WO2024079833A1

WO2024079833A1 - Information processing device, output method, and output program

Info

Publication number: WO2024079833A1
Application number: PCT/JP2022/038152
Authority: WO
Inventors: 隼人内出; 英祐仲澤; 修治宮下; 新士石原
Original assignee: 三菱電機株式会社
Priority date: 2022-10-13
Filing date: 2022-10-13
Publication date: 2024-04-18

Abstract

An information processing device (100) has: a storage unit (110) which stores one or more documents; an acquisition unit (120) which acquires search contents; a search unit (130) which performs search on the basis of the search contents for the one or more documents; a calculation unit (140) which calculates accuracy corresponding to each of a plurality of search results obtained by the search; and an output control unit (150). When the search is performed, the acquisition unit (120) acquires first information which is at least one of the failure scale and the failure occurrence probability corresponding to each of the plurality of search results. When the first information is acquired, the calculation unit (140) calculates display order of each of the plurality of search results on the basis of the accuracy and the first information. The output control unit (150) sorts the plurality of search results on the basis of the display order, and outputs the plurality of search results .

Description

Information processing device, output method, and output program

This disclosure relates to an information processing device, an output method, and an output program.

Sometimes, a failure occurs in a device, system, etc. A user uses a computer to perform a search to gather information about the failure. The search results are then displayed on the computer. A technology has been proposed for displaying search results (see Patent Document 1). The administrator terminal in Patent Document 1 displays the resolved issues selected by highly skilled support personnel at the top of the search results.

JP 2015-170179 A

With the above technology, search results selected by highly skilled support personnel are displayed at the top of the results. However, the search results that a user is looking for may not necessarily match the search results selected by highly skilled support personnel. As a result, the search results that a user is looking for may not be displayed at the top of the results.

The purpose of this disclosure is to display the search results that users are looking for at the top.

An information processing device according to one aspect of the present disclosure is provided. The information processing device has a storage unit that stores one or more documents, an acquisition unit that acquires search content, a search unit that performs a search on the one or more documents based on the search content, a calculation unit that calculates a degree of certainty corresponding to each of a plurality of search results obtained by the search, and an output control unit. When the search is performed, the acquisition unit acquires first information that is at least one of a failure scale and a failure occurrence probability corresponding to each of the plurality of search results. When the first information is acquired, the calculation unit calculates a display order for each of the plurality of search results based on the degree of certainty and the first information. The output control unit sorts the plurality of search results based on the display order, and outputs the plurality of search results.

According to this disclosure, search results that users are looking for can be displayed at the top.

FIG. 1 is a diagram showing a search system according to a first embodiment. FIG. 2 is a diagram illustrating hardware included in an information processing device according to a first embodiment. 2 is a block diagram showing functions of the information processing device according to the first embodiment; FIG. 13 is a diagram showing an example (part 1) of a management table according to the first embodiment; FIG. 2 is a diagram showing a record-based FTA method according to the first embodiment. FIG. 13 is a diagram showing an example (part 2) of the management table according to the first embodiment; 4 is a flowchart illustrating an example of processing executed by the information processing device according to the first embodiment. FIG. 11 is a block diagram showing the functions of an information processing device according to a second embodiment. 13 is a specific example of the process of the second embodiment. 13 is a flowchart illustrating an example of a process executed by an information processing device according to a second embodiment. 13 is a flowchart illustrating an example of a failure occurrence probability calculation process according to the second embodiment. FIG. 11 is a block diagram showing the functions of an information processing device according to a third embodiment. FIG. 13 is a diagram showing an example of key word information according to the third embodiment. FIG. 13 is a diagram showing an example of cluster information according to the third embodiment. 13 is a flowchart illustrating an example of processing executed by an information processing device according to a third embodiment. FIG. 13 is a diagram showing a specific example of highlight processing in the third embodiment.

Below, an embodiment will be described with reference to the drawings. The following embodiment is merely an example, and various modifications are possible within the scope of this disclosure.

Embodiment 1.
1 is a diagram showing a search system according to the first embodiment. The search system includes an information processing device 100 and a terminal device 200. The information processing device 100 and the terminal device 200 communicate with each other via a network. The network is a wired network or a wireless network.

