JP5774247B1 - Score calculation device and score calculation system - Google Patents

Abstract

In an apparatus for calculating a score, by providing specific digital content, it is possible to calculate a score having a high correlation with a process up to a result intended by a provider. A score calculation apparatus acquires at least two feature lists (S210). The feature list includes specific information that may be of interest to the operator of the target content, and a feature score corresponding to a high degree of relevance between the target content and the specific information, according to at least one action for the target content. Each action condition is associated with each other. For each behavioral condition, a weight corresponding to the stage of the behavioral condition included in the process until the provider reaches the target result by providing the target content is assigned to the feature score (S230). The feature scores given weights for each behavior condition are integrated for each specific information, and the score of each specific information is calculated (S240). [Selection] Figure 4

Description

  The present invention relates to a score calculation device and a score calculation system for calculating a score.

2. Description of the Related Art Conventionally, there has been known an apparatus that presents a search keyword with a high score as a candidate when receiving an input of a keyword for a search-linked advertisement (see Patent Document 1).
In the apparatus described in Patent Document 1, the search keyword score is calculated according to the input frequency of the search keyword.

JP 2014-6757 A

  By the way, an apparatus that calculates a score of a keyword is required to calculate a score that has a high correlation with a process up to a result intended by a provider by providing a specific website.

  However, in the apparatus described in Patent Document 1, the score is obtained according to the input frequency of the search keyword, and the obtained score reaches a result intended by the provider by providing a specific website. There was a possibility that the correlation with this process was low.

  In other words, the conventional technique has a problem in that a score having a high correlation with a process up to a result intended by the provider cannot be calculated by providing specific digital content.

  Therefore, an object of the present invention is to make it possible to calculate a score having a high correlation with a process up to a result intended by a provider by providing specific digital content in an apparatus for calculating a score. .

In order to achieve the above object, a score calculation apparatus according to one aspect of the present invention includes an acquisition unit, a grant unit, and a calculation unit.
The acquisition means obtains specific information that may be of interest to an operator of the target content, which is the target digital content, and a feature score corresponding to the high degree of relevance between the target content and the specific information. At least two or more feature lists associated with each are acquired. The action condition mentioned here is defined by at least one action for the target content.

  For each action condition, the assigning means assigns a weight corresponding to the stage of the action condition included in the process up to the provision purpose action to the feature score in the feature list. The provision purpose action referred to here is a result intended by the provider by providing the target content.

The calculating unit integrates the feature scores weighted for each action condition by the adding unit for each feature information, and calculates the score of each feature information.
As described above, the score calculation apparatus calculates the score of each feature information by integrating the feature score to which the weight is given for each feature information. The weight corresponds to the stage of the action condition included in the process leading to the target content providing action.

That is, according to the score calculation device, it is possible to calculate the score of feature information having a high correlation with the process up to the target content providing action.
In addition, since the score calculation device calculates the score of each feature information based on at least two feature lists, the amount of information used for calculating the score of the feature information can be increased. And by increasing the amount of information, it is possible to more accurately grasp the correlation between the process and the characteristic information until the target content providing action is achieved.

For this reason, according to the score calculation apparatus, it is possible to calculate the score of the feature information that more accurately reflects the correlation with the process up to the target content providing action.
The implementation action may include an action of browsing a specific part defined in the target content. In this case, the action condition may be one implementation action or a combination of two or more implementation actions different from each other.

In this case, in the score calculation device, the implementation behavior in the target content can be grasped more accurately, and the implementation behavior can be accurately reflected by the score of the specific information.
The assigning means of the score calculation device may assign a greater weight to an action condition that has a higher degree of connection with the target content providing action.

In such a score calculation device, it is possible to calculate the score of specific information that more appropriately reflects the correlation with the process up to the target content provision act.
By the way, a person who is more motivated to execute the target content provision purpose action is more likely to be performing many implementation actions on the target content.

  For this reason, the assigning unit may assign a greater weight as an action condition having a higher degree of connection to the target content providing purpose action as the number of the executed action actions increases.

