Visualization device, visualization method, and computer program

Abstract

According to the present disclosure, it is possible to provide a visualization device, a visualization method, and a program that can more appropriately visualize event information. [Solution] The visualization device includes a first event information acquisition unit that acquires first event information for a first event that took place in the past, a second event information acquisition unit that acquires second event information for a second event that is the subject of investigation, a comparison unit that compares the first event information with the second event information for multiple comparison items, and an output unit that performs display output so as to display a first icon in a manner according to the number of comparison items.

Description

[Technical Field]

[0001] The present disclosure relates to a visualization device, a visualization method, and a computer program. [Background technology]

[0002] Patent Document 1 discloses an information retrieval device that searches for images similar to a key image. This device extracts image features and calculates the degree of similarity of the image to the key image. The device generates an icon for each feature and displays it on a screen. Furthermore, the device displays the icons so that they are spaced apart by a distance corresponding to the degree of similarity. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2001-195415 Summary of the Invention [Problem to be solved by the invention]

[0004] In such a device, it is desirable to appropriately visualize information in order to identify information similar to the target information. [Means for solving the problem]

[0005] The visualization device according to the present disclosure includes a first event information acquisition unit that acquires first event information of a first event that took place in the past, a second event information acquisition unit that acquires second event information of a second event that is the subject of investigation, a comparison unit that compares information about the first event information and the second event information for a plurality of comparison items, and an output unit that performs display output so as to display a first icon in a manner according to the number of comparison items.

[0006] The visualization method of the present disclosure acquires first event information for a first event that took place in the past, acquires second event information for a second event that is the subject of investigation, compares the first event information with the second event information for a number of comparison items, and performs display output so as to display a first icon in a manner according to the number of comparison items.

[0007] The computer program according to the present disclosure causes a computer to execute the following processes: acquiring first event information of a first event that took place in the past; acquiring second event information of a second event that is the subject of investigation; comparing the first event information with the second event information for a plurality of comparison items; and displaying and outputting the first icon in a manner corresponding to the number of comparison items. [Effects of the Invention]

[0008] According to the present disclosure, it is possible to provide a visualization device, a visualization method, and a program that can visualize information more appropriately. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram illustrating an example of a configuration of a visualization device according to an embodiment. [Figure 2] FIG. 1 is a block diagram illustrating an example of a configuration of a visualization device. [Figure 3] 10 is a table for explaining event information. [Figure 4] FIG. 10 is a diagram illustrating an example of a display screen. [Figure 5] 10 is a flowchart illustrating an example of a visualization method. [Figure 6] FIG. 1 is a block diagram schematically illustrating a hardware configuration of an information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0010] Embodiment 1 Hereinafter, an embodiment will be described with reference to the drawings. First, an example of a visualization device according to the embodiment will be described. FIG. 1 is a block diagram showing an example of the configuration of an information processing device according to the embodiment. An information processing device 100 is a visualization device that visualizes event information. It includes a first event information acquisition unit 101, a second event information acquisition unit 102, a comparison unit 104, and an output unit 107.

[0011] The first event information acquisition unit 101 acquires first event information for a first event that took place before the time of investigation. The second event information acquisition unit 102 acquires second event information for a second event to be investigated. The comparison unit 104 compares the first event information with the second event information for a plurality of comparison items. The output unit 107 performs display output so as to display the first icon in a manner according to the number of comparison items. In this way, event information can be appropriately visualized.

[0012] Embodiment 2 A visualization device and a visualization method according to some embodiments will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the configuration of an information processing device 100, which is a visualization device according to some embodiments. The information processing device 100 functions as a visualization device for visualizing information related to event information that is the target of investigation.

[0013] In the following description, a person related to an event is referred to as a related person. A person who uses the information processing device 100 to investigate an event and its related people is referred to as an investigator. Here, the investigator may be one user or multiple users. A related person is a person who was witnessed at the time of the event or a person who has been confirmed to have been related to the event. In addition, a related person may also be a person who caused the event or a person who acted with the person who caused the event. A related person can also be referred to as a person to be investigated or a person being investigated who is investigated by an investigator. For example, an investigator uses the information processing device 100 to investigate whether there are any similar events to the event being investigated.