The information processing device 100 is a device that executes an output method.
The terminal device 200 is a device used by a user. The user inputs search content to the terminal device 200. The search content includes a search keyword and a query. The user may input the search content to the information processing device 100.

Next, the hardware of the information processing device 100 will be described.
2 is a diagram showing hardware included in the information processing apparatus according to embodiment 1. The information processing apparatus 100 includes a processor 101, a volatile storage device 102, and a non-volatile storage device 103.

The processor 101 controls the entire information processing device 100. For example, the processor 101 is a CPU (Central Processing Unit), an FPGA (Field Programmable Gate Array), etc. The processor 101 may be a multiprocessor. The information processing device 100 may also have a processing circuit.

The volatile memory device 102 is the main memory device of the information processing device 100. For example, the volatile memory device 102 is a RAM (Random Access Memory). The non-volatile memory device 103 is an auxiliary memory device of the information processing device 100. For example, the non-volatile memory device 103 is a HDD (Hard Disk Drive) or an SSD (Solid State Drive).

Next, functions of the information processing device 100 will be described.
3 is a block diagram showing functions of the information processing device of embodiment 1. The information processing device 100 includes a storage unit 110, an acquisition unit 120, a search unit 130, a calculation unit 140, and an output control unit 150.

The storage unit 110 may be realized as a storage area secured in the volatile storage device 102 or the non-volatile storage device 103 .
The acquiring unit 120, the searching unit 130, the calculating unit 140, and the output control unit 150 may be partly or entirely realized by a processing circuit. Also, the acquiring unit 120, the searching unit 130, the calculating unit 140, and the output control unit 150 may be partly or entirely realized as a module of a program executed by the processor 101. For example, the program executed by the processor 101 is also referred to as an output program. For example, the output program is recorded on a recording medium.

The storage unit 110 stores one or more documents. For example, a document is made up of one or more sentences.
The storage unit 110 may also store a management table.

4 is a diagram showing an example (part 1) of a management table according to the first embodiment. For example, the management table 111 is stored in the storage unit 110. The management table 111 is also referred to as management information. The management table 111 may be created based on past failure cases.
The management table 111 has the following items: "No.", system name, failure information, failure scale, occurrence probability according to FTA (Fault Tree Analysis) method, and failure occurrence probability.

In the "No." field, an identifier is registered. In the system name field, the name of the system in which the failure occurred is registered. In the failure information field, failure information is registered. In the failure scale field, a value indicating the scale of the failure is registered. For example, the scale of the failure is expressed as a value within the range of 0.00 to 1.00. In the FTA method occurrence probability field, the probability of the FTA method occurrence is registered. Here, a diagram showing the "No. 1" record using the FTA method is shown.

FIG. 5 is a diagram showing the record-based FTA method of the first embodiment. FIG. 5 shows top events. Fault information corresponds to the top events. In addition, "connector of device X is disconnected" and "connector of device Y is disconnected" are basic events.

Furthermore, FIG. 4 shows that the occurrence probability of "connector coming loose on device X" is 0.02. The occurrence probability of "connector coming loose on device Y" is 0.01. Thus, in FIG. 4, the occurrence probability of the FTA method is expressed as a value in the range of 0.00 to 1.00. The expression of the occurrence probability of the FTA method may be different. For example, the occurrence probability of the FTA method is expressed as a value in the range of 0 to 100%.

In the fault occurrence probability field in FIG. 4, a fault occurrence probability based on the occurrence probability of the FTA method is registered. The fault occurrence probability may be calculated by the calculation unit 140. For example, the calculation unit 140 uses formula (1) to calculate the fault occurrence probability of the record "No. 1". The calculation unit 140 may also calculate the fault occurrence probability by rounding down to the fourth decimal place.

The management table 111 may also have other items. Other items are shown below.

FIG. 6 is a diagram showing an example (part 2) of a management table according to the first embodiment. The management table 111 further includes items for the date of occurrence, cause, countermeasure method, and countermeasure completion date.

Returning to FIG. 3, the acquisition unit 120 will be described.
The acquiring unit 120 acquires the search content. For example, the acquiring unit 120 acquires the search content from the terminal device 200.