According to such a score calculation device, the stage of the process up to the target content providing action can be more accurately represented in the score of the specific information.
In addition, a person who has a high willingness to execute the target content provision purpose action is highly likely to execute the execution action for the target content in the prescribed order.

  For this reason, the assigning unit may assign a large weight to an action condition that is executed in the order in which a plurality of implementation actions are defined as an action condition having a high degree of connection with the target content providing action.

According to such a score calculation device, the stage of the process up to the target content providing action can be more accurately represented in the score of the specific information.
Further, the granting unit may give a weight to the feature score with the purchase behavior as the provisional purpose act.

According to such a score calculation device, a larger value score can be calculated for feature information that leads to purchase behavior.
Note that the acquisition unit may acquire a feature list using the keyword as the specific information or a feature list using the operator's position as the specific information.

  The acquisition unit may acquire a feature list from an apparatus including a detection unit, a collection unit, and a generation unit. The detection means detects that the execution action has been executed. When the collection unit detects that the execution behavior is executed by the detection unit, the collection unit collects information regarding the execution behavior. Further, the generating unit generates a feature list based on the result of collecting information by the collecting unit.

  According to such a score calculation device, the feature list used for calculating the score of the feature information can be acquired from the device that generates the feature list based on the result of collecting the information regarding the implementation behavior.

A score calculation system can be considered as one aspect of the present invention.
The score calculation system includes a detection unit, a collection unit, a generation unit, an acquisition unit, an assignment unit, and a calculation unit.

  The detection means detects that the execution action for the target site has been executed. When the collecting means detects that the implementation action for the target site has been executed, the collection means collects information related to the implementation action. The generating means generates at least two or more feature lists based on the result of collecting information by the collecting means.

  Then, the acquisition unit acquires at least two feature lists generated by the generation unit. For each action condition, the assigning means assigns a weight corresponding to the stage of the action condition included in the process up to the target result by providing the target content to the feature score in the feature list. Further, the calculation unit integrates the feature scores given the weights for each action condition by the granting unit for each specific information, and calculates the score of each specific information.

  According to such a score calculation system, it is possible to calculate a score having a high correlation with the process up to the result intended by the provider by providing the target content, like the score calculation device.

  Further, when a website is the target content, the target content may be provided with a tag that is activated when the implementation action is executed for each implementation action. In this case, when the tag is activated, the detection unit may detect that the execution action for the target content has been executed.

  According to such a score calculation device, the score of the specific information can be calculated based on the feature list generated due to the execution action being actually executed, and the reliability of the score of the specific information is higher Can be.

It is a block diagram which shows schematic structure of the score calculation system to which this invention was applied. It is a flowchart which shows the process sequence of a characteristic list production | generation process. It is a figure which illustrates a feature list. It is a flowchart which shows the process sequence of a score calculation process.

Embodiments of the present invention will be described below with reference to the drawings.
<Score calculation system>
The score calculation system 1 shown in FIG. 1 provides a result (hereinafter referred to as “provision purpose”) that the provider aims at by providing the target content for each piece of specific information that the operator of the target content is interested in. It is a system that calculates a score that reflects the weight corresponding to the stages of the process.

  The target content in the present embodiment is specific digital content to be targeted. The digital content referred to here is content in a digital format, and includes, for example, websites and applications, broadcast content of digital television, and the like. In the present embodiment, a specific website (hereinafter referred to as “target site”) will be described as target content. This target site includes, for example, a website that provides company products and services, and company information.

  The target site in the present embodiment has at least one web page. As an example of the web page, for example, a web page in which an operator confirms the content of a product or service provided by a company, or a web page for requesting materials for the product or service is assumed. Further, as an example of a web page, a web page requesting a quote and a web page where an operator makes a reservation to visit a company are assumed. Furthermore, as an example of the web page, a web page for registering the operator's personal information is assumed. Furthermore, as an example of the web page, there may be a web page for purchasing a product provided by the provider of the target site, a web page for receiving a service provided by the provider of the target site, or the like.