[0014] The information processing device 100 is, for example, a device such as a server, a cloud server, a personal computer, or a smartphone. The information processing device 100 has hardware such as a processor, a memory, and an input / output device. The processor executes a program recorded in the memory to perform the processing described below. The information processing device 100 is not limited to a single physical device. For example, multiple devices having communication functions may work together to function as the information processing device 100. The communication function may be compatible with multiple communication standards such as WiFi (registered trademark), Bluetooth (registered trademark), 5G (fifth generation), and LTE (Long Term Evolution).

[0015] The information processing device 100 includes a first event information acquisition unit 110, a second event information acquisition unit 120, a memory unit 130, a comparison unit 140, a determination unit 150, a map information generation unit 160, an output unit 170, an input unit 180, and a similarity calculation unit 190.

[0016] Application programs (also called apps) for executing each function may be installed in the information processing device 100. For example, the information processing device 100 has a map app, a search app, and the like.

[0017] The input unit 180 accepts input from the researcher. The input unit 180 has input devices such as a keyboard, a mouse, and a touch panel. The input unit 180 may also have a microphone for voice input. For example, the researcher operates the input unit 180 to input information about the event they wish to research, the period they wish to research, etc.

[0018] The output unit 170 outputs information for visualizing the event information. Typically, the output unit 170 has a display device that displays the event information. For example, the output unit 170 displays a map and an icon indicating the event. The output unit 170 displays the icon on the map at a position corresponding to the location where the event occurred.

[0019] The display device includes a monitor, a display, etc. The display device may be installed separately from the processor and the recording device. When the display device is a device separate from the information processing device 100, the output unit 170 outputs a display signal to the display device. In this case, the output unit 170 includes a display interface such as HDMI (High-Definition Multimedia Interface: registered trademark).

[0020] As will be described later, the map information generating unit 160 generates map information for displaying icons. For example, the map information generating unit 160 superimposes various information on a map displayed on a map application. For example, the map information generating unit 160 adds icons, text, etc. indicating information on the map. The output unit 170 performs display output so that a map including various information is displayed on a display device. Here, display output includes processing for outputting a signal for display or processing for displaying on a display device. In the following description, it is assumed that the output unit 170 is equipped with a display device.

[0021] The storage unit 130 includes a memory, a hard disk drive, or a solid-state drive (SSD) for storing event information for multiple events. The storage unit 130 may include storage located remotely from the processor, etc. The data stored as event information may be structured data.

[0022] Event information will be described using FIG. 3. FIG. 3 is a table showing an example of items included in event information. Event information includes items related to the date and time of the event, the location, the method, and related parties. The related party items include the clothing the related party was wearing at the time of the event, their age, gender, etc. The storage unit 130 stores multiple items of data for each event. For example, when a user operates a keyboard or the like to input event information, the storage unit 130 stores the event information. The date and time of the event may also include information such as the start time and end time. The location of the event, which is location information indicating the location where the event occurred, may be data indicating latitude and longitude, or may be data indicating the name of a facility, etc.

[0023] Furthermore, the event information items may be freely inputtable. For example, the user may input keywords that indicate the characteristics of the event in the free input field. The event information may also include items other than those mentioned above. For example, the event information may include items such as the tools used in the event, the heights and builds of the people involved, etc. Furthermore, the event information may include an item that indicates whether the event is resolved or unresolved.

[0024] The storage unit 130 may store the event information as a database. For example, the storage unit 130 stores the event information by assigning an identification number to each event. In this manner, the storage unit 130 stores each item of multiple event information. Note that although the event information is shown as text data, it may also include data other than text data, such as photo data. The storage unit 130 may also store text data extracted from photo data as event information.

[0025] Large Language Models (LLMs) and the like can be used to extract event information. For example, by using LLMs, the information processing device 100 can efficiently extract event information distributed across multiple systems and documents. The information processing device 100 uses LLMs to extract data related to each of the above items for each event. The information processing device 100 then stores the extracted data in the storage unit 130. Based on reports and the like input by researchers, the information processing device 100 can extract event information for multiple events. Each piece of event information includes data for multiple items. The information processing device 100 may also extract event information from event information input by multiple research organizations. The device that extracts information and the device that stores it may be separate devices.

[0026] The first event information acquisition unit 110 acquires, as the first event information, event information about an event that took place before the time of investigation. For example, the first event information acquisition unit 110 acquires, as the first event information, event information stored in the storage unit 130. As shown in FIG. 3, the first event information includes multiple items related to the date and time, location, method, involved parties, etc. Of course, data does not need to be entered into all items of the event information. In other words, the information in some items may be unknown.

