Search system, search method, and program

Abstract

The present disclosure addresses the problem of providing a search system, a search method, and a program with which it is possible to shorten the time required for narrowing down search results from a plurality of objects. In a search system (10), a first acquisition unit (12) acquires data pertaining to a first search condition (X1) set for a plurality of classification items for classifying a plurality of objects. A second acquisition unit (13) acquires, from a storage unit (11), data pertaining to a second search condition (X2) set for some of the plurality of classification items. A selection unit (14) selects, as specific objects and from among the plurality of objects, objects that satisfy a third search condition (X3) composed of the second search condition (X2) and at least a portion of the first search condition (X1). A data creation unit (15) creates list data indicating a list of the specific objects. A data output unit (16) outputs the list data.

Description

Search system, search method, and program

[0001] The present disclosure relates to a search system, a search method, and a program.

[0002] The product information search device in Patent Document 1 searches for information (product information) about nursing care equipment as a product, and includes a processing device and an input / output device. The processing device is a computer main body, and the input / output devices are a display device, a mouse, a speaker, and a printer. Nursing care equipment is broadly classified by product category, and each product category is further classified by product item, with specific products belonging to each product item.

[0003] In a product search, a list of product category names is displayed on the display device. When the operator uses the mouse to select one of these product category names, a list of product items belonging to the selected product category is displayed on the display device. When the operator uses the mouse to select and input one or more of the displayed product items and press the search button, the search begins.

[0004] When the Intake button is pressed without pressing the Search button during the selection input of product items, a User Status Selection screen is displayed on the display device. This allows for more detailed search conditions to be provided from the perspective of the user's status, in addition to the search conditions specified by the product category and product items described above. On the User Status Selection screen, the operator operates the mouse to input the user of the nursing equipment, the user's daily living situation, and their physical condition. After this, when the operator presses the OK button, the screen returns to the original product search screen, and when the operator operates the mouse to press the Search button, the screen moves to search.

[0005] In a product information search device (search system) such as that disclosed in Patent Document 1, search results may include objects with low adoption probability, which results in a long time being required to narrow down search results from multiple products.

[0006] Japanese Patent Application Publication No. 7-110832

[0007] An object of the present disclosure is to provide a search system, a search method, and a program that can reduce the time required to narrow down search results from multiple objects.

[0008] A search system according to one aspect of the present disclosure searches for multiple objects. The search system includes a first acquisition unit, a second acquisition unit, a selection unit, a data creation unit, and a data output unit. The first acquisition unit acquires data on first search conditions set for multiple classification items for classifying the multiple objects. The second acquisition unit acquires data on second search conditions from a storage unit that pre-stores second search conditions set for some of the multiple classification items. The selection unit selects, as specific objects, objects that satisfy third search conditions consisting of at least some of the first search conditions and the second search conditions from the multiple objects. The data creation unit creates list data that lists the specific objects. The data output unit outputs the list data.

[0009] A search method according to one aspect of the present disclosure searches for multiple objects. The search method includes a first acquisition step, a second acquisition step, a selection step, a data creation step, and a data output step. The first acquisition step acquires data of first search conditions set for multiple classification items for classifying the multiple objects. The second acquisition step acquires data of second search conditions set for some of the multiple classification items from a storage unit that pre-stores second search conditions set for some of the multiple classification items. The selection step selects, as specific objects, objects that satisfy third search conditions consisting of at least some of the first search conditions and the second search conditions from the multiple objects. The data creation step creates list data that lists the specific objects. The data output step outputs the list data.

[0010] A program according to one aspect of the present disclosure causes a computer system to execute the above-described search method.

[0011] FIG. 1 is a block diagram showing a search system according to an embodiment. FIG. 2 is a diagram showing appliance information in the search system according to the same. FIG. 3 is a diagram showing first search conditions in the search system according to the same. FIG. 4 is a diagram showing second search conditions in the search system according to the same. FIG. 5 is a diagram showing a setting screen in the search system according to the same. FIG. 6 is a diagram showing third search conditions in the search system according to the same. FIG. 7 is a diagram showing a list screen in the search system according to the same. FIG. 8 is a flowchart showing a search method according to an embodiment. FIG. 9 is a block diagram showing a search system according to a first modified example.

