Information management device, information management method, and information management program

Abstract

A related word acquisition unit (212) acquires, from a vocabulary list (32) in which a plurality of words representing similar targets are associated with each other, a related word, which is associated with an input word that has been input. A search unit (213) uses the input word to search management information and uses the related word acquired by the related word acquisition unit (212) to search management information (31), thereby identifying a retrieval target. For the retrieval target identified by the search unit (213), an evaluation value calculation unit (214) calculates an evaluation value from the degree of similarity between a word used during search for the retrieval target and the input word.

Description

Information management device, information management method, and information management program

[0001] The present disclosure relates to a technique for specifying a search target by taking into consideration differences in the expressions of words used in a search.

[0002] Smart cities are being built. Smart city services are provided using City OS to manage assets across multiple fields. OS stands for Operating System. When providing smart city services, there are times when it is necessary to identify the target asset.

[0003] Patent Document 1 describes a method of generating a knowledge graph by associating spatial data, equipment data, and measurement data according to ontology conversion rules, and searching the knowledge graph with input search information. In this way, Patent Document 1 identifies the spatial data, equipment data, and measurement data that correspond to the search information.

[0004] JP 2019-194883 A

[0005] When assets across multiple fields are managed, it is conceivable to use the technology of Patent Document 1 to search for a desired asset using a knowledge graph. However, vocabulary expressions differ depending on the field. Therefore, unless a user has a sufficient understanding of the assets being managed, it is difficult to search for assets using appropriate keywords. If the search is not performed using appropriate keywords, the desired asset may not be extracted. The present disclosure aims to enable a search target to be searched across different fields and to be appropriately identified.

[0006] The information management device according to the present disclosure includes a related word acquisition unit that acquires related words, which are words associated with an input word, from a vocabulary list in which a plurality of words representing similar objects are associated; a search unit that identifies a search target by searching management information using the input word and also searching the management information using the related words acquired by the related word acquisition unit; and an evaluation value calculation unit that calculates an evaluation value for the search target identified by the search unit from the similarity between the input word and the words used when searching for the search target.

[0007] In the present disclosure, a search target is identified by performing a search using an input word and also performing a search using related words associated with the input word. An evaluation value is then calculated from the similarity between the words used in the search for the search target and the input word. By performing a search using not only the input word but also related words, it is possible to properly extract the search target even when searching across different fields. Then, by referring to the evaluation value, it is possible to properly identify the desired search target.

[0008] 1 is a hardware configuration diagram of an information management device 10 according to the first embodiment. A functional configuration diagram of the information management device 10 according to the first embodiment. An explanatory diagram of management information 31 according to the first embodiment. An explanatory diagram of a vocabulary list 32 according to the first embodiment. A flowchart of processing by the information management device 10 according to the first embodiment. An explanatory diagram of word input processing according to the first embodiment. An explanatory diagram of result output processing according to the first embodiment. An explanatory diagram of another example according to the first embodiment. An explanatory diagram of another example according to the first embodiment. A functional configuration diagram of an information management device 10 according to a second embodiment. An explanatory diagram of a correction rule 33 according to the second embodiment. A flowchart of processing by the information management device 10 according to the second embodiment. An explanatory diagram of a vocabulary list 32 according to the second embodiment. An explanatory diagram of management information 31 according to the second embodiment. An explanatory diagram of a knowledge graph according to the second embodiment. A functional configuration diagram of an information management device 10 according to a third embodiment. An explanatory diagram of affiliation information 34 according to the third embodiment. An explanatory diagram of a vocabulary list 32 according to the third embodiment. A flowchart of processing by the information management device 10 according to the third embodiment. A functional configuration diagram of an information management device 10 according to a fourth embodiment. A flowchart of processing by the information management device 10 according to the fourth embodiment. 10 is an explanatory diagram of data regarding a search target according to Embodiment 4. FIG. 11 is a functional configuration diagram of an information management device 10 according to Embodiment 5. FIG. 12 is a flowchart of processing of the information management device 10 according to Embodiment 5.

[0009] First Embodiment In the first embodiment, an information management device 10 that manages assets across multiple fields as search targets will be described.

[0010] ***Description of Configuration*** The hardware configuration of an information management device 10 according to the first embodiment will be described with reference to Fig. 1. The information management device 10 is a computer. The information management device 10 includes the following hardware: a processor 11, a memory 12, a storage 13, and a communication interface 14. The processor 11 is connected to other hardware via signal lines and controls the other hardware.

