 (D, 2)) = 0.996557521, so DV ₁ (B ₁ ) = (1 + 0.98081465) + (1 + 0.697607458) + (1 + 0.996557521) = 5.683246444. Referring to Equation 6, f _DV (SA ₁ (A, 2)) = K ₁ × ((M _RE (A) + M _RE (A) -E _RE1 (A, 2)) = 1.145490285, f _DV (SA ₁ (C, 1)) = K ₁ × E _RE1 (C, 1) = 0.330392542, f _DV (SA ₁ (D, 2)) = K ₁ × ((M _RE (D) + M _{Since RE} (D) -E _RE1 (D, 2)) = 1.266504397, DV ₁ (B ₁ ) = (1 + 1.145490285) + (1 + 0.302392542) + (1 + 1.266504397) = 5.714387224.

When the data rank is determined in FIG. 1 or 3, the data index setting method may further include displaying the uploaded data in priority order according to the data rank.

4 is a diagram illustrating an example of an interface for displaying uploaded data according to a data rank according to an embodiment of the present invention. Referring to FIG. 4, the uploaded data is displayed on the interface 400 according to the categories 410 to 430. In one category 410, uploaded data 411 to 416 are displayed, and uploaded data 411 having the highest data index is displayed first. After that, the next data 412 to 416 is displayed according to the data rank.

The preset value, weight, determined behavior index, determined data index and determined influence index used for calculation in the behavior index are stored in predetermined places of the data index setting device.

5 is a block diagram of an apparatus for ranking a data uploaded to a network service according to an embodiment of the present invention.

Referring to FIG. 5, the data index setting apparatus 500 includes a communication unit 502, a storage unit 504, and a control unit 506, and the data index setting apparatus 500 includes a network service 510 and a user terminal ( 520 and a communication state through a wired or wireless network.

The network service 510 is at least one network service 510 to which a user is subscribed. For example, the network service 510 may be a social network service. The communication unit 502 receives information on the behavior of the second user with respect to data uploaded by the first user from the network service 510 to which the first user is subscribed or registered. A user signifies or registers with at least one network service 510 and uses the service. The data refers to all the entities that are exchanged between the user and the user in the network service 510. For example, the data may be information, news, images, videos, URLs, location information, and the like. The above data are examples only, but are not limited to these. The action of the user refers to the action of the user performed in the network service 510. Examples of user behavior include, but are not limited to, writing posts on network services such as Facebook, commenting on posts or clicking “Like”, uploading data such as images or videos, sharing on uploaded data, networks like Twitter Tweets from the service, retweets of others' tweets, and so on. The above user behavior is also an example only and is not limited thereto. The action of the first user means that the first user uploads data to the network service. In the example of the above user action, writing, uploading data, and tweeting can be viewed as the action of the first user. The action of the second user means a response action to the action of the first user. That is, the action of the second user is a response action to data uploaded by the first user. In the example of the above user action, a second user may view a comment or a like click on a post, share on uploaded data, or retweet.

The data index setting apparatus 500 uses an access token to at least one network service 510 to which the user is subscribed, and thus the user's activities, that is, actions and actions of the user, in the network service 510. Understand the behavior of other users. The data index setting apparatus 500 may access a resource of the network service 510 to which the user subscribes using the access token. The access token is used to request network service 510 APIs on behalf of that user. Various information about the user in the data rank setting network service 510 may be obtained. For example, Facebook, which is an example of the network service 510, will be described. Facebook provides an Open API based on OAuth. The key to OAuth authentication is to enter a user's ID and password on a Facebook page and, if the ID and password match, issue an access token instead. The issued access token can also be retrieved at any time, if desired by the user. If you do not use the OAuth method, if you create a linked page to log in to Facebook, the user inputs the Facebook ID and password of the user in the network service 510 to be linked, the server to server provided by Facebook (Server to Server) ) You can check the ID and password by using the interface. When using this method, the problem is that the user's password can be found in the network service 510 to be interworked, so that a security problem occurs, and the trust of the interworking service must be based on the authentication information issued after authentication. It is also not clear how to recover. To solve this problem, the user's ID and password are entered on a service page provided by Facebook, and instead, an encrypted token is issued to use the Open API. The access token contains information about the APIs that can be accessed, along with information that the user has been authenticated, and in some cases, the token can be set to invalid and can no longer be used. If the user enters his / her ID and password on the page in Facebook and authenticates with the issued access token, the following information can be accessed. Examples of information you can access on Facebook include 'accounts', which is the page information your account has, 'activities', which is profile information about your activity, 'adaccounts', which is your ad management account information, and 'albums', which is album information. , 'Apprequests' (app request information), 'books' (profile information) for the book, 'checkins' (region-based check-in information), 'cover' (pictures) used by the cover, and 'events' (events) Information, 'family' information about family, activity information I did to my friend, 'feed' information about posts I posted, 'friendlists' information about List, 'friendrequests' information about friend requests, 'friends' information, 'games' information about the game profile, 'groups' information on the Facebook group, 'home' information on the postings in my network, 'inbox' information on the inbox , Tube "Interests" information, likes, pages, apps, profile information "likes" information, shared link information "links" information, movie information "movies" information, music profile information 'Music' information, 'mutualfriends' information for common friends, 'notes' information for notes, 'notifications' for notification information, 'outbox' information for sent messages, 'payments' information for payment information, current access 'Permissions' information that is allowed to be accessed by tokens, 'photos' information that is tagged photo information, 'picture' information that is profile photo information, 'posts' information that I have written, and 'score information' posted by game apps 'scores' information, 'statuses' information I posted on the wall, 'tagged' information tagged, 'television' information related to TV, 'updates' information updated, and 'videos' information related to video Have information etc. All. The data index setting apparatus 500 may check the behavior of the first user and the behavior of the second user using some or all of the information accessible using the access token as described above. The data index setting apparatus 500 accesses the network service 510 periodically or aperiodically through the communication unit 502, receives information, and checks the behavior of the users based on this, and thus the influence index and data to be described below. You can get an index.