  The provision purpose action is a final action that the provider of the website (digital content) expects the operator to execute. As an example of the provision purpose action, a purchase action for purchasing a product provided by the provider of the target site, an action of receiving a service provided by the provider of the target site, and the like can be considered.

  Further, the specific information in the present embodiment includes a keyword, a URL of a web page, location information indicating the position of the operator, and the like. The keyword referred to here includes the search keyword used for the search, and may be a single word or a combination of a plurality of words.

The score calculation system 1 includes an information terminal 3, a feature list generation device 10, and an information processing device 30.
Among these, the information terminal 3 is a terminal connected to the public communication network 5 and having a function of searching and browsing a website and a function of downloading and executing an application. As this information terminal 3, for example, a well-known personal computer or portable information terminal can be considered. The portable information terminals referred to here include well-known smart phones and tablet terminals, smart televisions, wearable terminals, information terminals mounted on smart cars, and the like.
<Feature list generator>
The feature list generation device 10 is a device that generates a feature list 34, and includes a storage unit 12, an input unit 14, an output unit 16, and a control unit 20.

  The feature list 34 defines a keyword that may be of interest to the operator of the target site and a feature score corresponding to a high degree of relevance between the target site and the keyword, based on at least one action for the target site. Are associated with each action condition.

The storage unit 12 is a rewritable nonvolatile storage device, and is configured by, for example, a hard disk drive or a flash memory.
The input unit 14 receives input of information and data. The input unit 14 includes various input devices such as a keyboard, a pointing device, and a switch. Further, the input unit 14 includes an input port that accepts data input and a connection port connected to the public communication network 5.

  The output unit 16 outputs information and data. The output unit 16 includes various output devices such as a display device and an audio output device. Further, the output unit 16 includes an output port for outputting data and a connection port for connecting to the public communication network 5.

  The control unit 20 is a known control device that is configured around a known microcomputer including a ROM 22, a RAM 24, and a CPU 26. The ROM 22 stores data and programs that need to retain the stored contents even when the power is turned off. The RAM 24 temporarily stores data. The CPU 26 executes processing according to a program stored in the ROM 22 or RAM 24.

In the ROM 22 of the storage unit 12 or the control unit 20, a process for the control unit 20 to execute a feature list generation process for monitoring an operator's action on the target site and generating a feature list 34 based on the monitoring result. The program is stored.
<Information processing device>
The information processing apparatus 30 includes a storage unit 32, an input unit 36, an output unit 38, and a control unit 40.

  The storage unit 32 is a rewritable nonvolatile storage device, and includes, for example, a hard disk drive or a flash memory. The storage unit 32 stores the feature list 34 generated by the feature list generation process.

  The input unit 36 receives input of information and data. The input unit 36 includes various input devices such as a keyboard, a pointing device, and a switch. Further, the input unit 36 includes an input port and a connection port for receiving data input.

  The output unit 38 outputs information and data. The output unit 38 includes various output devices such as a display device, an audio output device, and a printing device. Further, the output unit 38 includes an output port for outputting data and a connection port.

  The control unit 40 is a known control device that is configured around a known microcomputer including a ROM 42, a RAM 44, and a CPU 46. The ROM 42 stores data and programs that need to retain the stored contents even when the power is turned off. The RAM 44 temporarily stores data. The CPU 46 executes processing according to a program stored in the ROM 42 or the RAM 44.

  The ROM 42 of the storage unit 32 or the control unit 40 has a score calculation process for calculating a score for each keyword (hereinafter referred to as “keyword feature score”) based on the feature list 34 generated by the feature list generation process. A processing program to be executed by the control unit 40 is stored.

That is, the information processing apparatus 30 functions as a score calculation apparatus described in the claims by executing a score calculation process.
<Feature list generation processing>
Next, a feature list generation process executed by the control unit 20 of the feature list generation device 10 will be described.

When the feature list generation process is activated, the control unit 20 sets a tag for each specific location in the target site as shown in FIG. 2 (S110).
The tag is a well-known tag that monitors an operator's action on the target site (hereinafter referred to as “implementation action”). Each of these tags is activated when the implementation action is executed.