[0011] The processor 11 is an IC that performs processing. IC stands for Integrated Circuit. Specific examples of the processor 11 include a CPU, a DSP, and a GPU. CPU stands for Central Processing Unit. DSP stands for Digital Signal Processor. GPU stands for Graphics Processing Unit.

[0012] The memory 12 is a storage device that temporarily stores data. Specific examples of the memory 12 include SRAM and DRAM. SRAM stands for Static Random Access Memory. DRAM stands for Dynamic Random Access Memory.

[0013] The storage 13 is a storage device that stores data. A specific example of the storage 13 is an HDD. HDD is an abbreviation for Hard Disk Drive. The storage 13 may also be a portable recording medium such as an SD (registered trademark) memory card, CompactFlash (registered trademark), NAND flash, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, or a DVD. SD is an abbreviation for Secure Digital. DVD is an abbreviation for Digital Versatile Disk.

[0014] The communication interface 14 is an interface for communicating with external devices. Specific examples of the communication interface 14 include Ethernet (registered trademark), USB, and HDMI (registered trademark) ports. USB stands for Universal Serial Bus. HDMI stands for High-Definition Multimedia Interface.

[0015] Referring to FIG. 2 , the functional configuration of the information management device 10 according to the first embodiment will be described. The information management device 10 includes functional components such as a target management unit 21, a data management unit 22, and a communication processing unit 23. The target management unit 21 performs functions such as searching for assets that are search targets. The data management unit manages information about the assets that are search targets. The communication processing unit controls communication between a system related to the assets that are search targets and an application program that inputs search instructions. The target management unit 21 includes functional components such as a word input unit 211, a related word acquisition unit 212, a search unit 213, an evaluation value calculation unit 214, and a result output unit 215. The functions of each functional component of the information management device 10 are realized by software. The storage 13 stores programs that realize the functions of each functional component of the information management device 10. The programs are loaded into the memory 12 by the processor 11 and executed by the processor 11. This realizes the functions of each functional component of the information management device 10.

[0016] The storage 13 stores management information 31 and a vocabulary list 32. The management information 31 is information relating to assets that are search targets. The vocabulary list 32 is information that associates multiple words that represent similar targets.

[0017] 1 shows only one processor 11. However, there may be a plurality of processors 11, and the plurality of processors 11 may cooperate to execute programs that realize the respective functions.

[0018] ***Description of Operation*** The operation of the information management device 10 according to the first embodiment will be described with reference to Figures 3 to 8. The operation procedure of the information management device 10 according to the first embodiment corresponds to the information management method according to the first embodiment. Furthermore, the program that realizes the operation of the information management device 10 according to the first embodiment corresponds to the information management program according to the first embodiment.

[0019] The management information 31 according to the first embodiment will be described with reference to FIG. 3 . The management information 31 includes words for each of a plurality of classifications for each asset. Here, an example will be described in which the management information 31 includes words for each of the classifications of name (Entity), function (Relationship), and attribute (Property) in the knowledge graph. Note that the classification is not limited to the name, function, and attribute of the knowledge graph. The classification may be, for example, a classification of a plurality of attribute types. Furthermore, words do not necessarily need to be set for all classifications, and words may be set for only some classifications. In FIG. 3 , for an asset named "temperature sensor," measurement is set as the function and temperature is set as the attribute. Furthermore, for an asset named "air conditioning indoor unit," acquisition is set as the function and room temperature and humidity are set as the attributes.

[0020] The vocabulary list 32 according to the first embodiment will be described with reference to FIG. 4. In the vocabulary list 32, a plurality of words representing similar objects are associated with each other, and a similarity between the words is set. Similar objects may be expressed by different words depending on the field. In the vocabulary list 32, words expressed by different expressions depending on the field are associated with each other. In FIG. 4, the word "acquire" is associated with the word "measure," and a similarity of 0.9 is set. Furthermore, the word "temperature" is associated with the word "room temperature," and a similarity of 0.8 is set. Here, the closer the similarity value is to 1, the more similar the words are. The similarity between the same words is set to 1.

[0021] The processing of the information management device 10 according to the first embodiment will be described with reference to Fig. 5. (Step S11: Word Input Processing) The word input unit 211 accepts input of words for searching for assets. The accepted words are called input words. Specifically, the word input unit 211 displays an input screen as shown in Fig. 6 and prompts the user to input words for each category. That is, here, the word input unit 211 accepts input of words for each of the categories of name, function, and attribute. Note that it is not necessary to input words for all categories, and words may be input only for some categories. In Fig. 6, the word "temperature" is input for the attribute category.