[0012] The following embodiments generally relate to a search system, a search method, and a program. More specifically, the following embodiments relate to a search system, a search method, and a program for searching multiple objects. Note that the embodiments described below are merely examples of embodiments of the present disclosure. The present disclosure is not limited to the following embodiments, and various modifications are possible depending on the design, etc., as long as the effects of the present disclosure can be achieved.

[0013] (1) Overview of the Search System The search system searches for multiple objects and extracts specific objects that satisfy search conditions from the multiple objects. Examples of the objects include electrical equipment, mechanical devices, books, television programs, movies, video content, and music content. However, the objects are not limited to these, and are not limited to specific objects.

[0014] The search system 10 shown in FIG. 1 searches for multiple objects. The search system 10 includes a first acquisition unit 12, a second acquisition unit 13, a selection unit 14, a data creation unit 15, and a data output unit 16. The first acquisition unit 12 acquires data on first search criteria X1 set for multiple classification items for classifying the multiple objects. The second acquisition unit 13 acquires data on second search criteria X2 from a storage unit 11 that pre-stores second search criteria X2 set for some of the multiple classification items. The selection unit 14 selects, as specific objects, objects that satisfy third search criteria X3 consisting of at least some of the first search criteria X1 and the second search criteria X2 from the multiple objects. The data creation unit 15 creates list data that lists the specific objects. The data output unit 16 outputs the list data.

[0015] The search system 10 having the above-described configuration extracts specific objects that satisfy third search criteria X3 from multiple objects. The third search criteria X3 are automatically created from at least a portion of the first search criteria X1 and second search criteria X2 pre-stored in the memory unit 11. The second search criteria X2 are search criteria that are pre-set for some of the multiple classification items, and the search system 10 narrows down the inspection results using the second search criteria X2 in addition to at least a portion of the first search criteria X1. As a result, the search system 10 can prevent objects with low adoption potential from being included in the search results. Therefore, the search system 10 can shorten the time required to narrow down search results from multiple objects.

[0016] Preferably, the search system 10 further includes a storage unit 11, a condition modification unit 17, and a condition update unit 18. Preferably, the search system 10 further includes an input device 2 and an output device 3. Preferably, the search system 10 further includes a database 4.

[0017] (2) Details Fig. 1 shows a block diagram of a search system 10. The search system 10 includes a search device 1, an input device 2, an output device 3, and a database 4, and executes a search method for extracting a specific object, which is an object that satisfies a search condition, from a plurality of objects.

[0018] The search system 10 of this embodiment is used when proposing a renewal to replace an existing lighting fixture Ea (see FIG. 3 ), which is an existing lighting fixture, with one of multiple (a large number) current lighting fixtures E1, E2, ... (see FIG. 2 ), which are currently on the market. The search system 10 searches the multiple current lighting fixtures E1, E2, ... (see FIG. 2 ) and extracts one or more current lighting fixtures that can replace the existing lighting fixture Ea as proposed lighting fixtures Eb (see FIG. 7 ). That is, the multiple targets in this embodiment are the multiple current lighting fixtures E1, E2, ..., and the proposed lighting fixture Eb that can replace the existing lighting fixture Ea is extracted as a specific target from the multiple current lighting fixtures E1, E2, ....

[0019] (2.1) Classification In this embodiment, the existing fixtures E1, E2, ..., and the existing fixture Ea are lighting fixtures. The lighting fixtures can be classified using classification items. That is, the classification items are used to classify the lighting fixtures. In particular, in the search system 10, the classification items are used to classify multiple existing fixtures E1, E2, ....

[0020] In this embodiment, there are a plurality of classification items, and each of the plurality of classification items is classified into either a basic item or an attribute item.