The search unit 130 performs a search based on the search content for one or more documents. As a result, multiple search results are retrieved. In addition, when performing a search, the search unit 130 may perform a morphological analysis on the search content and use the information obtained by the morphological analysis to perform the search.

The calculation unit 140 calculates the degree of accuracy corresponding to each of the multiple search results. For example, the calculation unit 140 calculates the degree of match between the search content and the search result corresponding to each of the multiple search results as the accuracy. Specifically, the calculation unit 140 calculates the accuracy by comparing the words included in the search content with the words included in the search results. As a result, each of the multiple search results is associated with a accuracy. Here, the search unit 130 may exclude from the search results any search results other than a predetermined number of search results from the top when the search results are sorted in descending order based on accuracy. In other words, the search unit 130 may exclude search results with accuracy less than the top n. Here, n is a positive integer. For example, the search unit 130 excludes search results less than the top 5 from the multiple search results. As a result, search results with high accuracy remain. In other words, information suitable as a search result remains.

The acquisition unit 120 acquires the fault scale corresponding to the search result. In detail, the acquisition unit 120 acquires the fault scale corresponding to the fault information having the same content as the search result. For example, when the management table 111 is stored in the storage unit 110, the acquisition unit 120 refers to the management table 111 and acquires the fault scale corresponding to the fault information having the same content as the search result. Specifically, when the search result is "Faults A1 and A2 occurred in device X," the acquisition unit 120 acquires the fault scale of "0.2." Here, the management table 111 may be stored in an external device. For example, the external device is a cloud server or the like. When the management table 111 is stored in an external device, the acquisition unit 120 acquires the fault scale from the external device by transmitting an instruction to the external device to transmit the fault scale corresponding to the fault information having the same content as the search result.

If there is no fault information in the management table 111 that has the same content as the search result, the acquisition unit 120 does not acquire the fault scale. Here, in the following explanation, it is assumed that each of the multiple search results has the same content as the fault information in the management table 111. Therefore, the acquisition unit 120 performs the above processing for each of the multiple search results. As a result, the fault scale corresponding to each of the multiple search results is obtained.

The acquisition unit 120 acquires the failure occurrence probability corresponding to the search result. In detail, the acquisition unit 120 acquires the failure occurrence probability corresponding to the failure information having the same content as the search result. For example, the acquisition unit 120 acquires the failure occurrence probability calculated by the calculation unit 140. Also, for example, if the management table 111 is stored in the storage unit 110, the acquisition unit 120 refers to the management table 111 and acquires the failure occurrence probability corresponding to the failure information having the same content as the search result. Specifically, if the search result is "Failures A1 and A2 occurred in device X," the acquisition unit 120 acquires the failure occurrence probability of "0.029." Also, if the management table 111 is stored in an external device, the acquisition unit 120 acquires the failure occurrence probability from the external device by transmitting an instruction to the external device to transmit the failure occurrence probability corresponding to the failure information having the same content as the search result.

The acquiring unit 120 does not acquire a failure occurrence probability if failure information having the same content as the search result does not exist in the management table 111. In the following description, it is assumed that each of the multiple search results has the same content as the failure information in the management table 111. Therefore, the acquiring unit 120 performs the above process for each of the multiple search results. As a result, a failure occurrence probability corresponding to each of the multiple search results is obtained.
This provides the degree of certainty, the scale of failure, and the probability of failure occurrence corresponding to each of the multiple search results.

The calculation unit 140 calculates the display order of each of the multiple search results based on the certainty, the scale of the fault, and the probability of the fault occurring. In detail, the calculation unit 140 calculates one display order using formula (2).

Note that Ks, Kd, and Ko are coefficients. For example, Ks, Kd, and Ko are set by the user. Ks, Kd, and Ko are used as weights. Furthermore, Ks, Kd, and Ko do not necessarily need to be included in equation (2).

The calculation unit 140 calculates the display order for each of the multiple search results using formula (2). As a result, a display order is associated with each of the multiple search results.

The output control unit 150 rearranges the multiple search results based on the display order. The output control unit 150 outputs the multiple search results. For example, the output control unit 150 outputs the multiple search results to the terminal device 200. Also, for example, the output control unit 150 outputs the multiple search results to the display of the information processing device 100. As a result, the multiple search results are displayed on the terminal device 200, a display, etc.