[0022] (Step S12: Related Word Acquisition Process) The related word acquisition unit 212 reads out the vocabulary list 32. Then, the related word acquisition unit 212 acquires, in the vocabulary list 32, words associated with the input word input in step S11 as related words. At this time, the related word acquisition unit 212 also acquires the similarity between the input word and the related words set in the vocabulary list 32. For example, assume that "temperature" is the input word as shown in FIG. 6. In the vocabulary list 32 shown in FIG. 4, "room temperature" is set as a word related to temperature. Therefore, when "temperature" is the input word, the related word acquisition unit 212 acquires "room temperature" as a related word. At this time, the related word acquisition unit 212 also acquires the similarity of 0.8 between the temperature set in the vocabulary list 32 and room temperature.

[0023] (Step S13: Search Process) The search unit 213 searches the management information 31 using the input word input in step S11. The search unit 213 also searches the management information 31 using the related words acquired in step S12. As a result, the search unit 213 identifies an asset that is the search target corresponding to the input word or the related word. For example, assume that "temperature" is the input word and "room temperature" is the related word. In this case, the search unit 213 searches the attribute classification of the management information 31 using temperature as a keyword. As a result, a temperature sensor is identified from the management information 31 shown in FIG. 3. The search unit 213 also searches the attribute classification of the management information 31 using room temperature as a keyword. As a result, an air conditioning indoor unit is identified from the management information 31 shown in FIG. 3. In other words, a temperature sensor and an air conditioning indoor unit are identified.

[0024] (Step S14: Evaluation Value Calculation Process) The evaluation value calculation unit 214 calculates an evaluation value for each asset identified in step S13. Specifically, the evaluation value calculation unit 214 sets each asset as a target asset. The evaluation value calculation unit 214 calculates an evaluation value from the similarity between the word used when searching for the target asset and the input word entered in step S11. As a specific example, the evaluation value calculation unit 214 uses the similarity as the evaluation value. For example, a temperature sensor was searched for using "temperature" as a keyword. Because "temperature" is an input word, the similarity with the input word is 1. Therefore, the evaluation value for the temperature sensor is 1. Furthermore, an air conditioner indoor unit was searched for using "room temperature" as a keyword. "Room temperature" is a related word, and the similarity with the input word "temperature" is 0.8, as obtained in step S12. Therefore, the evaluation value for the air conditioner indoor unit is 0.8.

[0025] (Step S15: Result Output Processing) The result output unit 215 outputs the asset identified in step S13 together with the evaluation value calculated in step S14. For example, when temperature is input as an input word as shown in Fig. 6, the result output unit 215 outputs a temperature sensor and an air conditioning indoor unit as assets as shown in Fig. 7. In this case, the result output unit 215 outputs an evaluation value of 1 for the temperature sensor and an evaluation value of 0.8 for the air conditioning indoor unit.

[0026] As shown in FIG. 8 , when "acquisition" is input as a function classification in step S11, in step S12 the related word acquisition unit 212 acquires "measurement" as a related word of "acquisition" from the vocabulary list 32 shown in FIG. 4. Then, in step S13, the search unit 213 searches for functions in the management information 31 using "acquisition" and "measurement" as keywords. By searching using "acquisition" as a keyword, the air conditioning indoor unit is identified. By searching using "measurement" as a keyword, the temperature sensor is identified. In step S14, the evaluation value calculation unit 214 calculates evaluation values ​​for each of the air conditioning indoor unit and the temperature sensor. Since the air conditioning indoor unit was searched for using the input word "acquisition" as a keyword, the evaluation value is 1. Since the temperature sensor was searched for using the related word "measurement" as a keyword, and the similarity between "measurement" and the input word "acquisition" is 0.9, the evaluation value is 0.9.

[0027] In the example of FIG. 6 , words are input only to attributes in step S11, while in the example of FIG. 8 , words are input only to functions in step S11. However, words may be input to two or more categories. In this case, in step S12, the related word acquisition unit 212 acquires related words for each input word input for two or more categories. In step S13, the search unit 213 identifies assets to be searched by searching the management information 31 using each combination obtained by setting input words or related words for each of the two or more categories. In step S14, the evaluation value calculation unit 214 calculates an evaluation value for each asset as a target asset from the similarity between the input word and each word included in the combination used when searching for the target asset. As a specific example, the evaluation value calculation unit 214 calculates the product of the similarity between the input word and each word included in the combination used when searching.

