JP7200577B2 - Information processing device, information processing system, information processing method, and program. - Google Patents

Description

The present invention relates to content evaluation.

In recent years, a document management system has been used to manage contents such as documents and materials. In such systems, a very large number of contents may be managed. Therefore, in order to efficiently manage a large number of contents, it is required to evaluate the contents.

One example of a content evaluation method is a method of evaluating content based on the total number of accesses to the content.

In addition, Patent Document 1 is cited as an example of a technique for evaluating documents. The document ranking aggregation unit according to Patent Document 1 uses five rules to perform scoring for aggregating scores of documents from reference histories. The five rules are as follows. "(1) Referenced by users belonging to the same group", "(2) Documents registered by users belonging to the same group", "(3) Referenced by specific users", "(4) Referenced by various users" ”, and “(5) Continuous reference for a period of time”.

Furthermore, Patent document 2 is mentioned as a similar technique. Specifically, the document search device according to Patent Document 2 determines the periodicity of the user's search intention expressed in the query in the search log, and reflects the input timing of the query input to the user terminal in the search results. . Further, the technique described in Patent Document 2 determines whether or not there is periodicity in feature words (keywords) through a fast Fourier transform technique in order to determine the periodicity of a user's search intention. Furthermore, the technique described in Patent Document 2 describes that the user ID is fixed, the log is analyzed, and the search behavior of each user is extracted.

Also, as a technology related to the present application, Patent Document 3 and the like can be cited.

Japanese Patent Application Laid-Open No. 2006-092023 Japanese Unexamined Patent Application Publication No. 2011-085992 JP 2011-154487 A

By the way, there are some contents whose reference frequency greatly changes with events that occur periodically as a trigger. Such contents include, for example, materials related to year-end tax adjustments whose frequency of reference increases at the end of the year, and materials related to tax returns whose frequency of reference increases at the end of the fiscal year. In this way, it is necessary to appropriately evaluate content whose reference frequency changes periodically.

However, when a method of evaluating content based on the total number of accesses to content is used, content with a small total number of accesses generally has a low evaluation. Therefore, according to this method, even if the content has a high reference frequency, the evaluation will be low if the total number of accesses is small. In other words, this method cannot appropriately evaluate content whose reference frequency changes periodically.

The technology disclosed in Patent Literature 1 scores documents using five rules, but there is no rule for evaluating content whose reference frequency changes periodically. Therefore, the technique disclosed in Patent Literature 1 cannot appropriately evaluate content whose reference frequency changes periodically.

The technique disclosed in Patent Literature 2 only discloses a technique for determining the periodicity of user's search intention, and does not evaluate the content itself.

The present invention solves the above problems and can provide an information processing device, an information processing system, an information processing method, and an information processing program capable of appropriately evaluating content whose reference frequency changes periodically.

An information processing apparatus according to the present invention includes an acquisition unit that acquires content reference history information, a calculation unit that calculates periodic characteristics of the reference history information based on the reference history information, and content evaluation using the periodic characteristics. and an evaluation unit that performs

An information processing system according to the present invention includes an acquisition unit that acquires content reference history information, a calculation unit that calculates periodic characteristics of the reference history information based on the reference history information, and content evaluation using the periodic characteristics. an input device for inputting a predetermined period; and a display device for displaying an evaluation result of the evaluation unit.

An information processing method according to the present invention acquires reference history information of content, calculates a periodic characteristic of the reference history information based on the reference history information, and evaluates the content using the periodic characteristic.

A program of the present invention obtains reference history information of content, calculates a periodic characteristic of the reference history information based on the reference history information, and evaluates the content using the periodic characteristic.
Let the computer do the work.

According to the present invention, it is possible to provide an information processing device, an information processing method, and an information processing program capable of appropriately evaluating content whose reference frequency changes periodically.