[0021] (Basic Items) The basic items are classification items mainly related to the outline of the lighting fixture. The basic items include classification items such as the "shape," "category," "lamp brightness," and "light color" of the lighting fixture.

[0022] The basic item "shape" classifies the shape of the lighting fixture into "square", "round", etc.

[0023] The basic item "category" is subdivided into, for example, hierarchical basic items "large category," "medium category," and "small category." The basic item "large category" classifies lighting fixture categories into "auxiliary lighting," "base light," "emergency light," "guide light," etc. The basic item "medium category" is constructed under the basic item "large category" and is created for each classification of the "large category." For example, if "base light" is set as the basic item "large category," the basic item "medium category" corresponding to "base light" classifies lighting fixture categories into "pendant light," "direct-mounted base light," "recessed base light," "ceiling light," etc. The basic item "small category" is constructed under the basic item "medium category" and is created for each classification of the "medium category." For example, if "recessed base light" is set as the basic item "medium category," the basic item "small category" corresponding to "recessed base light" classifies lighting fixture categories into "panel-mounted," "oval panel-mounted," "open-bottom type," "louver-mounted," etc.

[0024] The classification item "lamp brightness" classifies the brightness of the lamp of a lighting fixture by the rated power consumption of the lamp or by the type of lamp.

[0025] The classification item "light color" classifies the light color of a lamp into "daylight color," "neutral white," "white," "warm white," "incandescent white," and the like.

[0026] (Attribute Items) Attribute items are classification items mainly relating to the details of a lighting fixture. Attribute items include classification items such as "function," "dimension," "color," "material," and "price" of a lighting fixture, for example.

[0027] The attribute item "function" classifies the presence or absence of functions such as "pull switch," "color adjustment," "human sensor," "brightness sensor," "HACCP compliant," "guard / box," and "renewal plate." The attribute item "function" also classifies the type of each function such as "power supply," "emergency lighting time," "reflector," "glare reduction," and "light distribution." HACCP is an abbreviation for Hazard Analysis and Critical Control Point, and is a hygiene management method.

[0028] (2.2) Input Device The input device 2 has a user interface function for accepting user operations. The input device 2 has at least one user interface such as a touch panel display, a keyboard, and a mouse.

[0029] In this embodiment, the user performs operations on the input device 2 to cause the search device 1 to execute a search process. For example, by operating the input device 2, the user inputs data on the basic items and attribute items of the existing appliance Ea into the search device 1, or instructs the search device 1 to start or end the search process.

[0030] (2.3) Output Device The output device 3 includes a liquid crystal display device or an organic EL display device, and receives image data from the search device 1 and displays the image data. The image data displays, for example, an input screen for each data item of the existing appliance Ea, an operation screen for executing and stopping a search process for extracting the proposed appliance Eb as a specific object, and a notification screen for the execution process and results of the search process. The user operates the input device 2 while viewing the screen displayed on the output device 3 to input each data item of the existing appliance Ea, execute and stop the search process, and check the process and results of the search process. The input device 2 and output device 3 may be the operation unit and screen of a smartphone, tablet terminal, or the like. While a display device is generally used as the output device 3, a printer may also be used.

[0031] (2.4) Database The database 4 is, for example, a server device, and stores the fixture information Y1 shown in Fig. 2. The fixture information Y1 is information on the basic items and attribute items of each of the current fixtures E1, E2, ..., which are lighting fixtures currently on sale. That is, the fixture information Y1 includes information on the basic items and attribute items associated with each of the current fixtures E1, E2, ....

[0032] The database 4 is communicatively connected to the network. The search device 1 is also communicatively connected to the network, and the search device 1 can access the database 4 via the network. The network is constructed to include a LAN (Local Area Network) or a public communication network such as a mobile phone network, the Internet, or a fixed telephone network. The network may also be a dedicated line for an organization such as a company, factory, office, or department.