[0028] For example, as shown in Fig. 9, assume that "acquisition" is input as the function classification and "temperature" is input as the attribute classification in step S11. In this case, in step S12, the related word acquisition unit 212 acquires "measurement" as a related word for "acquisition" from the vocabulary list 32 shown in Fig. 4. Also, "room temperature" is acquired as a related word for "temperature." Here, the related word acquisition unit 212 acquires 0.9 as the similarity for "measurement" and 0.8 as the similarity for "room temperature."

[0029] In step S13, the search unit 213 searches the management information 31 using each combination in which the function classification is set to acquisition or measurement and the attribute classification is set to temperature or room temperature. That is, the search unit 213 searches the management information 31 using each of the following combinations 1 to 4. Combination 1 is a combination in which the function classification is set to acquisition and the attribute classification is set to temperature. Combination 2 is a combination in which the function classification is set to acquisition and the attribute classification is set to room temperature. Combination 3 is a combination in which the function classification is set to measurement and the attribute classification is set to temperature. Combination 4 is a combination in which the function classification is set to measurement and the attribute classification is set to room temperature. Here, searching the management information 31 using combination 1 means searching for assets in which the function is set to acquisition and the attribute is set to temperature. The same applies to combinations 2 to 4. Then, from the management information 31 shown in FIG. 3, an air conditioning indoor unit is identified by a search using combination 2, and a temperature sensor is identified by a search using combination 3.

[0030] In step S14, the evaluation value calculation unit 214 calculates an evaluation value for each of the air conditioning indoor unit and the temperature sensor. For the air conditioning indoor unit, the calculation is as follows: Acquisition, which is included in combination 2, is an input word and has a similarity of 1, and Room Temperature, which is a related word and has a similarity of 0.8. Therefore, the evaluation value calculation unit 214 calculates an evaluation value of 0.8 by multiplying 1 by 0.8. For the temperature sensor, the calculation is as follows: Measurement, which is included in combination 3, is a related word and has a similarity of 0.9, and Temperature, which is an input word and has a similarity of 1. Therefore, the evaluation value calculation unit 214 calculates an evaluation value of 0.9 by multiplying 0.9 by 1.

[0031] ***Effects of Embodiment 1*** As described above, the information management device 10 according to embodiment 1 identifies a search target by searching using related words associated with an input word. Then, an evaluation value is calculated from the similarity between the input word and the words used when searching for the search target. There may be differences in vocabulary expressions depending on the field. Even when searching across different fields with different vocabulary expressions, it is possible to properly extract a search target by searching using not only the input word but also related words. Then, by referring to the evaluation value, it is possible to properly identify the desired search target.

[0032] ***Other Configurations*** <Modification 1> In the first embodiment, each functional component is realized by software. However, in Modification 1, each functional component may be realized by hardware. The differences between Modification 1 and the first embodiment will be described below.

[0033] When each functional component is realized by hardware, the information management device 10 includes an electronic circuit instead of the processor 11, the memory 12, and the storage 13. The electronic circuit is a dedicated circuit that realizes the functions of each functional component, the memory 12, and the storage 13.

[0034] Possible electronic circuits include a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, a GA, an ASIC, and an FPGA. GA stands for Gate Array. ASIC stands for Application Specific Integrated Circuit. FPGA stands for Field-Programmable Gate Array. Each functional component may be realized by a single electronic circuit, or each functional component may be distributed across multiple electronic circuits.

[0035] <Modification 2> As a modification 2, some of the functional components may be realized by hardware, and other functional components may be realized by software.

[0036] The processor 11, the memory 12, the storage 13, and the electronic circuitry are collectively referred to as a processing circuit. In other words, the functions of the respective functional components are realized by the processing circuit.

[0037] Furthermore, the term "unit" in the above description may be read as a "circuit," "step," "procedure," "process," or "processing circuit."

[0038] Embodiment 2. Embodiment 2 differs from embodiment 1 in that an evaluation value is calculated using the structure of a knowledge graph for the asset to be searched. In embodiment 2, this difference will be explained, and explanations of the same points will be omitted.

[0039] ***Description of Configuration*** The functional configuration of the information management device 10 according to the second embodiment will be described with reference to Fig. 10. The information management device 10 differs from the information management device 10 shown in Fig. 2 in that the evaluation value calculation unit 214 includes a similarity calculation unit 216, a structural comparison unit 217, and a correction unit 218. The information management device 10 also differs from the information management device 10 shown in Fig. 2 in that correction rules 33 are stored in the storage 13. The correction rules 33 indicate rules for correcting evaluation values ​​based on the structure of a knowledge graph.