1 is a diagram showing a configuration of an information processing system 100; FIG. FIG. 2 is a flowchart showing the operation of the information processing device 10. As shown in FIG. 5 is a diagram showing a specific example of reference history information stored in a storage unit 50; FIG. 5 is a diagram showing a specific example 500 of periodic characteristics; FIG. FIG. 3 is a conceptual diagram for explaining period T1, amplitude A1, and phase α1; 4 is a diagram showing a specific example of data handled by a prediction unit 40; FIG. FIG. 10 is a diagram showing a specific example of data adjusted using phase; FIG. 10 is a diagram showing a specific example of predicted peak positions; 5 is a diagram showing a specific example of display content 510. FIG. 5 is a diagram showing a specific example of display content 520. FIG. 1 is a diagram showing a configuration of an information processing system 101; FIG. 4 is a flowchart showing the operation of the information processing device 11; FIG. 10 is a diagram showing a specific example in which the calculation unit 200 adds up reference history information; 4 is a diagram showing a specific example of classification reference history information calculated by the calculation unit 200. FIG. 2 is a diagram showing a block diagram of an information processing device 12; FIG. 4 is a flowchart showing the operation of the information processing device 12; It is a block diagram showing an example of a computer.

<First Embodiment>
[Constitution]
A first embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a diagram showing the configuration of an information processing system 100 according to the first embodiment.

The information processing system 100 includes an input device 1 , a display device 2 and an information processing device 10 .

The input device 1 inputs information to the information processing device 10 . Specific examples of the input device 1 include a keyboard, mouse, touch panel, and the like. The input device 1 can input, for example, a period specified by a user or the like to the information processing device 10 . The user may be anyone who can use the input device 1 to input information to the information processing apparatus, such as an administrator of a document management system or a viewer of content.

The display device 2 displays information output by the information processing device 10 . A specific example of the display device 2 is, for example, a display. Note that the configuration of the input device 1 and the display device 2 may be combined into one using a touch panel display or the like.

The information processing device 10 includes an acquisition unit 20 , a calculation unit 30 , a prediction unit 40 , a storage unit 50 , an evaluation unit 60 and an output unit 70 .

The acquisition unit 20 acquires reference history information of content registered in the document management system and stores it in the storage unit 50 . The storage unit 50 will be described later. The reference history information is time-series data indicating the reference frequency of the content per unit time such as date and time. The reference history information also includes information about the start time when acquisition of the information was started and the end time when the acquisition of the information was completed. The reference frequency is information indicating the frequency with which content is referenced, such as the number of times the content has been accessed.

The calculation unit 30 calculates the periodic characteristics of the reference history information by using an analysis method such as Fast Fourier Transform for the reference history information of the content stored in the storage unit 50, and calculates the periodic characteristics of the reference history information. is associated with the content and stored in the storage unit 50 . A periodic characteristic represents a relationship between a period and some physical quantity. For example, the period characteristic includes information about the period (frequency) with which the content is referenced, the amplitude indicating the frequency with which the content is referenced, and the phase (initial phase). A detailed description of the periodic characteristics will be given later. Note that the calculation unit 30 may associate the period, the amplitude, and the phase with each other and store them in the storage unit 50 . For the sake of explanation, a combination of values of period, amplitude, and phase will be referred to as a period set. Note that the calculation unit 30 may use any analysis method as long as it can calculate the periodicity of the content.

The prediction unit 40 acquires the period and phase corresponding to the amplitude equal to or greater than a predetermined threshold from the period characteristics of the content stored in the storage unit 50 . Specifically, the prediction unit 40 acquires a period set including amplitudes equal to or greater than a predetermined threshold. The prediction unit 40 uses the start time of the reference history information, the end time of the reference history information, the acquired period, and the acquired phase to predict the time when the content is expected to be most often referred to in the future. Predict. The timing predicted by the prediction unit 40 is called a reference timing. The prediction unit 40 associates the reference time with the content and stores them in the storage unit 50 . A specific operation of predicting the reference time by the prediction unit 40 will be described later.

The storage unit 50 stores reference history information, period characteristics, and reference times of content in association with each other. The storage unit 50 may divide the area for storing the reference history information, period characteristic, and reference time of the content by type. For example, the storage unit 50 may have a storage area for storing reference history information, a storage area for storing period characteristics, and a storage area for storing reference times.

The evaluation unit 60 evaluates content using periodicity and reference time. For example, to evaluate content, the evaluation unit 60 acquires content whose reference time overlaps during a period specified by the user or the like using the input device 1 (hereinafter referred to as a specified period), and evaluates the acquired content. and ranking using amplitude. It should be noted that any content evaluation may be used as long as the evaluation unit 60 evaluates the content using the periodic characteristics and reference time.