[0033] (2.5) Search Device The search device 1 includes a computer system primarily composed of one or more processors and memory. The search device 1 is realized by one or more processors executing a program stored in the memory of the computer system. The program may be pre-recorded in the memory. Alternatively, the program may be provided via a telecommunications line. Furthermore, the program may be provided by being recorded on a non-transitory recording medium, such as a memory card, optical disk, or hard disk drive, that is readable by the processor. The processor is composed of one or more electronic circuits including a semiconductor integrated circuit (IC) or a large-scale integrated circuit (LSI). The IC or LSI referred to here is referred to by different names depending on the degree of integration, and includes integrated circuits called system LSI, very large scale integration (VLSI), or ultra large scale integration (ULSI). Furthermore, a field-programmable gate array (FPGA), which is programmed after the LSI is manufactured, or a logic device capable of reconfiguring the connections within the LSI or the circuit partitions within the LSI can also be used as a processor. The electronic circuits may be integrated into one chip or distributed across multiple chips. The chips may be integrated into one device or distributed across multiple devices. The computer system referred to here includes a microcontroller having one or more processors and one or more memories. Therefore, the microcontroller is also composed of one or more electronic circuits including a semiconductor integrated circuit or a large-scale integrated circuit.

[0034] The search device 1 may be housed in a single housing, or may be housed in two or more housings. The search device 1 is not limited to being implemented by a single computer device, but may also be implemented by multiple computers linked to each other. Furthermore, the search device 1 may be constructed as a cloud computing system.

[0035] As shown in FIG. 1, the search device 1 includes a memory unit 11, a first acquisition unit 12, a second acquisition unit 13, a selection unit 14, a data creation unit 15, a data output unit 16, a condition change unit 17, and a condition update unit 18.

[0036] (2.5.1) Storage Unit The storage unit 11 has a storage medium such as an EEPROM (Electrically Erasable Programmable Read-Only Memory), a flash memory, an HDD (Hard Disk Drive), an SSD (Solid State Drive), or a memory card.

[0037] The storage unit 11 stores data of the first search criteria X1 and the second search criteria X2.

[0038] (First Search Conditions) The first search conditions X1 are set based on the existing fixtures Ea. As shown in FIG. 3 , the first search conditions X1 include basic information X11 and first attribute information X12 of the existing fixtures Ea, which are existing lighting fixtures. The first search conditions X1 set classification items (basic items and attribute items) of the existing fixtures Ea. The data of the first search conditions X1 is created, for example, by the user operating the input device 2 and stored in the memory unit 11.

[0039] The basic information X11 is information for narrowing down search results from multiple existing fixtures E1, E2, ... and is information related to the above-mentioned basic items of lighting fixtures. That is, the basic information X11 includes basic items such as the "shape," "category," "lamp brightness," and "light color" of the existing fixture Ea. Note that the basic information X11 does not need to include all basic items; it is sufficient to include at least one basic item.

[0040] The first attribute information X12 is information for further narrowing down search results to existing fixtures E1, E2, ... that satisfy the basic information X11, and is information regarding the above-mentioned attribute items of the lighting fixtures. That is, the first attribute information X12 includes attribute items such as the function, dimensions, color, material, and price of the existing fixture Ea. Note that the first attribute information X12 does not need to include all attribute items; it is sufficient to include at least one attribute item.

[0041] The first search criteria X1 illustrated in Fig. 3 associate basic information X11 and first attribute information X12 with the existing appliance Ea. Note that the first search criteria X1 illustrated in Fig. 3 includes attribute items "attribute 1," "attribute 2," ... as the first attribute information X12. Note that "attribute 1," "attribute 2," ... each indicate one of the attribute items such as "function," "dimension," "color," "material," and "price" described above.