Next, the process executed by the information processing device 100 will be described with reference to a flowchart.
FIG. 7 is a flowchart illustrating an example of processing executed by the information processing device according to the first embodiment.
(Step S11) The acquiring unit 120 acquires search contents.
(Step S12) The search unit 130 searches one or more documents based on the search content, thereby obtaining a plurality of search results.
(Step S13) The calculation unit 140 calculates the likelihood corresponding to each of the multiple search results.

(Step S14) The acquiring unit 120 acquires the failure scale corresponding to each of the multiple search results.
(Step S15) The obtaining unit 120 obtains a failure occurrence probability corresponding to each of the multiple search results.
(Step S16) The calculation unit 140 calculates a display order for each of the search results based on the certainty, the fault scale, and the fault occurrence probability.
(Step S17) The output control unit 150 rearranges the search results based on the display order.
(Step S18) The output control unit 150 outputs a plurality of search results.

According to the first embodiment, the information processing device 100 calculates the display order of each of the multiple search results based on the accuracy, the scale of the failure, and the probability of the failure occurring. As a result, each of the multiple search results is associated with a display order based on the scale of the failure and the probability of the failure occurring that the user desires. The information processing device 100 sorts the multiple search results based on the display order, and outputs the multiple search results. Thus, the information processing device 100 can display the search results that the user desires at the top.

The above describes a case where the fault scale and fault occurrence probability corresponding to each of the multiple search results are obtained. At least one of the fault scale and fault occurrence probability corresponding to each of the multiple search results may be obtained. Note that at least one of the fault scale and fault occurrence probability is also referred to as first information. When the first information is obtained, the calculation unit 140 calculates the display order of each of the multiple search results based on the accuracy and the first information.

As a result, for example, each of the multiple search results is associated with a display order based on the scale of the problem desired by the user. When calculating the display order, the calculation unit 140 calculates one display order using formula (3).

The calculation unit 140 calculates the display order for each of the search results using formula (3).
In this way, each of the multiple search results is associated with a display order based on the scale of the failure desired by the user. Therefore, the user can know the multiple search results in the display order based on the scale of the failure. Therefore, the information processing device 100 can display the search results desired by the user at the top. Note that equation (3) does not need to include a coefficient.

Furthermore, for example, each of the search results is associated with a display order based on the failure occurrence probability desired by the user. When calculating the display order, the calculation unit 140 calculates one display order using formula (4).

The calculation unit 140 calculates the display order for each of the search results using formula (4).
In this way, each of the multiple search results is associated with a display order based on the failure occurrence probability desired by the user. Therefore, the user can know the multiple search results in a display order based on the failure occurrence probability. Therefore, the information processing device 100 can display the search results desired by the user at the top. Note that the formula (4) does not need to include a coefficient.

When calculating the display order, the calculation unit 140 uses coefficients to calculate the display order. That is, the calculation unit 140 calculates the display order using formula (2) including coefficients Ks, Kd, and Ko. The coefficients Ks, Kd, and Ko are used as weights. Therefore, when it is desired to influence the display order, large values are set for the coefficients Ks, Kd, and Ko. For example, when the user places importance on the scale of the failure, a large value is set for Kd. As a result, search results related to the scale of the failure are displayed at the top. In this way, the information processing device 100 can use coefficients to display search results related to the content that the user places importance on at the top.

Embodiment 2.
Next, a description will be given of embodiment 2. In embodiment 2, differences from embodiment 1 will be mainly described. Furthermore, in embodiment 2, description of matters common to embodiment 1 will be omitted.

FIG. 8 is a block diagram showing the functions of the information processing device of the second embodiment. The information processing device 100 further includes an extraction unit 160 and a modification unit 170. A part or all of the extraction unit 160 and the modification unit 170 may be realized by a processing circuit. Also, a part or all of the extraction unit 160 and the modification unit 170 may be realized as a program module executed by the processor 101.

The acquiring unit 120 acquires the search content. For example, the search content is "Fault A3 occurred in device A where condensation occurred."
The extraction unit 160 extracts events from the search content. For example, the extraction unit 160 extracts events from the search content using an event list generated based on information from the FTA method as shown in FIG. 5. For example, the event list includes basic events and intermediate events. Specifically, for example, the event list includes "condensation." If the search content is "Fault A3 occurred in device A that was condensed," the extraction unit 160 extracts "condensation."