The controller 506 determines the behavior index for the behavior of the second user. The behavior index refers to a value set for a response behavior to a user's behavior. An example of calculating the behavior index is shown in Equation 1 above. According to an embodiment of the present invention, the behavior index may be obtained based on a preset value according to the aspect of the response behavior. An example of the equation for calculating the behavior index is shown in Equation 2 below. The behavior index is the sum of preset values according to aspects of the response behavior. The use of the sum in the behavioral index is just one example, and the calculation may vary from case to case. According to another embodiment of the present invention, the behavior index may be obtained by adding weights to preset values according to aspects of the response behavior. An example of the equation for calculating the behavior index is shown in Equation 3 below. According to another embodiment of the present invention, the behavior index may be obtained by adding a probability related to the occurrence of the behavior to a preset value according to the aspect of the response behavior. An example of the equation for calculating the behavior index is shown in Equation 4 below. Also in this case, weights may be further added according to the respective behavioral aspects as in the equation (3). According to another embodiment of the present invention, the behavior index may be obtained by using the highest probability among the probability and the probability related to the occurrence of the behavior at a preset value according to the aspect of the response behavior. An example of the equation for calculating the behavior index is shown in Equation 6 below. In another embodiment of the present invention, when there is no access token for the user to obtain the behavior index, it is impossible to obtain information from the network service 510, and thus the behavior index cannot be calculated. In this case, the controller 506 calculates a value obtained by averaging the probability of the user having the access token as the behavior index. In one embodiment of the present invention, the probability is obtained by using normal distribution after extracting information about the behavior. This is an example only, and there is no limit to how the probability is calculated. If the user's action is more than a certain number of times, the probability distribution to perform the action is normally distributed. The probability density function can be assumed to be a Gaussian function. Then, when the mean value and the standard deviation or variance are found, the probability of any behavior can be estimated.

Based on Tables 1 to 6, an example of determining the behavior index using probabilities has been described above, and will be omitted below.

The controller 506 determines the data index of the uploaded data based on the behavior index. The control unit 506 substitutes the behavior index into a predetermined expression to obtain a data index (value). Equation 7 above is an example of a formula for obtaining a data index.

The controller 506 determines the data rank according to the data index of the uploaded data among the data in which the at least one data index is determined. Preferably, the higher the data index, the higher the ranking.

In another embodiment of the present invention, the control unit 506 determines the influence index of the second user. The impact index refers to an influence calculated according to an activity of a user in the network service 510 or another user's response to the activity, that is, the degree of response of the other user. Responses to socially famous people's actions or those of famous people's actions have a greater impact or influence on the network service 510 than those of ordinary people. The control unit 506 calculates the influence index of the user by analyzing the behavior of a user, that is, the behavior of another user with respect to the uploaded data, in the network service 510. In one embodiment of the present invention, the control unit 506 calculates the influence index based on the data index for the data created by the user during a predetermined time point or interval. Alternatively, the controller 506 may calculate the influence index by adding the calculated impact index to the data index for the data created by the user for a predetermined time point or section, immediately before the time or section of the time for calculating the current impact index. Examples of equations for calculating the influence index are shown in Equations 8 and 9 above.

Thereafter, the controller 506 determines the data index of the uploaded data based on the influence index and the behavior index of the second user. The control unit 506 calculates the data index (value) of the extracted influence index and the behavior index of the second user according to a predetermined formula. Equations 10 and 11 are examples of formulas for obtaining data exponents.

The storage unit 504 stores a predetermined value, a weight, a determined behavior index, a determined data index, and a determined impact index used for the calculation in the behavior index.

The controller 506 transmits a command to the user terminal 520 through the communication unit 502 to display the uploaded data in priority order according to the determined ranking of the data index.