The output unit 70 outputs the result of the evaluation performed by the evaluation unit 60 to the display device 2 . The display device 2 displays information output by the output unit 70 .
[motion]
Next, operations in the first embodiment will be described using a flowchart.

FIG. 2 is a flowchart showing the operation of the information processing device 10. As shown in FIG.

The acquisition unit 20 acquires content reference history information (S1).

The calculation unit 30 calculates periodic characteristics using the reference history information (S2).

The prediction unit 40 acquires a period set including amplitudes equal to or greater than a predetermined threshold. (S3).

The prediction unit 40 predicts the reference time using the acquired period and phase and the start time and end time of the reference history information (S4).

The evaluation unit 60 evaluates the content using the periodic characteristics and reference period (S5).

The output unit 70 outputs the result of the evaluation performed by the evaluation unit 60 (S6).
[Concrete example]
Next, detailed operations in the first embodiment will be described using specific examples.

The acquisition unit 20 acquires reference history information of content registered in the document management system and stores it in the storage unit 50 .

FIG. 3 shows a specific example of reference history information stored in the storage unit 50. As shown in FIG. The reference history information stored in the storage unit 50 is chronological data in which the horizontal axis indicates time and the vertical axis indicates reference frequency.

The calculation unit 30 calculates the period characteristics of the content using an analysis method such as fast Fourier transform for the reference history information stored in the storage unit 50, and associates the content with the period characteristics. , is stored in the storage unit 50 .

Specifically, the calculation unit 30 calculates the frequency and the amplitude and phase corresponding to the frequency by using an analysis technique such as fast Fourier transform on the reference history information. The calculation unit 30 converts the frequency into a period using the reciprocal of the frequency, associates the period with the amplitude and phase corresponding to the period, and stores them in the storage unit 50 .

FIG. 4 shows a specific example 500 of periodic characteristics stored in the storage unit 50 . An example periodic characteristic 500 has a period 501 , an amplitude 502 and a phase 503 . Note that the specific example 500 of the periodic characteristic shown in FIG. 4 is merely an example, and the periodic characteristic is not limited to this specific example as long as it represents the relationship between the period and some physical quantity.

A period 501 indicates the period calculated by the calculator 30 . Amplitude 502 indicates the amplitude corresponding to period 501 . A phase 503 indicates a phase corresponding to the period 501 .

To explain using the specific example of FIG. 4, for example, the period T1 is stored in the storage unit 50 in association with the amplitude A1 and the phase α1.

FIG. 5 shows a conceptual diagram explaining the period T1, the amplitude A1, and the phase α1.

The period T1 shown in FIG. 5 indicates the period in which the content is referenced, the amplitude A1 in FIG. 5 indicates the frequency in which the content is referenced, and the phase α1 in FIG. It shows positional information of fluctuating waves.

The prediction unit 40 acquires the period and phase corresponding to the amplitude equal to or greater than a predetermined threshold from the period characteristics of the content stored in the storage unit 50 . Specifically, the prediction unit 40 acquires a period set including amplitudes equal to or greater than a predetermined threshold. To explain using the example of FIG. 4, the prediction unit 40 acquires T1, A1, and α1 as a period set when the amplitude A1 is equal to or greater than a predetermined threshold. Note that the prediction unit 40 may acquire a plurality of period sets when there are a plurality of amplitudes equal to or greater than a predetermined threshold value, or may acquire the period and phase corresponding to the highest amplitude as the period set. . Hereinafter, a specific example in which the prediction unit 40 acquires T1, A1, and α1 as a period set will be described.

The prediction unit 40 predicts the reference time for the period set using the start time of the reference history information, the end time of the reference history information, the period T1 of the period set, and the phase α1 of the period set.

The process of predicting the reference time by the prediction unit 40 will be described below using a specific example. Note that the following specific example is merely an example for explanation, and if the prediction unit 40 can predict the reference time using the start time, end time, period, and phase, what kind of processing is used? I don't mind.