[0040] ***Explanation of Operation*** The correction rule 33 according to the second embodiment will be described with reference to FIG. 11. The correction rule 33 indicates a rule for correcting an evaluation value. Specifically, the correction rule 33 indicates a rule for correcting an evaluation value based on the degree of match between the knowledge graph structure of an asset that is a search target identified by performing a search using an input word and the knowledge graph structure of an asset that is a search target identified by performing a search using related words. Here, the correction rule 33 indicates a rule depending on how many hops away from the identified asset the structures match. The correction rule 33 is a rule for correcting an evaluation value so that the farther the structures match, the closer the evaluation value becomes to 1.

[0041] The processing of the information management device 10 according to the second embodiment will be described with reference to Fig. 12. The processing from step S21 to step S23 is the same as the processing from step S11 to step S13 in Fig. 5. Furthermore, the processing from step S28 is the same as the processing from step S15 in Fig. 5.

[0042] The processes from step S24 to step S27 correspond to the evaluation value calculation process of step S14 in Fig. 5. (Step S24: Similarity Calculation Process) As in step S14 in Fig. 5, the similarity calculation unit 216 calculates an evaluation value for each asset identified in step S23 from the similarity between the words used when searching for that asset and the input words entered in step S21.

[0043] (Step S25: Structural comparison processing) The structural comparison unit 217 compares the structure of the input graph with the structure of the association graph to determine the degree of match. The input graph is a knowledge graph about the asset that is the search target identified by performing a search using an input word. The association graph is a knowledge graph about the asset that is the search target identified by performing a search using an associated word. Here, the structural comparison unit 217 determines the degree of match by determining how many hops away from the identified asset the structures match.

[0044] A specific description will be given with reference to FIGS. 13 to 15 . As shown in FIG. 13 , the vocabulary list 32 associates the word “point data” with the word “monitoring data.” At this time, it is assumed that the word “point data” is specified as the attribute classification in step S21. Then, in step S22, monitoring data is acquired as a related word of the point data. Then, in step S23, a search is performed using each of the point data and the monitoring data as keywords. Then, when a search is performed using point data as a keyword from the management information 31 shown in FIG. 14 , an IoTGW is identified, and when a search is performed using monitoring data as a keyword, a remote monitoring device is identified. In step S24, the similarity calculation unit 216 calculates an evaluation value for each of the IoTGW and the remote monitoring device based on the similarity between the input word, point data, and the word used in the search. Here, since the IoTGW was searched using the input word, point data, as a keyword, the evaluation value is 1. Since the remote monitoring device has a similarity of 0.7 between the monitoring data and the input word, point data, the evaluation value is 0.7.

[0045] In step S25, the structure comparison unit 217 compares the structure of the input graph with the structure of the association graph to determine the degree of match. First, the structure comparison unit 217 sets the assets searched for using the related words as keywords as target assets. In this example, only the remote monitoring device is set as the target asset. The structure comparison unit 217 compares the structure of the input graph, which is a knowledge graph for the IoTGW, with the structure of the association graph, which is a knowledge graph for the remote monitoring device set for the target asset. The assets related to the IoTGW and the assets related to the remote monitoring device in the management information 31 shown in FIG. 14 are represented as graph structures as shown in FIG. 15. The structure comparison unit 217 determines the degree of match, indicating how many hops away from the identified asset (here, the IoTGW and the remote monitoring device) the structure of the input graph and the structure of the association graph match. Whether the structures match is determined based on whether the graph shapes are the same and whether the vocabulary of the functions (relationships) is the same. If both are the same, the structures are determined to be a complete match. If only one is the same, the structures are determined to be a partial match. Here, the structure comparison unit 217 determines that the structures are a perfect match up to two hops away. That is, the degree of match is determined as a perfect match up to two hops away.

[0046] (Step S26: Matching Degree Determination Process) The structure comparison unit 217 determines whether or not the structure of the input graph and the structure of the associated graph match at least partially in step S25. If there is at least a partial match, the structure comparison unit 217 determines that correction of the evaluation value is necessary, and proceeds to step S27. On the other hand, if there is no match at all, the structure comparison unit 217 determines that correction of the evaluation value is unnecessary, and proceeds to step S28.

[0047] (Step S27: Correction Process) The correction unit 218 corrects the evaluation value calculated in step S24 according to the rule corresponding to the degree of match identified in step S25. In the examples of FIGS. 13 to 15, the degree of match is a perfect match in the configurations up to two hops away. Therefore, the correction unit 218 reads out a rule for the case where the configurations are a perfect match up to two hops away from the correction rule 33. As shown in FIG. 11, the rule for the case where the configurations are a perfect match up to two hops away is: Corrected evaluation value = (evaluation value + 2) / 3. Therefore, the correction unit 218 substitutes the evaluation value calculated in step S24 into this formula. The evaluation value calculated in step S24 is 0.7. Therefore, the corrected evaluation value becomes (0.7 + 2) / 3 = 0.9.