The implementation behavior referred to here includes, for example, access to a target site and a web page constituting the target site, an on-click operation, and other operations that can be performed on the website.
That is, in S110, for example, a tag may be set on the target site itself or the web page constituting the target site so that access to the target site or the web page constituting the target site is detected as an implementation action. Moreover, in S110, you may set a tag in the one part prescribed | regulated to the target site so that on-click operation may be detected as implementation action. Furthermore, in S110, a tag may be set at a part of the site defined in the target site so that a request for a document or a request for an estimate is detected as an implementation action. Furthermore, in S110, a tag may be set at a part of the site defined in the target site so that registration of personal information is detected as an implementation action.

In addition, what is necessary is just to set the specific site | part which sets a tag, ie, the implementation action which should monitor whether it implemented, according to the provision purpose action, etc. arbitrarily.
Subsequently, the control unit 20 monitors whether or not each tag set in S110 is activated, and collects a log when the tag is activated (S120). In the log collected in S120, at least tag identification information for identifying a tag, each keyword used for a search by the operator who activated the tag, and operator identification information for identifying the operator are associated with each other. It is a thing.

Note that the operator specifying information referred to here includes, for example, a cookie. Furthermore, the log collected in S120 may include the time when the tag is activated.
Further, the control unit 20 determines whether or not a predetermined time specified in advance has elapsed (S130). The specified time referred to here is a period required for the access to the target site to reach a certain number or more, for example, a period such as one week or one month.

  If the specified time has not elapsed as a result of the determination in S130 (S130: NO), the control unit 20 returns the feature list generation process to S120. In S120, tag activation is monitored and log collection is continued.

  On the other hand, if the prescribed time has elapsed as a result of the determination in S130 (S130: YES), the control unit 20 calculates a keyword feature score for each action condition based on the log collected in S120 (S140). Further, in S140, the control unit 20 generates a feature list 34 in which the calculated feature score is associated with the keyword for each action condition.

The action condition in this embodiment includes a single action condition and a plurality of action conditions.
The single action condition referred to here is that one execution action defined in advance is executed. The determination of whether or not one implementation action has been performed may be performed based on whether or not the tag has been activated.

  Further, the multiple action condition is that at least two or more execution actions prescribed in advance by the same operator are executed. As specific examples of the multiple action conditions, it is conceivable that both the request for the material and the request for the estimate are performed, and the on-click operation is performed after the personal information is registered. Furthermore, as a specific example of the multiple action conditions, it is conceivable to make a reservation for a visit to a company that provides the target site after both requesting materials and requesting an estimate.

  Moreover, what is necessary is just to perform the determination whether the same operator performed at least 2 or more implementation action based on a log. Specifically, if a cookie associated with each tag identification information is common, it may be determined that a plurality of tags are activated by the same operator.

The contents of these action conditions may be arbitrarily set by the provider of the target site depending on the provision purpose action as long as it is defined by at least one action.
In addition, as a feature score calculation method, the number of keyword inputs may be counted, and the result of the calculation may be multiplied by a coefficient so that the keyword that has entered the target site has a larger value. It is done. However, the feature score calculation method is not limited to this, and various methods are conceivable.

Thereafter, the control unit 20 ends the feature list generation process.
That is, in the feature list generation process, the control unit 20 detects that the implementation action for the target site has been executed based on the activation of the tag. And if it detects that the implementation action with respect to an object site was performed, the log will be collected. Based on the collected logs, at least two or more feature lists 34 in which keywords and feature scores are associated with each behavior condition shown in FIG. 3 are generated. Note that the number of unique users described in the feature list 34 shown in FIG. 3 is the number of users (operators) who satisfy the action conditions.
<Score calculation processing>
Next, a score calculation process executed by the information processing apparatus 30 will be described.

  When the score calculation process is started, the control unit 40 acquires at least two or more feature lists 34 generated for each behavior condition as shown in FIG. 4 (S210). The acquisition source of the feature list 34 may be the storage unit 32 or the storage unit 12 of the feature list generation device 10. In the latter case, it may be acquired via a network or may be acquired via a portable storage medium.