FIG. 6 shows a specific example of data handled by the prediction unit 40. As shown in FIG. FIG. 6 shows data for period T1. The horizontal axis shown in FIG. 6 represents time. The start point of the data shown in FIG. 6 represents the start time, and the end point of the data shown in FIG. 6 represents the end time. Although not shown in FIG. 6, the data may have a vertical axis representing amplitude. The data shown in FIG. 6 has two positions with the largest amplitude (hereafter referred to as peaks).

FIG. 7 shows a specific example of data adjusted using the phase. The data shown in FIG. 7 is the result of adjusting the phase shift using the phase α1 with respect to the data shown in FIG. Of the two peaks shown in FIG. 7, by sequentially adding the period to the peak closest to the end time, it is possible to calculate the time when the peak comes after the end time. Referring to FIG. 7, for example, by adding one cycle to the peak closest to the end (rightmost) of the two peaks, the position of the next peak can be calculated. Further, by adding two cycles to the peak (rightmost) closest to the end time, the position of the next peak after the next peak can be calculated. Hereinafter, the position predicted as the next and subsequent peaks, which can be calculated by adding the period to the peak closest to the end time, will be referred to as the predicted peak position. In other words, the predicted peak position indicates the position where the peak is predicted after the end time.

FIG. 8 shows a specific example of the predicted peak position. The time indicated by the predicted peak position indicates the reference time. Specifically, when two predicted peak positions are calculated as shown in FIG. 8, each period indicated by the two predicted peak positions indicates a reference period. Although two predicted peak positions are calculated in the example of FIG. 8, the number of predicted peak positions may be one or two or more.

The evaluation unit 60 evaluates content using periodicity and reference time. Specifically, the evaluation unit 60 acquires content whose reference time overlaps with the specified period, and ranks the acquired content using amplitude.

The output unit 70 outputs the result of the evaluation performed by the evaluation unit 60 to the display device 2 . For example, the display content 510 when the user or the like specifies the specified period as within the last two weeks will be specifically described.

FIG. 9 shows a specific example of display content 510 .

Display content 510 includes ranking 511 , content ID 512 , content name 513 , reference time 514 , and amplitude 515 .

The ranking 511 indicates the ranking of the target content. The content ID 512 indicates the ID of the target content. The content name 513 indicates the name of the target content. Reference time 514 indicates the reference time of the target content. Amplitude 515 indicates the amplitude of the content of interest.

For example, by referring to the display content 510, the user or the like can grasp the content that is expected to be frequently referred to among the content that is most likely to be referred to within the last two weeks. This is to rank content based on amplitude. By referring to the display content 510, the user or the like can see that the content ID 3333 ranked first is the content that is expected to be referred to most frequently among the content that will be referred to within the last two weeks. can be understood. Furthermore, the user or the like can understand that the content ID 3333 is content that is expected to be referred to the most on July 14, 2018.

FIG. 10 shows a specific example of the display content 520 when the user or the like designates the designated period as within the last one month. Referring to FIG. 10, it can be seen that content ID 44 and content ID 11111 are newly added to the display contents by extending the specified period from two weeks to one month. In this manner, the present invention can change the content to be displayed according to the period designated by the user or the like. In other words, the present invention can display content of high importance during a period designated by a user or the like.

Note that the specified period is not limited to the most recent specification. A user or the like can designate an arbitrary period as the designated period.

The present invention is used when selecting maintenance targets and setting priorities (hereinafter referred to as maintenance target selection, etc.) from content managed by a management system, and when selecting browsing targets and setting priorities (hereinafter , selection of browsing targets, etc.).

As an example, the reason why the present invention is effective when selecting a maintenance target will be described. Conventionally, among contents whose reference frequency changes with events that occur periodically, when selecting maintenance targets, etc., we have knowledge of events such as what kind of event will occur at what time. I needed it. Furthermore, in addition to the above knowledge, the administrator who performs maintenance needs to have knowledge of the relationship between events and content, i.e., what kind of event the content managed by the management system is related to. .

However, the number of events and contents is enormous, and it is often difficult for administrators to retain such knowledge. In addition, there is a possibility that the content that the administrator prejudices, conjectures, or the like thinks is related to the event, but includes content that is not actually related or has low relevance. Therefore, if the manager selects maintenance targets using the knowledge held by the manager, there is a risk that the accuracy of the selection will decrease.