[0027] The second event information acquisition unit 120 acquires, as second event information, event information of a second event to be investigated. The second event is an event that the investigator wishes to investigate. The second event may be an event that occurred in the past before the time of the investigation. Specifically, when the investigator inputs event information of a newly occurring event, the second event information acquisition unit 120 acquires the input event information as second event information. Furthermore, two or more events may be input as the second event.

[0028] Furthermore, the second event information acquisition unit 120 may acquire, as the second event information, event information stored in the storage unit 130. For example, when a user inputs specific information for identifying an event, the second event information acquisition unit 120 performs a search based on the specific information. The second event information acquisition unit 120 acquires, as the second event information, event information that matches the specific information from the event information stored in the storage unit 130.

[0029] The comparison unit 140 compares the first event information with the second event information for multiple comparison items. As described above, the event information includes multiple items. The comparison unit 140 compares the first event information with the second event information for each item. The comparison unit 140 determines whether the first event information and the second event information are similar for each item. The comparison unit 140 outputs the comparison result to the output unit 170.

[0030] For example, if the comparison item is the gender of the related person, and the gender in the first event information matches that in the second event information, the comparison unit 140 determines that they are similar. Alternatively, if the comparison item is the age of the related person, and the age in the first event information is 25 years old and the age in the second event information is in the twenties, the comparison unit 140 determines that they are similar. Alternatively, the comparison unit 140 compares the first event information and the second event information and calculates the difference between the two values. The comparison unit 140 determines whether they match by comparing the difference value with a threshold.

[0031] The comparison unit 140 may compare all of the multiple items included in the event information, or may compare only some of the items. For example, if the first event information or the second event information does not include information on some of the items, the comparison unit 140 will not compare those items. Alternatively, the researcher may select items to compare or items not to compare. The number of comparison items to compare may be variable.

[0032] The output unit 170 performs display output so as to display a first icon indicating a first event in a format according to the number of comparison items compared by the comparison unit 140. Fig. 4 is a diagram showing an example of the display screen 20 displayed by the output unit 170. The output unit 170 generates data for display by referring to the event information, the comparison results, etc.

[0033] (Visualization example 1) A map 30 is displayed on the display screen 20. Event icons 71 and 81 are displayed on the map 30. Event icons 71 and 81 indicating events are displayed on the map 30. The map 30 is displayed in an app window and can be zoomed in and out, moved, and the like. Therefore, the researcher can zoom in or out on the map area where the map 30 is displayed. The researcher can also move or change the display area to display a location different from the currently displayed location. Therefore, when the researcher zooms in, zooms out, moves, or changes the map 30, the display positions and number of the event icons 71 and 81 change. The area of ​​the map that is initially displayed may be determined by the number of event icons 71 included in the map. For example, the area of ​​the map that is initially displayed can be expanded or reduced so that the number of event icons 71 becomes a predetermined number. For example, if the number of event icons 71 is small, the output unit 170 expands the display area and increases the number of event icons 71. The position of the map that is initially displayed may also be determined by the location of the target second event.

[0034] The event icon 81 is a target icon that indicates a second event that is the target of investigation. The output unit 170 displays the event icon 81 at the location of the second event on the map 30. The event icon 71 is an icon that indicates a first event. The output unit 170 displays the event icon 71 at the location where the first event occurred on the map 30. Here, event icons 71 that indicate a plurality of first events included in the range of the map 30 are displayed.

[0035] In this way, the output unit 170 displays the event icons 71 and 81 based on the location information indicating the location where the event occurred. In other words, the output unit 170 displays the event icons 71 and 81 at positions corresponding to the locations where the events occurred, thereby making it possible to visualize the geographical proximity of the events. A first event that occurred near the location where the second event occurred is displayed on the map. In this way, event information can be appropriately visualized. The researcher can easily recognize the first event that occurred near the second event. The event icon 71 indicating the first event becomes the first icon indicating similarity or proximity to the second event.

[0036] The output unit 170 displays the event icon 71 in a manner according to the number of comparison items. For example, the output unit 170 changes the color of the event icon 71 based on the comparison result. The greater the number of similar comparison items, the closer the output unit 170 displays the event icon 71 in a color that is closer to the display color of the event icon 81. The output unit 170 changes the hue of the icon according to the number of similar items. In this way, event information can be visualized appropriately.