  Subsequently, the control unit 40 calculates a weight for each action condition (S220). In S220, the control unit 40 calculates a weight corresponding to the stage of the action condition included in the process up to the provision purpose action. In the calculation of the weight, a larger weight is calculated for an action condition having a higher degree of connection with the provision purpose action.

  Specifically, the control unit 40 has a larger value as an action condition having a higher degree of execution action, that is, an action condition having a higher degree of connection with the intended purpose action as an action condition having a larger number of activated tags. A weight may be calculated. In addition, the control unit 40 sets a behavior condition in which a plurality of implementation actions are executed in a prescribed order, that is, a behavior condition in which a tag is activated in a prescribed order as an action condition having a high degree of connection with the provision purpose action. A large value weight may be calculated.

  As an example of this weight calculation method, a multiple regression analysis with “Y” as the number of persons who performed the scheduled action and “X” as each action condition can be considered. In the case of using the multiple regression analysis, the determination as to whether or not the operator has performed the scheduled action is performed by, for example, storing the personal information submitted by the person when the scheduled action is performed and the feature list generating apparatus 10. What is necessary is just to implement by collating with the operator specific information contained in the recorded log.

  Note that the weight calculation method is not limited to the multiple regression analysis, and for example, a single regression analysis may be used, or other methods may be used. Other approaches include determining arbitrary coefficients.

  Further, the control unit 40 assigns the weight calculated in S220 to the feature score (S230). Specifically, in S230, the control unit 40 assigns a weight corresponding to the action condition to the keyword feature score in the feature list 34 for each action condition. As a method for assigning a weight to the feature score, multiplication or addition can be considered.

  Subsequently, the control unit 40 calculates the keyword feature score by integrating the feature score given the weight for each action condition in S230 for each keyword (S240). The integration referred to here includes calculating a representative value of the feature score for each keyword. Specific examples of calculating the representative value include adding a weighted feature score for each behavior condition, multiplying a weighted feature score for each behavior condition, and averaging the weighted feature scores for each behavior condition It is conceivable to calculate a value.

Further, the control unit 40 generates a list in which the keyword feature score calculated in S240 is associated with the keyword, and outputs the list through the output unit 38 (S250).
Thereafter, the control unit 40 ends the score calculation process.

  That is, in the score calculation process, at least two feature lists 34 are acquired. Then, the weight corresponding to the stage of the action condition included in the process up to the provision purpose action is calculated for each action condition. Furthermore, the calculated weight for each action condition is assigned to the characteristic score of the corresponding action condition.

Subsequently, in the score calculation process, the feature scores given weights for each behavior condition are integrated for each keyword, and the keyword feature score is calculated for each keyword.
[Effect of the embodiment]
As described above, in the score calculation process, the score of each keyword is calculated by integrating the feature score to which the weight is given for each keyword. The weight corresponds to the stage of the action condition included in the process up to the provision purpose action.

That is, according to the information processing apparatus 30, it is possible to calculate the score of a keyword having a high correlation with the process up to the provision purpose action.
Furthermore, in the score calculation process, a higher weight is calculated and given to the feature score for an action condition having a higher degree of connection with the provision purpose action.

As a result, the information processing apparatus 30 can calculate a keyword score that more appropriately reflects the correlation with the process up to the provision purpose action.
In addition, in the score calculation process, since the score of each keyword is calculated based on at least two feature lists, the amount of information used for calculating the keyword score can be increased. And by increasing the amount of information, it is possible to more accurately grasp the correlation between the process leading to the provision purpose action and the keyword.

For this reason, according to the information processing apparatus 30, it is possible to calculate the score of the keyword that more accurately reflects the correlation with the process leading to the provision purpose action.
By the way, a person with a high willingness to execute the provision purpose action is more likely to execute a number of implementation actions on the target site. For this reason, in the score calculation process, if a greater weight is given as the number of executed actions performed increases, the stage of the process up to the provision target action can be accurately reflected in the keyword score.