The subsequent processing will be explained with reference to the drawings.
FIG. 9 shows a specific example of the process according to the second embodiment.
The acquiring unit 120 acquires the occurrence probability of the FTA method corresponding to the search result and the occurrence probability event of the FTA method. For example, if the search result is "Failures A3 and A4 occurred in device X," the acquiring unit 120 identifies the failure information of No. 4 in the management table 111, which is the same as the search result. The acquiring unit 120 acquires the occurrence probability of the FTA method of No. 4 in the management table 111 and the occurrence probability event of the FTA method of No. 4.
The acquisition unit 120 acquires the occurrence probability of the FTA method corresponding to the search result and the event of the occurrence probability of the FTA method from the storage unit 110 or an external device.

If the event with the occurrence probability of the FTA method is the same as the extracted event, the modification unit 170 changes the occurrence probability of the FTA method corresponding to the extracted event to the maximum value. Since the extracted event "condensation" and the event with the occurrence probability of the FTA method "condensation" are the same, the modification unit 170 changes the occurrence probability of the FTA method corresponding to the event "condensation" to the maximum value "1.0".

The reason for changing the occurrence probability of the FTA method to the maximum value is as follows. If the search content includes "condensation," it can be assumed that the user wants to know the probability of a fault occurring when condensation is the cause of the fault. Therefore, the change unit 170 changes the occurrence probability of the FTA method corresponding to "condensation" to the maximum value.

The calculation unit 140 calculates the failure occurrence probability corresponding to each of the multiple search results based on the occurrence probability of the FTA method corresponding to each of the multiple search results. For example, the calculation unit 140 calculates the failure occurrence probability using formula (5).

The subsequent processing is the same as in embodiment 1.

Next, the process executed by the information processing device 100 will be described with reference to a flowchart.
Fig. 10 is a flowchart showing an example of a process executed by the information processing device of the second embodiment. The process of Fig. 10 differs from the process of Fig. 7 in that step S15a is executed. Therefore, step S15a will be described in Fig. 10. Descriptions of the processes other than step S15a will be omitted.
(Step S15a) The information processing device 100 executes a failure occurrence probability calculation process.

Fig. 11 is a flowchart showing an example of a failure occurrence probability calculation process according to embodiment 2. The process in Fig. 11 corresponds to step S15a.
(Step S21) The extraction unit 160 extracts events from the search contents.
(Step S22) The acquisition unit 120 acquires the occurrence probability of the FTA method corresponding to each of the multiple search results and the event of the occurrence probability of the FTA method.

(Step S23) The change unit 170 selects an event of occurrence probability of one FTA method.
(Step S24) The change unit 170 determines whether the event of the occurrence probability of the selected FTA method is the same as the extracted event.
If the events are the same, the process proceeds to step S25. If the events are different, the process proceeds to step S26.

(Step S25) The change unit 170 changes the occurrence probability of the FTA method to the maximum value.
(Step S26) The calculation unit 140 calculates a failure occurrence probability based on the occurrence probability of the FTA method.
(Step S27) The change unit 170 judges whether or not all have been selected. If all have been selected, the process ends. If not all have been selected, the process proceeds to step S23.

According to the second embodiment, the information processing device 100 changes the occurrence probability of the FTA method to the maximum value. The failure occurrence probability based on the changed occurrence probability of the FTA method becomes higher. Therefore, the display order of the search results corresponding to the failure occurrence probability also becomes higher. Therefore, the information processing device 100 can display the search results desired by the user at a higher position.

Embodiment 3.
Next, a description will be given of embodiment 3. In embodiment 3, differences from embodiment 1 will be mainly described. Furthermore, in embodiment 3, description of matters common to embodiment 1 will be omitted.

FIG. 12 is a block diagram showing the functions of an information processing device according to the third embodiment. The information processing device 100 further includes an information generating unit 180. A part or all of the information generating unit 180 may be realized by a processing circuit. Also, a part or all of the information generating unit 180 may be realized as a program module executed by the processor 101.