[0037] For example, the output unit 170 displays the event icon 81 of the investigation target in red. The event icon 81 of the first event that is similar to the second event in all items is the same red as the event icon 71. The event icon 81 of the first event that is not similar to the second event in all items is blue. The event icon 81 of the first event that is similar to the second event in only some items is a color between red and blue, for example, green. The greater the number of similar comparison items, the closer to red the event icon 71 becomes, for example, pink. The fewer the number of similar comparison items, the less close to red the event icon 71 becomes, for example, blue. In this way, event information can be appropriately visualized. For example, an investigator can easily identify first events that are similar to the second event being investigated.

[0038] Of course, the manner in which the icon is changed depending on the number of similar comparison items is not limited to the color of the icon. For example, the output unit 170 may change the shape, size, shade, pattern, etc. of the event icon 71 depending on the number of comparison items. When there are more comparison items, the amount of information to be displayed increases. Therefore, the output unit 170 changes both the color and shape of the event icon 71. In other words, the output unit 170 may change the display manner depending on the number of comparison items. The color of the event icon 71 may also be changed depending on the distance between the location where the first event occurred and the location where the second event occurred. For example, the closer the location where the first event occurred is to the location where the second event occurred, the closer the color of the event icon 71 may be to the color of the event icon 81. This makes it possible to display an event icon 71 that indicates the proximity of the event occurrence locations.

[0039] Furthermore, the output unit 170 may change the display of the event icon 71 based on the similarity, which will be described later. That is, for a first event that has a high similarity to a second event, the output unit 170 displays the event icon 71 in a manner similar to the event icon 81. In this way, the researcher can easily recognize in what respects the second event being researched and the first event are similar.

[0040] The display screen 20 may include an item input field 50. The item input field 50 includes items 53 of similar viewpoints. Here, a check box 51 is provided for each item. The researcher can select the items to be compared by checking the check boxes 51. The comparison unit 140 compares event information only for items for which the check boxes 51 are checked. In this way, the researcher can select the items to focus on. Then, the output unit 170 changes the display mode of the event icon 71 based on the number of similar items among the selected comparison items. In this way, the information processing device 100 can appropriately visualize event information. Therefore, the researcher can efficiently research related events.

[0041] Furthermore, the event icons 71 and 81 may be icons that show data for each item. For example, the event icons 71 and 81 are polygonal like a radar chart. The event icons 71 and 81 are icons in which the data for each item is plotted on a polygon. For example, if there are six comparison items, the output unit 170 displays a hexagonal radar chart. In this way, the event information can be visualized appropriately.

[0042] Furthermore, the item input field 50 may include a filtering field 54 for narrowing down the events. The researcher may be able to narrow down the events to be displayed by checking check boxes 52. For example, the events can be narrowed down by the gender of the related person. When the researcher checks the gender check box 52, the output unit 170 narrows down the events to be displayed. When the researcher checks the male check box 52, the output unit 170 displays only events in which the related person is registered as male. Alternatively, when the researcher checks the unresolved check box 52, the output unit 170 displays only icons for unresolved events.

[0043] In this way, the information processing device 100 can visualize the event information more appropriately. The narrowing down items are items that take discrete information, such as gender and resolved / unresolved. Of course, the narrowing down items are not limited to gender, etc. In this way, the information processing device 100 can visualize the event information appropriately. Therefore, the investigator can input items that are essential for the investigation, and related events can be investigated efficiently.

[0044] Furthermore, the display screen 20 may include a period input field 40 for inputting the investigation period. Here, the output unit 170 displays the period input field 40 below the map 30 on the display screen 20. The period input field 40 is a field for inputting the start date and end date of the investigation period. In FIG. 4, a bar graph showing the number of events is displayed on the time axis. Also, the first event and the second event may be displayed in a bar graph with different colors. Of course, the number of events may be visualized using a graph other than a bar graph.

[0045] The researcher can input the research period by inputting the date and time or using the scroll bar. When the researcher inputs the research period, only events that occurred during the research period are displayed on the map 30. In other words, icons are not displayed for events outside the research period. In this way, the information processing device 100 can appropriately visualize event information. Therefore, the researcher can efficiently research related events.