[0048] Therefore, in step S28, the result output unit 215 outputs the IoTGW with an evaluation value of 1, and the remote monitoring device with an evaluation value of 0.9.

[0049] ***Effects of Embodiment 2*** As described above, the information management device 10 according to Embodiment 2 calculates an evaluation value using the structure of a knowledge graph for the asset that is the search target. Specifically, the information management device 10 calculates the evaluation value based on the degree of agreement between the structure of the input graph and the structure of the association graph. This makes it possible to calculate the evaluation value more appropriately.

[0050] Embodiment 3. Embodiment 3 differs from Embodiments 1 and 2 in that related words are limited depending on the field to which the input word belongs. In Embodiment 3, this difference will be explained, and explanation of the same points will be omitted. In Embodiment 3, a case where a function is added to Embodiment 1 will be explained. However, it is also possible to add a function to Embodiment 2.

[0051] ***Description of Configuration*** The functional configuration of the information management device 10 according to the third embodiment will be described with reference to Fig. 16. The information management device 10 differs from the information management device 10 shown in Fig. 2 in that affiliation information 34 is stored in the storage 13. The affiliation information 34 indicates the field to which the input word belongs.

[0052] ***Explanation of Operation*** The affiliation information 34 according to the third embodiment will be described with reference to Fig. 17. The affiliation information 34 indicates the application program that is the source of the input word or the field to which the user belongs. In Fig. 17, it is assumed that the input source is an application program, and the affiliation information 34 sets the fields to which the elevator program and the timetable search program belong.

[0053] The vocabulary list 32 according to the third embodiment will be described with reference to FIG. 18 . In the vocabulary list 32, a plurality of words representing similar objects are associated with each other, and the similarity between the words is set. In the vocabulary list 32, a field of use is further set for each word. For example, in FIG. 18 , a destination and a destination station are associated with each other, and the similarity is set to 0.7. Furthermore, the field of use for the destination is set to building, and the field of use for the destination station is set to transportation.

[0054] The processing of the information management device 10 according to the third embodiment will be described with reference to Fig. 19. The processing of steps S31 and S32 is the same as the processing of steps S11 and S12 in Fig. 5. The processing of steps S35 to S37 is the same as the processing of steps S13 to S15 in Fig. 5.

[0055] The processes of steps S33 and S34 are executed for each of the one or more related words acquired in step S32.

[0056] (Step S33: Affiliation Determination Process) The related word acquisition unit 212 determines whether the field of use of the target related word is the same as the field of affiliation of the input source of the input word. Here, it is assumed that the application program or user that input the word has been identified. For example, authentication processing or the like is performed when accessing the information management device 10, and the input source application program or user is identified. If the field of use is the same as the affiliation field, the related word acquisition unit 212 proceeds to step S34. On the other hand, if the field of use is different from the affiliation field, the related word acquisition unit 212 skips step S34 and ends processing for the target related word.

[0057] (Step S34: Word Exclusion Processing) The related word acquisition unit 212 excludes the target related word from the related words acquired in step S32. In other words, the related word acquisition unit 212 prevents the target related word from being used as a keyword during the search in step S35. For example, suppose that an arrival station is input by an elevator program. Then, in step S32, "floor arrival" is acquired as a related word. However, since the field to which the elevator program belongs and the field of use of "floor arrival" are the same building, the process proceeds to step S34 in step S33, and "floor arrival" is excluded from the related words.

[0058] In this way, by the processes of steps S32 to S34, the related word acquisition unit 212 acquires, as related words, only words whose registered field of use is different from the field to which the input word belongs. In other words, the related word acquisition unit 212 stops acquiring, as related words, words whose registered field of use is the same as the field to which the input word belongs.

[0059] ***Effects of Embodiment 3*** As described above, the information management device 10 according to Embodiment 3 stops acquiring, as related words, words registered in the same field of use as the field to which the input word belongs that is the source of the input word. This makes it possible to reduce the number of related words. As a result, it is possible to reduce the processing load related to searching and calculating evaluation values. It is also possible to prevent unintended search targets from being extracted.

[0060] Here, it is assumed that the vocabulary of the field of affiliation is properly understood. Therefore, it is considered that there is little need to acquire words in the field of affiliation as related words. For example, if the field of affiliation is buildings, it is considered that the user would not call "arrival" "arrival station." Therefore, when "arrival station" is input, it is considered that there is little need to acquire "arrival" as a related word and perform a search using "arrival" as a keyword. In other words, it is considered that a search using "arrival" as a keyword will not be the search intended by the input source.