The information generating unit 180 identifies important words based on the fault information registered in the management table 111. For example, the information generating unit 180 identifies important words using a key word dictionary. For example, the information generating unit 180 identifies the important word "Fault A3" based on the fault information No. 2.
The information generating unit 180 associates the identified key word with the scale of the problem. For example, the information generating unit 180 associates the key word "problem A3" with the scale of the problem of "0.8".
The information generating unit 180 associates the failure scale with a color. For example, the information generating unit 180 associates a failure scale of "0.8" with the color "red."
In this way, the keyword, the scale of the damage, and the color are associated with each other. Information indicating the correspondence between the keyword, the scale of the damage, and the color is called keyword information. The keyword information may indicate the correspondence between the keyword and the color. An example of keyword information is shown below.

13 is a diagram showing an example of the important word information according to the third embodiment. The important word information 112 indicates the correspondence between the important word, the scale of the damage, and the color. The information generating unit 180 stores the important word information 112 in the storage unit 110 or an external device.
The information generating unit 180 clusters multiple pieces of fault information registered in the management table 111. The information generating unit 180 associates a color with the result obtained by clustering (i.e., a cluster). In this way, the clusters and the colors are associated with each other. Information indicating the association between the clusters and the colors is called cluster information. An example of cluster information is shown below.

FIG. 14 is a diagram showing an example of cluster information in the third embodiment. Cluster information 113 indicates the correspondence between the cluster to which the fault information belongs and the color. The information generating unit 180 stores the cluster information 113 in the storage unit 110 or an external device.

Next, the process executed by the information processing device 100 will be described with reference to a flowchart.
Fig. 15 is a flowchart showing an example of processing executed by the information processing device of the third embodiment. The processing of Fig. 15 differs from the processing of Fig. 7 in that steps S17a and 17b are executed. Therefore, steps S17a and 17b will be described in Fig. 15. Descriptions of processing other than steps S17a and 17b will be omitted.

(Step S17a) The acquiring unit 120 acquires the important word information 112 and the cluster information 113. For example, the acquiring unit 120 acquires the important word information 112 and the cluster information 113 from the storage unit 110 or an external device. The acquiring unit 120 may acquire only the important word information 112. The acquiring unit 120 may acquire only the cluster information 113.
(Step S17b) The output control unit 150 performs color-based highlighting on key words included in a plurality of search results using the key word information 112. Here, a specific example of highlighting is shown.

FIG. 16 is a diagram showing a specific example of the highlighting process of the third embodiment. FIG. 16 shows the state in which the search results are arranged in display order. For example, the output control unit 150 uses the key word information 112 to underline in red the key words "XXX" and "ZZZ" contained in the search result, fault information A. As a result, the key words "XXX" and "ZZZ" are highlighted.

The output control unit 150 also uses the cluster information 113 to highlight multiple search results based on color. For example, the output control unit 150 uses the cluster information 113 to color an area that includes the search result, fault information A, in blue. This highlights the fault information A.

According to the third embodiment, important words are highlighted, so that the user can easily find them. In addition, the user can recognize the importance of important words by the difference in color.

In addition, by highlighting the area containing the search results (i.e., fault information), the user can recognize the cluster of the search results. For example, the user can recognize that the search results, fault information A and fault information C, belong to the same cluster.

Here, the important word information 112 may indicate the correspondence between important words, the scale of the disorder, and fonts. The important word information 112 may also be expressed as indicating the correspondence between important words and fonts. The output control unit 150 uses the important word information 112 to highlight important words included in multiple search results based on fonts. As a result, important words are displayed in a font based on the important word information 112. In other words, important words are displayed in a font that is different from characters other than important words. This allows the user to easily find important words.

The important word information 112 may also indicate the correspondence between important words, the scale of the disorder, and the thickness of the characters. The important word information 112 may also be expressed as indicating the correspondence between important words and the thickness of the characters. The output control unit 150 uses the important word information 112 to highlight important words included in multiple search results based on the thickness of the characters. As a result, important words are displayed in a thickness of characters based on the important word information 112. In other words, important words are displayed in a thickness that differs from the thickness of characters other than important words. This allows the user to easily find important words.

Furthermore, embodiment 3 can be applied to embodiment 2.