[0046] (Visualization example 2) Furthermore, the output unit 170 may display a similarity icon 73 indicating the value of the similarity. Specifically, the similarity calculation unit 190 calculates the similarity based on the two event information. The similarity is expressed in the range of 0 to 1. The closer the similarity is to 1, the more similar the two events are.

[0047] The similarity calculation unit 190 calculates a similarity score for each item. Then, the similarity calculation unit 190 calculates the similarity by weighting and adding the similarity scores. For example, in the event information, for items that take continuous values, such as date and time or location, the similarity calculation unit 190 calculates the similarity score based on the difference value between two pieces of data. For items that take discrete values, such as multiple colors or gender, the similarity calculation unit 190 calculates the similarity score according to the comparison result by the comparison unit 140. For example, the similarity calculation unit 190 calculates the similarity score according to whether the data for each item matches.

[0048] For example, if the data match, the score is set to 1, and if they do not match, the score is set to 0. Alternatively, if the data takes on discrete values, the similarity calculation unit 190 may calculate the score using a pre-set table. For example, in the table, scores are set in stages so that similar data has a higher score.

[0049] The similarity calculation unit 190 calculates the similarity of the first event to the second event by weighting and adding the scores of each item. The higher the similarity, the more similar the first event is to the second event. The weight for the weighting is a value set according to the importance of the item. This allows the similarity to be calculated appropriately. The output unit 170 displays a similarity icon 73 indicating the numerical value of the similarity. Note that the similarity may be displayed using a method other than a numerical value. For example, the similarity may be expressed by changing the color, shade, size, etc. of the event icon 71, etc.

[0050] Furthermore, the weights in the weighted addition may be variable. The researcher may set or change the weights in the weighted addition as appropriate. When the researcher designates an important item, the similarity calculation unit 190 can increase the weight of that item. For example, when the researcher checks the checkbox 51 in the item input field 50, the similarity calculation unit 190 increases the weight of the checked item. In this way, the researcher can select important items. Alternatively, the information processing device 100 may adjust the weight using an input field or bar for inputting the weight.

[0051] Furthermore, the researcher may select the items to be compared by the comparison unit 140. The similarity calculation unit 190 may calculate scores only for items for which the check boxes 52 in the narrowing down field 54 are checked. In other words, the similarity calculation unit 190 sets the score of unchecked items to 0. Alternatively, the comparison unit 140 may compare only checked items. This allows the researcher to select important items and items to be compared, thereby enabling more appropriate visualization.

[0052] (Visualization example 3) Furthermore, the output unit 170 may be configured to display arrow icons 72, 82 near the event icons 71, 81. Also, instead of the event icons 71, 81, whose display mode changes depending on the relationship between the first event information and the second event information, the arrow icons 72, 82 may be displayed near any icon indicating the location where the event occurred. Furthermore, the output unit 170 may be configured to display the arrow icons 72, 82 when the number of comparison items exceeds a threshold. For example, as the number of comparison items increases, the amount of information to be displayed increases. Therefore, by the output unit 170 displaying the arrow icons 72, 82, more information can be visualized.

[0053] The output unit 170 displays an arrow icon 82 in association with the event icon 81. The output unit 170 generates and displays the arrow icon 82 based on the first event information. The output unit 170 generates and displays the arrow icon 82 based on the second event information.

[0054] The arrow icons 72 and 82 are icons that visualize information related to the corresponding event icons 71 and 81. The arrow icon 82 shows information related to the second event as a two-dimensional vector on the display screen 20. The arrow icon 72 shows information related to the first event as a two-dimensional vector on the display screen 20. The output unit 170 can visualize the event information according to the direction (orientation) and size of the arrow icons 72 and 82.

[0055] For example, the output unit 170 changes the size of the arrow icons 72, 82 based on time information related to the date and time of the event occurrence. The length of the arrow icon 82 of the second event under investigation is set as the reference length. The closer the arrow icon 82 is to the occurrence date and time of the second event, the closer the length of the arrow icon 72 is to the length of the arrow icon 82. For example, if the arrow icon 82 is set to the longest length, it can be seen that the longer the arrow icon 72 is, the closer the first event is to the occurrence date and time of the event under investigation. In this way, temporal proximity can be visualized.