[0061] Embodiment 4. Embodiment 4 differs from embodiments 1 to 3 in that an evaluation value is calculated using data on the search target. In embodiment 4, this difference will be explained, and explanation of the same points will be omitted. In embodiment 4, a case where a function is added to embodiment 1 will be explained. However, it is also possible to add a function to embodiments 2 and 3.

[0062] ***Description of Configuration*** The functional configuration of the information management device 10 according to embodiment 4 will be described with reference to Fig. 20. The information management device 10 differs from the information management device 10 shown in Fig. 2 in that the evaluation value calculation unit 214 includes a similarity calculation unit 216, a correction unit 218, and a data comparison unit 219.

[0063] ***Description of Operation*** The processing of the information management device 10 according to embodiment 4 will be described with reference to Fig. 21. The processing from step S41 to step S43 is the same as the processing from step S11 to step S13 in Fig. 5. Furthermore, the processing of step S48 is the same as the processing of step S15 in Fig. 5.

[0064] The processes from step S44 to step S47 correspond to the evaluation value calculation process of step S14 in Fig. 5. (Step S44: Similarity Calculation Process) As in step S14 in Fig. 5, the similarity calculation unit 216 calculates an evaluation value for each asset identified in step S23 from the similarity between the words used when searching for that asset and the input words entered in step S41.

[0065] (Step S45: Data Acquisition Processing) The data comparison unit 219 acquires data about the asset that is the search target identified in step S43. Information about the asset is managed by the data management unit 22. Specifically, the data comparison unit 219 performs a search using an input word and acquires data related to the input word for the identified search target. Furthermore, the data comparison unit 219 performs a search using related words and acquires data related to the related words for the identified search target. For example, as shown in FIG. 22 , assume that the input word is temperature and the related word is room temperature. Assume that a boiler is identified using temperature as a keyword and an air conditioning indoor unit is identified using room temperature as a keyword. In this case, the data comparison unit 219 acquires time-series values ​​of the boiler temperature as data related to the boiler temperature. Furthermore, the data comparison unit 219 acquires time-series values ​​of the air conditioning indoor unit room temperature as data related to the room temperature for the air conditioning indoor unit.

[0066] (Step S46: Data Comparison Processing) The data comparison unit 219 compares data related to the input word for the search target identified by performing a search using the input word with data related to the related word for the search target identified by performing a search using the related word. The data comparison unit 219 then determines whether there is similarity between the data. In the example of FIG. 22 , the boiler temperature range is 25 to 65°C. In contrast, the room temperature range for the air conditioning indoor unit is 25 to 26°C. Therefore, it is determined that there is no similarity between the data. If there is no similarity, the data comparison unit 219 determines that correction of the evaluation value is necessary, and proceeds to step S47. On the other hand, if there is similarity, the data comparison unit 219 determines that correction of the evaluation value is unnecessary, and proceeds to step S48.

[0067] (Step S47: Correction Process) The correction unit 218 corrects the evaluation value calculated in step S44 to a lower value. The correction unit 218 may correct the evaluation value so that the lower the similarity, the lower the evaluation value. As in the second embodiment, correction rules 33 indicating rules for each similarity may be stored in the storage 13 and referenced for correction.

[0068] ***Effects of Embodiment 4*** As described above, the information management device 10 according to Embodiment 4 calculates an evaluation value using data about the search target. Even if a search target has related words set, if the search target handles a different type of data, it is highly likely that the search target is not the desired search target. The information management device 10 according to Embodiment 4 can easily identify the desired search target by lowering the evaluation value for such search targets.

[0069] Embodiment 5. Embodiment 5 differs from embodiments 1 to 4 in that related words are displayed together with the degree of similarity before a search. In embodiment 5, this difference will be explained, and explanations of the same points will be omitted. In embodiment 5, a case where a function is added to embodiment 1 will be explained. However, it is also possible to add a function to embodiments 2 to 4.

[0070] ***Description of Configuration*** The functional configuration of the information management device 10 according to embodiment 5 will be described with reference to Fig. 23. The information management device 10 differs from the information management device 10 shown in Fig. 2 in that it includes a candidate display unit 220 as a functional component.

[0071] ***Description of Operation*** The processing of the information management device 10 according to embodiment 5 will be described with reference to Fig. 24. The processing of step S51 is the same as the processing of step S11 in Fig. 5. The processing of steps S55 to S58 is the same as the processing of steps S12 to S15 in Fig. 5.