The present invention does not use specific event information or the like, but uses only the content reference history information managed by the management system to perform the display as shown in FIG. 9 or 10 . Therefore, even if the administrator does not have knowledge of the event and the relationship between the event and the content, or lacks such knowledge, it is possible to select maintenance targets. is.

Further, the present invention performs display as shown in FIG. 9 or 10 using only reference history information independently for each content. Therefore, even if the administrator's knowledge about the relationship between events and content is incorrect, it is possible to select maintenance targets without being affected by the error. It should be noted that such an effect can also be taught when selecting an object to be browsed.

It should be noted that content evaluation can be used in ways other than those described above. For example, it is possible to make use of the setting of a smart folder or the like. In this way, the technology described in the present invention can be widely applied on the viewer side and the administrator side.

In the present embodiment, the input device 1 and the display device 2 have been described as separate devices from the information processing device 10, but the present invention is not limited to this. For example, the information processing apparatus 10 according to the present invention can have the functions of the input device 1 and the display device 2 as an input section and a display section. Specifically, the input unit included in the information processing apparatus 10 can receive input of a specified period from an input device such as a keyboard, and transmit the specified period to the evaluation unit 60 or the like. Further, the display unit included in the information processing device 10 can display information and the like output by the output unit 70 .

As described above, the present invention calculates the periodicity of the reference history information and evaluates the content using the periodicity. Therefore, it is possible to appropriately evaluate the content whose reference frequency changes periodically.
<Second embodiment>
[Constitution]
A second embodiment of the present invention will be described with reference to the drawings. In addition, description is abbreviate|omitted about the structure similar to 1st Embodiment. FIG. 11 is a diagram showing the configuration of an information processing system 101 according to the second embodiment. The information processing apparatus 11 according to the second embodiment newly includes a calculation unit 200 .

The calculation unit 200 calculates classification reference history information by summing reference history information of contents having a common classification and calculating an average of the summed reference history information. The classification of content is information indicating attributes of content, such as tax return and year-end tax adjustment. For example, the classification of content related to tax returns is tax returns. The classification reference history information is information indicating the reference frequency of the classification.

The calculation unit 200 associates the classification reference history information with the classification indicated by the classification reference history information and stores them in the storage unit 50 .

It is assumed that the storage unit 50 stores in advance a list of categories and content belonging to the category in association with each other.
[motion]
Next, main operations in the second embodiment of the present invention will be described. Note that the same configuration as in the first embodiment will be omitted.

FIG. 12 is a flow chart showing the operation of the information processing device 11. As shown in FIG.

The calculation unit 200 sums up the reference history information of contents having a common classification (S11).

The calculation unit 200 calculates the classification reference history information by calculating the average of the combined reference history information (S12).

The calculation unit 200 stores the calculated classification reference history information in the storage unit 50 (S13).
[Concrete example]
Next, detailed operation in the second embodiment of the present invention will be described using a specific example. Note that the same configuration as in the first embodiment will be omitted.

For example, the calculation unit 200 sums the reference history information of two contents classified as final tax returns.

FIG. 13 shows a specific example in which the calculation unit 200 adds up the reference history information.

The calculation unit 200 calculates the classification reference history information by calculating the average of the summed reference history information.

FIG. 14 shows a specific example of the classification reference history information calculated by the calculation unit 200. As shown in FIG.

The calculation unit 200 stores the classification reference history information in the storage unit 50 in association with the classification.

Note that the calculation unit 200 can calculate the start time and end time corresponding to the classification reference history information. For example, the calculation unit 200 calculates the start time and end time corresponding to the classification reference history information by calculating the average of the start time and end time of content having a common classification. Also, the method of calculating the start time and end time corresponding to the classification reference history information is not limited to the above. For example, the start time and end time corresponding to the classification reference history information may be determined by a user or the like, or the start time and end time of arbitrary content among contents having a common classification may be used.

Note that the classification reference history information can be handled in the same manner as the reference history information in the first embodiment. For example, the calculation unit 30 can calculate the periodic characteristics of the classification reference history information by using an analysis technique such as fast Fourier transform. The prediction unit 40 can predict the reference time using the periodic characteristics. The evaluation unit 60 can evaluate the classification using the periodic characteristics and the reference period. The output unit 70 outputs information evaluated by the evaluation unit 60 to the display device 2 .