[0042] (Second Search Conditions) As shown in FIG. 4 , the second search conditions X2 include second attribute information X22 and are pre-stored in the storage unit 11. The second attribute information X22 is information about the above-described attribute items of the lighting fixtures and is used to further narrow down search results to current fixtures E1, E2, E3, E4, E5, etc. that satisfy the basic information X11. The second attribute information X22 is also pre-stored information about attribute items required for a lighting fixture (i.e., a proposed fixture Eb) to replace the existing fixture Ea. The second search conditions X2 are initial setting conditions for attribute items used by the selection unit 14 (described later) when selecting a specific target, the proposed fixture Eb, from the current fixtures E1, E2, etc. A user who actually performs a search process does not need to create data for the second search conditions X2 each time a search is performed. The data for the second search conditions X2 is created in advance by an administrator or user of the search system 10 at an appropriate time (before a search is performed) and stored in the storage unit 11. That is, the second search criteria X2 are search criteria that are used not only for the current search but also for other searches.

[0043] Specifically, the second search criteria X2 are set based on the requirements for proposed fixtures Eb to replace the existing fixtures Ea. The second search criteria X2 include attribute items that are likely to be emphasized when proposing replacement lighting fixtures, but do not include attribute items that are unlikely to be emphasized. Whether each of the attribute items is likely to be emphasized or unlikely to be emphasized is determined based on the environment of the current renovation site and the track record of previous lighting fixture proposals, and this determination is reflected in the second search criteria X2 in advance. That is, the second search criteria X2 are created in advance based on the environment of the current renovation site and the track record of previous lighting fixture proposals, and are pre-stored in the storage unit 11. Examples of renovation sites where lighting fixture replacement is actually performed include factories, offices, stores, commercial facilities, hospitals, schools, stadiums, and residential buildings. Because attribute items that are emphasized vary depending on the environment of the renovation site, the attribute items included in the second attribute information X22 are set for each environment of the renovation site. The second attribute information X22 does not need to include all attribute items; it is sufficient to include at least one attribute item. The second search criteria X2 illustrated in FIG. 4 include attribute items "attribute 1," "attribute 3," "attribute 7," and so on as second attribute information X22.

[0044] As described above, the classification items of the first search criteria X1 include both basic items and attribute items. On the other hand, the classification items of the second search criteria X2 include only attribute items. In other words, the second search criteria X2 are set for a portion of the classification items of the first search criteria X1.

[0045] 5 shows a setting screen G1 for creating second search criteria X2. In this embodiment, the setting screen G1 is displayed on the output device 3. An administrator or user of the search system 10 displays the setting screen G1 on the output device 3 at an appropriate timing, and operates the input device 2 to create data for the second search criteria X2 and store it in advance in the storage unit 11. A user who actually performs a search does not need to use the setting screen G1 to create data for the second search criteria X2 every time they perform a search.

[0046] The settings screen G1 allows the settings of each of the following functions: "Pull Switch," "Color Adjustment," "Human Sensor," "Brightness Sensor," "HACCP Compliance," "Power," "Emergency Illumination Time," "Hanging Device / Metal Fitting," "Guard / Box," "Renewal Plate," "Reflector," "Glare Reduction," and "Light Distribution." Specifically, the settings screen G1 allows the settings of each function as "Not Selected" or "Selected." For functions set as "Selected," the presence or absence of the function or the type of function is set. Functions set as "Selected" are included in the attribute items of the second search conditions X2, and the presence or absence of the function or the type of function is set in the second search conditions X2. Functions set as "Not Selected" are not included in the attribute items of the second search conditions X2. That is, the second attribute information X22 of the second search conditions X2 in FIG. 4 includes the attribute items "Attribute 1," "Attribute 3," "Attribute 7," etc., corresponding to the functions set as "Selected" on the settings screen G1.

[0047] (2.5.2) First Acquisition Unit and Second Acquisition Unit The first acquisition unit 12 accesses the storage unit 11 and acquires (reads out) data of the first search criteria X1 from the storage unit 11.

[0048] The second acquisition unit 13 accesses the storage unit 11 and acquires (reads) data of the second search criteria X2 from the storage unit 11 .