  In addition, it is highly likely that a person who has a high willingness to execute the provision purpose action is browsing the implementation actions for the target site in a prescribed order. For this reason, in the score calculation process, if a large weight is given to action conditions that are executed in the order in which a plurality of action actions are defined, the process stage up to the provision purpose action can be accurately determined in the keyword score. Can be reflected.

In the present embodiment, if a specific example of the provision purpose action is a purchase action, a keyword characteristic score having a larger value can be calculated for a keyword that leads to an implementation action that is considered to be highly motivated to purchase. As a result, the list generated by the score calculation process can be used for specifying a keyword that directly relates to purchase behavior.
[Other Embodiments]
As mentioned above, although embodiment of this invention was described, this invention is not limited to the said embodiment, In the range which does not deviate from the summary of this invention, it is possible to implement in various aspects.

  For example, in the above-described embodiment, the calculation of “weight” is executed in S220 of the score calculation process, but the process of calculating “weight” may not be executed in S220 of the score calculation process. . The process of calculating the “weight” may be executed independently of the score calculation process. Furthermore, the subject that performs the process of calculating the “weight” may not be the information processing apparatus 30, but may be an apparatus other than the information processing apparatus 30.

  Moreover, in the said embodiment, although the tag provided in the website activated, it detected that implementation action was performed, However, In this invention, the method of detecting implementation action is restricted to this is not. For example, when an application is assumed as the target content, it may be detected that the implementation action has been executed via a software development kit (SDK). The implementation behavior in this case includes downloading of the application and various operations on the application.

  In addition, the log collected by the feature list generation device includes at least implementation action identification information for identifying the implementation action, each keyword used by the operator who executed the implementation action for the search, and operator identification information for identifying the operator. May be associated with each other. The operator specifying information referred to here may be identification information assigned to each operator, terminal identification information assigned to each terminal device, and the like, in addition to a cookie. Further, the log may include advertisement identification information for identifying advertisement content.

  Furthermore, in the above embodiment, as an example of the implementation action, access to the target site and the web page constituting the target site, on-click operation, and other operations that can be performed on the website are assumed. Implementation actions in are not limited to this. For example, the implementation action in the present invention may include downloading an application, purchasing an item, searching by voice input, and the like. That is, the action content in the present invention may be any action content as long as it is some action on the target content.

In the above-described embodiment, a website is assumed as an object operated by the operator. However, an object operated by the operator of the present invention may be digital content.
Furthermore, in the above embodiment, a keyword is assumed as an example of the specific information, but the specific information in the present invention may include location information indicating the position of the information terminal 3. In this case, location information may be included in addition to the keyword, or only location information may be included instead of the keyword. As an example of the location information acquisition method, it is conceivable to acquire location information detected by a known method based on a signal from a GPS satellite received by a GPS receiver provided in the information terminal 3.

  Thus, if location information is included as specific information, a score can be calculated for a position where a person with a high degree of realization of the provision purpose action is interested. If a score can be calculated for such a position, traffic advertisements and location-based advertisements can be used for placement.

  In the above embodiment, the execution subject of the feature list generation process is the control unit 20 of the feature list generation device 10. However, in the present invention, the execution subject of the feature list generation process is the information processing device 30. The control unit 40 may be used. In this case, the feature list generation device 10 may be omitted.

  In addition, the execution subject of the score calculation process in the above embodiment is the control unit 40 of the information processing apparatus 30, but the execution subject of the score calculation process in the present invention is the control unit 20 of the feature list generation apparatus 10. Also good. In this case, the information processing apparatus 30 may be omitted.

  In addition, the aspect which abbreviate | omitted a part of structure of the said embodiment is also embodiment of this invention. Further, an aspect configured by appropriately combining the above embodiment and the modification is also an embodiment of the present invention. Moreover, all the aspects which can be considered in the limit which does not deviate from the essence of the invention specified by the wording described in the claims are the embodiments of the present invention.