[0056] Alternatively, the output unit 170 may change the position of the arrow icon 72 based on information related to the time of the first event. Specifically, the orientation of the arrow icons 72, 82 indicates the start time of the event. That is, the information processing device 100 can visualize the start time of the event, which is indicated by 0 to 24 hours, in an orientation of 0 to 360 degrees. The start point of the arrow icon 82 is the event icon 81, and the end point is located in the upper left. That is, the arrow icon 82 extends diagonally upward to the left. The orientation of the arrow icon 82 is in the upper left.

[0057] The starting point of the arrow icon 72 is the event icon 71, and the position of the end point of the arrow icon 72 changes according to the time. The first event, whose direction of the arrow icon 72 is to the upper left, has a start time close to the start time of the second event. Also, the first event, whose direction of the arrow icon 72 is to the lower right, has a start time that is far away from the start time of the second event. In this way, temporal proximity can be visualized. The start times of the events can be visualized appropriately.

[0058] For example, because the arrow icons 72, 82 of events that occurred during the same time period point in the same direction, researchers can easily identify events that start close together. In the above explanation, the direction of the arrow icons 72, 82 indicates the start time of the event, but they may also indicate the date, time, end time, duration, etc. In this way, researchers can easily identify events that occur close together in date and time, etc.

[0059] The length (size) of the arrow icons 72, 82 may indicate the similarity between the events. For example, the similarity calculation unit 190 calculates the similarity based on the comparison results of each item of the event information. The size of the arrow icon 72 indicates the similarity between the first event and the second event.

[0060] The length of the arrow icon 82 of the second event is set as the reference length. For example, the arrow icon 82 is set as the longest length. When the data of the first event and the data of the second event match in all items, the length of the arrow icon 72 of the first event becomes the reference length. The longer the length of the arrow icon 72, the higher the similarity. The lower the similarity, the shorter the length of the arrow icon 72.

[0061] The information processing device 100 can appropriately visualize the first event information by displaying the arrow icons 72 of different lengths. By comparing the lengths of the arrow icons 72 and 82, the researcher can quickly determine whether the first event is similar to the second event.

[0062] (Visualization example 4) The information processing device 100 may calculate a feature vector for each event and display an icon in a manner corresponding to the feature vector. The similarity calculation unit 190 calculates a feature vector using data for each item of the event as a feature. The elements of the feature vector are the data for each item. The similarity calculation unit 190 performs multivariate analysis on the feature vectors of multiple events. The similarity calculation unit 190 reduces the number of dimensions of the feature vector and represents it as a two-dimensional vector. The output unit 170 displays arrow icons 72, 82 indicating the two-dimensional vector.

[0063] Specifically, the similarity calculation unit 190 performs principal component analysis on the feature vectors of multiple events to determine first and second principal component scores. The similarity calculation unit 190 determines a two-dimensional vector having the first and second principal component scores as elements. The output unit 170 displays arrow icons 72 and 82 indicating the two-dimensional vector. In this way, by comparing the arrow icon 82 of the second event with the arrow icon 72 of the first event, it is possible to easily identify similar events.

[0064] Alternatively, the researcher may specify the items from which features are to be extracted. For example, the items from which features are to be extracted can be specified by checking the checkboxes 51 in the item input field 50. The similarity calculation unit 190 may calculate a feature vector that uses the data of only the specified items as features. In this case, the researcher can set the number of dimensions of the feature vector.

[0065] Furthermore, the manner in which the first event information is displayed is not limited to the above example. For example, the output unit 170 may display the feature vector as a polygon like a radar chart. Furthermore, when the researcher clicks on the event icon 71, the output unit 170 may display detailed information. Furthermore, the output unit 170 does not have to display an icon indicating the first event on the map. For example, the icon may be displayed on a white background.

[0066] Furthermore, the colors of the event icons 71, 81 and the arrow icons 72, 82 may be determined according to the feature vector. For example, when the researcher selects three items, the output unit 170 assigns red (R), green (G), and blue (B) to each item. Alternatively, the first to third principal component scores obtained by principal component analysis are assigned to RGB. Then, RGB brightness values ​​are set for the data of each item. In this way, the information processing device 100 can display icons in colors according to the feature vector.

[0067] The information processing device 100 may use each of the above visualization examples 1 to 4 alone, or may combine two or more of them. Alternatively, the information processing device 100 may display only a part of any one of the visualization examples. The researcher may register multiple target second events. In this case, the similarity may be calculated based on items common to the multiple second events.