As a result, the information processing system 101 according to the second embodiment can evaluate the classification as well as the content. In other words, the information processing system 101 according to the second embodiment can appropriately evaluate categories whose reference frequencies change periodically.

In addition, since the information processing system according to the second embodiment collectively evaluates a group of contents having a common classification, it is possible to efficiently evaluate all the contents possessed by the management system rather than evaluating each content individually. Sometimes we can.
<Third Embodiment>
[Constitution]
A third embodiment of the present invention will be described with reference to the drawings. FIG. 15 is a diagram showing a block diagram of the information processing device 12 in the third embodiment. An information processing device 12 in the second embodiment includes an acquisition unit 13 , a calculation unit 14 and an evaluation unit 15 .

The acquisition unit 13 acquires content reference history information.

Based on the reference history information acquired by the acquisition unit 13, the calculation unit 14 calculates the period characteristics of the reference history information.

The evaluation unit 15 evaluates the content using the periodic characteristics calculated by the calculation unit 14 .
[motion]
Next, main operations in the third embodiment of the present invention will be described.

FIG. 16 is a flowchart showing the operation of the information processing device 12. As shown in FIG.

The acquisition unit 13 acquires content reference history information (S21).

Based on the reference history information acquired by the acquisition unit 13, the calculation unit 14 calculates the period characteristics of the reference history information (S22).

The evaluation unit 15 evaluates the content using the periodic characteristics calculated by the calculation unit 14 (S23).

As described above, the present invention calculates the periodicity of the reference history information and evaluates the content using the periodicity. Therefore, it is possible to appropriately evaluate the content whose reference frequency changes periodically.
[program]
A program in the present invention is a program that causes a computer to execute the processing of the present invention. The present invention can be implemented by installing and executing this program on a computer.

Here, a computer that implements the present invention by executing the program of the present invention will be described with reference to FIG.

FIG. 17 is a block diagram showing an example of a computer that implements the present invention.

As shown in FIG. 17 , computer 110 includes CPU 111 , main memory 112 , storage device 113 , input interface 114 , display controller 115 , data reader/writer 116 and communication interface 117 . These units are connected to each other via a bus 121 so as to be able to communicate with each other.

The CPU 111 expands the programs (codes) of the present invention stored in the storage device 113 into the main memory 112 and executes them in a predetermined order to perform various calculations. The main memory 112 is typically a volatile storage device such as a DRAM (Dynamic Random Access Memory). Also, the program according to the present invention is provided in a state stored in a computer-readable recording medium 120 . It should be noted that the program in the present invention may be distributed on the Internet connected via the communication interface 117 .

The storage device 113 may be a hard disk drive or a semiconductor storage device such as a flash memory. Input interface 114 mediates data transmission between CPU 111 and input device 118 . The input device 118 includes, for example, a keyboard, a mouse, and a touch panel. The display controller 115 is connected to the display device 119 and controls display on the display device 119 .

Data reader/writer 116 mediates data transmission between CPU 111 and recording medium 120 , reads programs from recording medium 120 , and writes processing results in computer 110 to recording medium 120 . Communication interface 117 mediates data transmission between CPU 111 and other computers.

Specific examples of the recording medium 120 include general-purpose semiconductor storage devices such as CF (Compact Flash (registered trademark)) and SD (Secure Digital), or magnetic storage media such as flexible disks. . Furthermore, a specific example of the recording medium 120 includes an optical storage medium such as a CD-ROM (Compact Disk Read Only Memory).

Although the embodiments for carrying out the present invention have been described so far, the present invention is not limited to the above-described embodiments. For example, the order of processing in the flowcharts described in this specification is merely an example, and can be changed within a range that does not contradict when implementing the present invention. Moreover, the configuration described in this specification is merely an example, and it is possible to change the configuration within a range that is not inconsistent when implementing the present invention. That is, the present invention can apply various aspects that can be understood by those skilled in the art within a range that is not inconsistent when implementing the present invention. included in the technical scope of