[0072] 5, the related word acquisition unit 212 acquires, as related words, words associated with the input word input in step S11 in the vocabulary list 32. At this time, the related word acquisition unit 212 also acquires the similarity between the input word and the related words set in the vocabulary list 32.

[0073] (Step S53: Candidate display process) The candidate display unit 220 displays the input word input in step S51 and the related words acquired in step S52. At this time, the candidate display unit 220 also displays the similarity between the input word and the related words.

[0074] (Step S54: Word Selection Process) The word input unit 211 accepts the selection of a word to be used in the search from the input word and related words displayed in step S53. The selected word is used as the input word, and the processes from step S55 onwards are executed.

[0075] ***Effects of Embodiment 5*** As described above, the information management device 10 according to Embodiment 5 displays related words together with their similarities, allowing the user to select words to use in a search. When the vocabulary used in the target search target or how the vocabulary is used is not fully understood, referring to candidate words makes it easier to specify appropriate words.

[0076] The embodiments and modifications of the present disclosure have been described above. Some of these embodiments and modifications may be combined and implemented. Furthermore, one or more of them may be implemented partially. Note that the present disclosure is not limited to the above embodiments and modifications, and various modifications are possible as needed.

[0077] 10 Information management device, 11 Processor, 12 Memory, 13 Storage, 14 Communication interface, 21 Object management unit, 22 Data management unit, 23 Communication processing unit, 211 Word input unit, 212 Related word acquisition unit, 213 Search unit, 214 Evaluation value calculation unit, 215 Result output unit, 216 Similarity calculation unit, 217 Structural comparison unit, 218 Correction unit, 219 Data comparison unit, 220 Candidate display unit, 31 Management information, 32 Vocabulary list, 33 Correction rules, 34 Affiliation information.

Claims

1. An information management device comprising: a related word acquisition unit that acquires related words, which are words associated with an input word, from a vocabulary list in which multiple words representing similar objects are associated; a search unit that identifies a search target by searching management information using the input word and also searching the management information using the related words acquired by the related word acquisition unit; and an evaluation value calculation unit that calculates an evaluation value for the search target identified by the search unit based on the similarity between the input word and the words used when searching for the search target.

2. The information management device of claim 1, wherein the management information includes words for each of a plurality of classifications for each search target, the related word acquisition unit acquires the related words for each of the input words entered for two or more of the plurality of classifications, the search unit identifies the search target by searching the management information using each combination obtained by setting the input word or the related words for each of the two or more classifications, and the evaluation value calculation unit calculates an evaluation value from the similarity between each word included in the combination used when searching for the search target and the input word.

3. An information management device as described in claim 1 or 2, wherein the management information includes a knowledge graph for each search target, and the evaluation value calculation unit calculates the evaluation value from the degree of agreement between the structure of the knowledge graph for the search target identified by performing a search using the input word and the structure of the knowledge graph for the search target identified by performing a search using the related word.

4. An information management device as claimed in any one of claims 1 to 3, wherein the vocabulary list has a field of use registered for each word, and the related word acquisition unit stops acquiring as the related word any word for which the same field of use as the field to which the input word belongs is registered.

5. An information management device as claimed in any one of claims 1 to 4, wherein the evaluation value calculation unit calculates the evaluation value from the similarity between data relating to the input word for a search target identified by performing a search using the input word and data relating to the related words for a search target identified by performing a search using the related words.

6. The information management device according to any one of claims 1 to 5, further comprising: a candidate display unit that displays the related words together with the similarity between the related words and the input word.

7. An information management device as claimed in any one of claims 1 to 6, wherein the search target is an asset in one of a plurality of fields, and the vocabulary list is a plurality of words used in different fields among the plurality of fields, and a plurality of words representing similar objects are associated with each other.

8. An information management method in which a computer retrieves related words, which are words associated with an input word, from a vocabulary list in which multiple words representing similar objects are associated; the computer searches management information using the input word and also searches management information using the related words, thereby identifying a search target; and the computer calculates an evaluation value for the identified search target based on the similarity between the input word and the words used when searching for the search target.

9. An information management program that causes a computer to function as an information management device that performs the following steps: a related word acquisition process that acquires related words, which are words associated with an input word, from a vocabulary list in which multiple words representing similar objects are associated; a search process that identifies a search target by searching management information using the input word and also using the related words acquired by the related word acquisition process; and an evaluation value calculation process that calculates an evaluation value for the search target identified by the search process based on the similarity between the input word and the words used when searching for the search target.

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