[0068] 5 is a flowchart showing an example of a visualization method. First, the first event information acquisition unit 110 acquires first event information of a first event that took place in the past (S11). The second event information acquisition unit 120 acquires second event information of a second event that is the subject of investigation (S12). Note that the order in which the first event information and second event information are acquired is not particularly limited.

[0069] Next, the comparison unit 140 compares the first event information with the second event information for a plurality of comparison items (S13). The output unit 170 performs display output so that the first icon and the second icon are displayed in association with each other in a manner according to the number of comparison items. In this way, the event information can be appropriately visualized.

[0070] 6 shows an example of the hardware configuration of an information processing device 100 according to some embodiments. In the example shown in the figure, the information processing device 100 includes a memory 191, a processor 192, and a user interface 193.

[0071] The user interface 193 is equipped with an input device that accepts input from the user. The user interface 193 includes an input unit 180 such as a keyboard, a mouse, and a touch panel. The user interface 193 includes an output device that provides output to the user. The user interface 193 is equipped with a display device, a speaker, etc. The user interface 193 is equipped with an output unit 170 that provides display output.

[0072] The processor 192 may be, for example, a microprocessor, a microprocessing unit (MPU), or a central processing unit (CPU). The processor 192 may include multiple processors.

[0073] The memory 191 is configured by a combination of volatile memory and nonvolatile memory. The memory 191 may include multiple physically independent memory devices. The volatile memory is, for example, Static Random Access Memory (SRAM), Dynamic RAM (DRAM), or a combination thereof. The nonvolatile memory is, for example, Mask Read Only Memory (MROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, a hard disk drive, or a solid-state drive (SSD), or any combination thereof. The memory 191 may include storage located remotely from the processor 192. In this case, the processor 192 may access the memory 191 via an I / O (Input / Output) interface (not shown).

[0074] The memory 191 may store software modules (computer programs) including instructions and data for performing processing by the information processing device 100 described in the above-mentioned embodiments. In some implementations, the processor 192 may be configured to read and execute the software modules from the memory 191, thereby performing processing by the information processing device 100 described in the above-mentioned embodiments.

[0075] The information processing device 100 described above can also be used in criminal investigations such as special fraud. For example, the subjects of investigation are criminals, suspects, suspects, etc., and the investigators are officials of public investigative agencies or law enforcement agencies. Specifically, the investigators are officials of the police, prosecutors, immigration bureaus, national tax bureaus, drug enforcement agencies, etc. Each event corresponds to a criminal case.

[0076] An investigator uses the information processing device 100 to collect information about crimes. The investigator registers information about crimes obtained from arrested suspects, etc. as event information. Alternatively, the investigator registers information about crimes obtained from witnesses as event information. In this way, the investigator can collect information that is useful for criminal investigations, etc. For example, an investigator can investigate a specific case and identify other crimes committed by the suspect. An investigator can identify crimes committed by the same suspect or accomplices from unresolved events. This can improve convenience.

[0077] The above-mentioned program includes instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more functions described in this disclosure. The program may be stored on a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, computer-readable medium or tangible storage medium includes RAM, ROM, flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray disc or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable medium or communication medium includes electrical, optical, acoustic, or other forms of propagated signals.

[0078] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0079] Furthermore, each drawing is merely an example for describing one or more embodiments. Each drawing may relate not only to one particular embodiment, but also to one or more other embodiments. As will be understood by those skilled in the art, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings to create, for example, an embodiment not explicitly shown or described. Not all features or steps shown in any one drawing are necessarily required to describe an exemplary embodiment, and some features or steps may be omitted. The order of steps described in any drawing may be changed as appropriate.

[0080] The present invention is not limited to the above-described embodiment, and can be modified as appropriate within the scope of the invention.