The features of each of the embodiments described above can be combined as appropriate.

100: Information processing device; 101: Processor; 102: Volatile storage device; 103: Non-volatile storage device; 110: Storage unit; 111: Management table; 112: Key word information; 113: Cluster information; 120: Acquisition unit; 130: Search unit; 140: Calculation unit; 150: Output control unit; 160: Extraction unit; 170: Change unit; 180: Information generation unit; 200: Terminal device.

Claims

a storage unit for storing one or more documents;
an acquisition unit for acquiring search contents;
a search unit that searches the one or more documents based on the search content;
A calculation unit that calculates a degree of accuracy corresponding to each of a plurality of search results obtained by the search;
An output control unit;
having
the acquiring unit acquires, when the search is performed, first information corresponding to each of the plurality of search results, the first information being at least one of a failure scale and a failure occurrence probability;
the calculation unit, when the first information is acquired, calculates a display order of each of the plurality of search results based on the certainty and the first information;
the output control unit sorts the search results based on the display order, and outputs the search results.
Information processing device.
the acquiring unit acquires a fault scale and a fault occurrence probability corresponding to each of the plurality of search results when the certainty is calculated,
the calculation unit, when the failure scale and the failure occurrence probability are acquired, calculates a display order of each of the plurality of search results based on the accuracy, the failure scale, and the failure occurrence probability.
The information processing device according to claim 1 .
The failure occurrence probability is a failure occurrence probability based on the occurrence probability of the FTA method,
3. The information processing device according to claim 1 or 2.
an extraction unit that extracts an event from the search content;
A modification unit;
and
The acquisition unit acquires an occurrence probability of an FTA method corresponding to each of the plurality of search results and an event of the occurrence probability of the FTA method;
The change unit changes the occurrence probability of the FTA method corresponding to the extracted event to a maximum value when the event of the occurrence probability of the FTA method is the same as the extracted event;
the calculation unit calculates the failure occurrence probability corresponding to each of the plurality of search results based on an occurrence probability of an FTA method corresponding to each of the plurality of search results;
3. The information processing device according to claim 1 or 2.
The acquiring unit acquires keyword information indicating a correspondence relationship between a keyword and a color,
the output control unit uses the keyword information to highlight the keyword included in the plurality of search results based on the color.
The information processing device according to claim 1 .
The acquiring unit acquires key word information indicating a correspondence between key words and fonts,
the output control unit uses the keyword information to highlight, based on the font, a keyword included in the plurality of search results.
The information processing device according to claim 1 .
the acquiring unit acquires key word information indicating a correspondence relationship between a key word and a character thickness;
the output control unit uses the keyword information to highlight the keyword included in the plurality of search results based on the thickness of the characters.
The information processing device according to claim 1 .
the acquiring unit acquires cluster information indicating a correspondence relationship between a cluster to which the fault information belongs and a color,
the output control unit uses the cluster information to highlight the search results corresponding to the plurality of pieces of fault information based on the color.
The information processing device according to claim 1 .
the search unit excludes from the search results, search results other than a predetermined number of search results from the top when the search results are sorted in descending order based on the accuracy.
The information processing device according to claim 1 .
When calculating the display order, the calculation unit calculates the display order by using a coefficient.
The information processing device according to claim 1 .
An information processing device having a storage unit for storing one or more documents,
Get the search results,
performing a search based on the search content on the one or more documents;
Calculating a probability corresponding to each of a plurality of search results obtained by the search, and acquiring first information corresponding to each of the plurality of search results, the first information being at least one of a failure scale and a failure occurrence probability;
Calculating a display order for each of the plurality of search results based on the certainty and the first information;
sorting the plurality of search results based on the display order, and outputting the plurality of search results;
output method.
An information processing device having a storage unit for storing one or more documents,
Get the search results,
performing a search based on the search content on the one or more documents;
Calculating a probability corresponding to each of a plurality of search results obtained by the search, and acquiring first information corresponding to each of the plurality of search results, the first information being at least one of a failure scale and a failure occurrence probability;
Calculating a display order for each of the plurality of search results based on the certainty and the first information;
sorting the plurality of search results based on the display order, and outputting the plurality of search results;
The output program that causes the processing to occur.