The data index setting method as described above can also be embodied as computer readable codes on a computer readable recording medium. A computer-readable recording medium includes all kinds of recording media in which data that can be read by a computer system is stored. Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, and the like. The computer readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner. And, functional programs, codes, and code segments for implementing the disk management method can be easily deduced by the programmers of the present invention.

So far I looked at the center of the preferred embodiment for the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

500: data index setting device
502: communication unit 504: storage unit
506: control unit
510: network services
520: the user terminal 520

Claims (13)

A method for setting the data index in a server for setting a data index of data uploaded to the network service by a first user in a network service,
Confirming, by the server, a response behavior of a second user to the uploaded data;
Extracting, by the server, a preset value for the response behavior of the second user;
Determining, by the server, a behavior index for the response behavior of the second user by adding a probability associated with the occurrence of the response behavior by the second user to the extracted preset value; And
And determining, by the server, the data index of the data by substituting the determined behavior index into a predetermined expression. A method for setting the data index in a server for setting a data index of data uploaded to the network service by a first user in a network service,
Confirming, by the server, a response behavior of a second user to the uploaded data;
Extracting, by the server, a preset value for the response behavior of the second user;
The server adding a preset weight to the extracted preset value;
Determining, by the server, a behavior index for the response behavior of the second user by substituting the predetermined value to which the weight is added to a predetermined expression; And
And determining, by the server, the data index of the data by substituting the determined behavior index into a predetermined expression. A method for setting the data index in a server for setting a data index of data uploaded to the network service by a first user in a network service,
Confirming, by the server, a response behavior of a second user to the uploaded data;
Determining, by the server, an influence index of the second user;
Determining, by the server, a behavioral index for the response behavior of the second user; And
And determining, by the server, the data index of the uploaded data by substituting the determined impact index and the behavior index into a predetermined expression. The method of claim 3, wherein
Determining, by the server, the influence index of the second user,
The server extracting a previous influence index of the second user previously stored in the server;
Determining, by the server, a data index of data uploaded by the second user up to a predetermined point in time; And
And determining, by the server, the influence index of the second user by substituting the extracted previous influence index of the second user and the data index of the data uploaded by the determined second user into a predetermined expression. The data index setting method. The method of claim 3, wherein
Wherein the server determines the behavior index for the response behavior of the second user,
Extracting, by the server, a preset value for the response behavior of the second user;
The server adding a preset weight to the extracted preset value; And
And determining, by the server, a behavior index for the response behavior of the second user by substituting the predetermined value to which the weight is added to a predetermined expression. The method of claim 3, wherein
Wherein the server determines the behavior index for the response behavior of the second user,
Extracting, by the server, a preset value for the response behavior of the second user; And
Determining, by the server, a behavior index for the response behavior of the second user by adding a probability associated with occurrence of the response behavior by the second user to the extracted preset value. Way. The method according to any one of claims 1 to 3,
The server further comprises the step of determining the ranking of the uploaded data according to the determined data index. The method according to any one of claims 1 to 3,
Determining, by the server, the ranking of the uploaded data according to the determined data index; And
And displaying, by the server, priority to display the uploaded data according to the determined data rank. An apparatus for setting a data index of data uploaded to a network service by a first user,
A communication unit receiving information on a response action of a second user to the uploaded data from the network service;
A storage unit which stores a preset value for the response behavior of the second user; And
Extracting a preset value for the response behavior of the second user from the storage unit, and adding a probability associated with the occurrence of the response behavior by the second user to the extracted preset value to the response behavior of the second user. And a control unit for determining a behavioral index of the data and substituting the behavioral index into a predetermined equation to determine a data index of the data. An apparatus for setting a data index of data uploaded to a network service by a first user,
A communication unit configured to receive information about a second user's action on the uploaded data from the network service;
A storage unit which stores a preset value for the response behavior of the second user; And
Extracting a preset value for the response behavior of the second user from the storage unit, adding a predetermined weight to the extracted preset value, and assigning the predetermined value to which the weight is added to a predetermined equation; And a controller configured to determine a behavioral index for the response behavior of the user, and to determine the data index of the data by substituting the determined behavioral index into a predetermined equation. An apparatus for setting a data index of data uploaded to a network service by a first user,
A communication unit configured to receive information about a second user's action on the uploaded data from the network service;
A storage unit to store a previous influence index of the second user; And
Extracts a previous influence index of the second user stored in the storage unit, and determines a data index of data uploaded by the second user up to a predetermined time point; The influence index of the second user is determined by substituting the determined data index of the data uploaded by the determined second user into a predetermined equation, the behavior index for the response behavior of the second user, the determined impact index and And a controller configured to determine a data index of the uploaded data by substituting a behavior index into a predetermined expression. 12. The method according to any one of claims 9 to 11,
And the control unit determines the rank of the uploaded data according to the determined data index. 12. The method according to any one of claims 9 to 11,
And the control unit transmits a command to display the uploaded data in priority order according to the determined data rank to an external device through the communication unit.

Images