[0081] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes. (Appendix 1) a first event information acquisition unit that acquires first event information of a first event that has been held in the past; a second event information acquisition unit that acquires first event information of a second event to be investigated; a comparison unit that compares the first event information with the second event information for a plurality of comparison items; an output unit that performs display output so as to display the first icon in a manner according to the number of the comparison items. (Appendix 2) the first event information includes location information indicating a location where the first event occurred, 2. The visualization device according to claim 1, wherein the output unit performs display output so as to display the first icon on a map at the location where the first event occurred. (Appendix 3) 3. The visualization device according to claim 1, wherein when the number of the comparison items exceeds a threshold, a display output is performed so as to display a second icon in association with the first icon. (Appendix 4) 4. The visualization device according to claim 3, wherein the visualization device performs display output so as to change the display position of the second icon relative to the first icon based on the time of the first event and the time of the second event. (Appendix 5) the second icon is an arrow icon, 5. The visualization device according to claim 4, wherein the direction of the arrow icon changes based on the time of the second event. (Appendix 6) a similarity calculation unit that calculates a similarity between the first event information and the second event information, 4. The visualization device according to claim 3, wherein a display mode of the second icon is changed in accordance with the degree of similarity. (Appendix 7) 7. The visualization device according to claim 6, wherein the size of the second icon is changed in accordance with the degree of similarity. (Appendix 8) calculating a feature vector having the first event information as a feature; 4. The visualization device according to claim 3, wherein the second icon is displayed in a manner according to the feature vector. (Appendix 9) Obtain the first event information of the first event that was held in the past, Obtain second event information for the second event to be investigated, comparing the first event information with the second event information for a plurality of comparison items; A visualization method for displaying and outputting a first icon in a manner according to the number of comparison items. (Appendix 10) For computers, A process of acquiring first event information of a first event that has been held in the past; A process for acquiring second event information of the second event to be investigated; A process of comparing the first event information with the second event information for a plurality of comparison items; and executing a process of performing a display output so as to display the first icon in a manner according to the number of the comparison items. Computer program.

[0082] Some or all of the elements (e.g., configurations and functions) described in Supplementary Notes 2 to 8 that are dependent on Supplementary Note 1 may also be dependent on Supplementary Notes 9 and 10 in the same dependency relationship as Supplementary Notes 2 to 8. Some or all of the elements described in any Supplementary Note may be applied to various hardware, software, recording means for recording software, systems, and methods. [Explanation of symbols]

[0083] 20 display screen 30 Map 40 Period input field 50 fields to enter 100 Information processing device 101 First event information acquisition unit 102 Second event information acquisition unit 104 Comparison Section 107 Output section 110 First event information acquisition unit 120 Second Event Information Acquisition Unit 130 Storage section 140 Comparison Section 150 Judgment section 160 Map information generation unit 170 Output section 180 Input section 190 Similarity calculation part 191 memory 192 processors 193 User Interface

Claims

1. a first event information acquisition unit that acquires first event information of a first event that has been held in the past; a second event information acquisition unit that acquires second event information of a second event to be investigated; a comparison unit that compares the first event information with the second event information for a plurality of comparison items; an output unit that performs display output so as to display the first icon in a manner according to the number of comparison items.

2. the first event information includes location information indicating a location where the first event occurred, The visualization device according to claim 1 , wherein the output unit performs display output so as to display the first icon on a map at the location where the first event occurred.

3. The visualization device according to claim 1 , wherein when the number of the comparison items exceeds a threshold, a display output is performed so as to display a second icon in association with the first icon.

4. The visualization device according to claim 3 , wherein the display output is performed such that the display position of the second icon corresponding to the first icon is changed based on the time of the first event and the time of the second event.

5. the second icon is an arrow icon, The visualization device according to claim 4 , wherein the direction of the arrow icon changes based on the time of the second event.

6. a similarity calculation unit that calculates a similarity between the first event information and the second event information, The visualization device according to claim 3 , wherein a display mode of the second icon is changed depending on the degree of similarity.

7. The visualization device according to claim 6 , wherein the size of the second icon is changed in accordance with the degree of similarity.

8. calculating a feature vector having the first event information as a feature; The visualization device according to claim 3 , wherein the second icon is displayed in a manner corresponding to the feature vector.

9. Acquire first event information of a first event that has been held in the past; Acquire second event information of the second event to be investigated; comparing the first event information with the second event information for a plurality of comparison items; A visualization method for displaying and outputting the first icon in a manner according to the number of comparison items.

10. For computers, A process of acquiring first event information of a first event that was held in the past; A process of acquiring second event information of a second event to be investigated; a process of comparing the first event information with the second event information for a plurality of comparison items; and executing a process of performing a display output so as to display the first icon in a manner according to the number of the comparison items. Computer program.

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