Reference Signs List 1 input device 2 display device 10 information processing device 11 information processing device 12 information processing device 13 acquisition unit 14 calculation unit 15 evaluation unit 20 acquisition unit 30 calculation unit 40 prediction unit 50 storage unit 60 evaluation unit 70 output unit 100 information processing system 101 Information processing system 110 computer 111 CPU
112 main memory 113 storage device 114 input interface 115 display controller 116 data reader/writer 117 communication interface 118 input device 119 display device 120 recording medium

200 calculator 500 specific example of periodic characteristics 501 period 502 amplitude 503 phase 510 display content 511 rank 512 content ID
513 Content name 514 Time information 515 Amplitude 520 Display content

Claims (9)

an acquisition unit that acquires reference history information, which is time-series data indicating the frequency of content references per unit time ;
a calculation unit that calculates periodic characteristics including information on a period in which content corresponding to the reference history information is referenced, an amplitude indicating the frequency of reference to the content, and a phase based on the reference history information ;
Based on the start time at which acquisition of the reference history information was started, the end time at which acquisition of the reference history information was completed, and the periodic characteristics, which are included in the reference history information, the content that will be referred to most often in the future. a prediction unit that predicts a reference time that is a time expected to occur;
an evaluation unit that evaluates content using the periodic characteristics and the reference time ;
with
The calculation unit calculates the periodic characteristic for each content,
The prediction unit predicts the reference time for content having periodic characteristics including an amplitude equal to or greater than a threshold among a plurality of contents.
Information processing equipment. The prediction unit predicts the reference time based on the period, the phase, the start time, and the end time .
The information processing device according to claim 1 . The evaluation unit ranks the information about the content whose reference time is predicted according to the magnitude of the amplitude.
The information processing apparatus according to claim 1 or 2 . Further comprising an input unit for inputting a predetermined period,
The evaluation unit ranks the information about the content whose reference time is within the period input from the input unit according to the magnitude of the amplitude.
The information processing apparatus according to any one of claims 1 to 3 . further comprising a calculation unit that calculates classification reference history information by summing reference history information of contents having a common classification and calculating an average of the summed reference history information,
The calculation unit calculates periodic characteristics of the classification reference history information,
The prediction unit predicts a reference time corresponding to the classification reference history information based on a start time and an end time corresponding to the classification reference history information and periodic characteristics of the classification reference history information,
The evaluation unit evaluates the classification using the periodic characteristics of the classification reference history information and the predicted reference time .
The information processing apparatus according to any one of claims 1 to 4 . The calculation unit calculates the start time and end time corresponding to the classification reference history information by calculating the average of the start time and end time of content having a common classification.
The information processing device according to claim 5 . an information processing apparatus according to any one of claims 1 to 6 ;
an input device for inputting a predetermined period;
a display device for displaying the evaluation result of the evaluation unit;
An information processing system comprising the computer
Acquire reference history information, which is time-series data that indicates the frequency of content references per unit time ,
Based on the reference history information, calculate periodic characteristics including information on a period in which the content corresponding to the reference history information is referenced, an amplitude indicating the frequency with which the content is referenced, and a phase ;
Based on the start time at which acquisition of the reference history information was started, the end time at which acquisition of the reference history information was completed, and the periodic characteristics, which are included in the reference history information, the content that will be referred to most often in the future. Predict the reference time, which is the time when it is expected that
evaluating content using the periodicity and the reference time;
In the calculating step, calculating the periodic characteristic for each content;
In the predicting step, predicting the reference time for content with periodic characteristics including an amplitude equal to or greater than a threshold among a plurality of contents;
Information processing methods. Acquire reference history information, which is time-series data that indicates the frequency of content references per unit time ,
Based on the reference history information, calculate periodic characteristics including information on a period in which the content corresponding to the reference history information is referenced, an amplitude indicating the frequency with which the content is referenced, and a phase ;
Based on the start time at which acquisition of the reference history information was started, the end time at which acquisition of the reference history information was completed, and the periodic characteristics, which are included in the reference history information, the content that will be referred to most often in the future. Predict the reference time, which is the time when it is expected that
evaluating content using the periodicity and the reference time;
let the computer do the work ,
In the calculating process, the periodic characteristic is calculated for each content,
In the prediction process, predicting the reference time for content having periodic characteristics including an amplitude equal to or greater than a threshold among a plurality of content;
program.

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