In addition to the above-described score calculation device and score calculation system, the present invention can be realized in various forms such as a program executed by a computer to calculate a keyword feature score.
[Correspondence between Embodiment and Claims]
Finally, the relationship between the description of the above embodiment and the description of the scope of claims will be described.

  The function obtained by executing S210 in the score calculation process of the above embodiment is an example of the obtaining unit described in the claims, and the function obtained by executing S230 is in the claims. It is an example of the described provision means. Moreover, the function obtained by executing S240 is an example of the calculation means described in the claims.

  Furthermore, the function obtained by executing S120 in the feature list generation processing of the above embodiment is an example of the detection means and the collection means described in the claims, and the function obtained by executing S140 Is an example of the generating means described in the claims.

  DESCRIPTION OF SYMBOLS 1 ... Score calculation system 3 ... Information terminal 5 ... Public communication network 10 ... Feature list production | generation apparatus 12, 32 ... Memory | storage part 14,36 ... Input part 16,38 ... Output part 20,40 ... Control part 22,42 ... ROM 24 44, RAM 26, 46 ... CPU 30 ... Information processing device

Claims (11)

At least one implementation with respect to the target content of specific information of interest to an operator of the target content, which is the target digital content, and a feature score corresponding to a high degree of relevance between the target content and the specific information An acquisition means for acquiring at least two or more feature lists associated with each action condition defined by the action;
For each of the action conditions, a weight corresponding to the stage of the action condition included in the process up to the provision purpose action, which is a result that the provider aims for by providing the target content, is set in the feature list. A granting means for granting to the feature score;
A score calculation apparatus comprising: a calculation unit that integrates, for each of the specific information, a feature score that is given a weight for each action condition by the adding unit, and calculates a score for each of the specific information. The implementation action includes an action of operating a specific part defined in the target content,
The score calculation apparatus according to claim 1, wherein the behavior condition is one implementation behavior or a combination of two or more different implementation behaviors. The giving means is
The score calculation apparatus according to claim 1 or 2, wherein a greater weight is given to the action condition having a higher degree of connection with the provision purpose action. The giving means is
The score calculation apparatus according to claim 3, wherein the action condition having a higher degree of connection with the provision purpose action is set as the number of the executed action is increased. The giving means is
5. The score calculation according to claim 3, wherein the action conditions that are executed in a prescribed order are set as the action conditions having a high degree of connection with the provision purpose action. apparatus. The giving means is
The score calculation device according to any one of claims 1 to 5, wherein the weight is assigned with a purchase action as the provision purpose action. The acquisition means includes
The score list according to any one of claims 1 to 6, wherein the feature list is acquired using a keyword as the specific information. The acquisition means includes
The score calculation device according to any one of claims 1 to 7, wherein the feature list is acquired using the position of the operator as the specific information. The acquisition means includes
Detection means for detecting that the execution action has been executed, collection means for collecting information relating to the execution action when the detection means detects that the execution action has been executed, and collecting information by the collection means The score calculation device according to any one of claims 1 to 8, wherein the feature list is acquired from a device including a generation unit that generates the feature list based on a result obtained. . Detecting means for detecting that at least one implementation action is performed on the target content that is the target digital content;
A collection unit that collects information regarding the implementation behavior when the detection unit detects that the implementation behavior is performed on the target content;
Based on the result of collecting information by the collecting means, specific information that may be of interest to an operator of the target content, and a feature score corresponding to the degree of relevance between the target content and the specific information Generating means for generating at least two feature lists associated with each action condition defined by the at least one implementation action;
Obtaining means for obtaining at least two or more feature lists generated by the generating means;
Giving means for assigning a weight corresponding to the behavior condition included in the process up to a result intended by the provider by providing the target content to the feature score in the feature list for each behavior condition When,
A score calculation system comprising: a calculation unit that integrates, for each of the specific information, a feature score that is given a weight for each action condition by the adding unit, and calculates a score for each of the specific information. The target content is a website,
In the target content, a tag that is activated when the execution action is executed is provided for each of the execution actions.
The detection means includes
The score calculation system according to claim 10, wherein when the tag is activated, the execution behavior is detected.

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