[0049] (2.5.3) Selection Unit The selection unit 14 selects, as a specific object, a proposed appliance Eb that satisfies third search conditions X3 consisting of at least a part of the first search conditions X1 and the second search conditions X2 from a plurality of current appliances E1, E2, ....

[0050] Specifically, the selection unit 14 creates third search criteria X3 including the basic information X11 of the first search criteria X1 and the second attribute information X22 of the second search criteria X2. The third search criteria X3 shown in Fig. 6 is composed of the basic information X11 and the second attribute information X22. The selection unit 14 then applies the third search criteria X3 to the appliance information Y1 (see Fig. 2) read from the database 4, thereby selecting, as the proposed appliance Eb, an current appliance that satisfies the third search criteria X3 from among the current appliances E1, E2, ....

[0051] Here, the second attribute information X22 includes attribute items that are likely to be important when proposing replacement lighting fixtures. Meanwhile, the first attribute information X12 is the attribute item settings of the existing fixture Ea and may include settings that are not suitable for the current installation site environment. Therefore, the selection unit 14 narrows down the current fixtures E1, E2, ... to those that satisfy the basic information X11. When further narrowing down the current fixtures that satisfy the basic information X11, the selection unit 14 uses the second attribute information X22 of the second search criteria X2 created on the setting screen G1 (see FIG. 5 ), rather than the first attribute information X12 (information on the existing fixture Ea) of the first search criteria X1. That is, the selection unit 14 narrows down the current fixtures that satisfy the basic information X11 to those that satisfy the second attribute information X22.

[0052] The second attribute information X22 includes attribute items that are likely to be emphasized when proposing a replacement lighting fixture, but does not include attribute items that are unlikely to be emphasized. Therefore, the selector 14 can select an existing fixture that is suitable for the renovation site as the proposed fixture Eb, which reduces the number of searches.

[0053] The third search conditions X3 may include part or all of the first attribute information X12 of the first search conditions X1, in addition to the basic information X11 of the first search conditions X1 and the second attribute information X22 of the second search conditions X2. In this case, if an attribute item included in the first attribute information X12 is the same as an attribute item included in the second attribute information X22, the setting of the attribute item in the third search conditions X3 is prioritized over the setting of the first attribute information X12.

[0054] (2.5.4) Data Creation Unit The data creation unit 15 creates list data showing a list of the proposed instruments Eb selected by the selection unit 14.

[0055] Specifically, the data creation unit 15 creates data for a list screen G2 shown in FIG. 7 as the list data. On the list screen G2, three current appliances E1, E6, and E15 (specific objects) are displayed as suggested appliances Eb. The list screen G2 associates the settings of the attribute items of the current appliances E1, E6, and E15 with the three current appliances E1, E6, and E15. The associated attribute items on the list screen G2 include the attribute items included in the second attribute information X22 of the third search criteria X3.

[0056] The list screen G2 has selection buttons B1 arranged corresponding to the three current appliances E1, E6, and E15, which are the proposed appliances Eb, in association with each other.

[0057] The list screen G2 has a condition change button B2 arranged corresponding to each attribute item.

[0058] (2.5.5) Data Output Unit The data output unit 16 outputs data of the list screen G2 (see FIG. 7) to the output device 3. The output device 3 displays the list screen G2. By looking at the list screen G2 displayed on the output device 3, the user can confirm that the current appliances E1, E6, and E15 are proposed appliances Eb that can replace the existing appliance Ea.

[0059] Furthermore, the user selects the selection button B1 corresponding to the current fixture to be adopted from among the three current fixtures E1, E6, and E15 displayed as the proposed fixture Eb, thereby determining from among the current fixtures E1, E6, and E15 the lighting fixture to replace the existing fixture Ea.

[0060] (2.5.6) Condition Modification Unit The condition modification unit 17 can modify the third search conditions X3 (see FIG. 6 ). Specifically, the condition modification unit 17 can change the settings of the attribute items included in the second attribute information X22 of the third search conditions X3.

[0061] Specifically, when the user presses the condition change button B2 on the list screen G2 (see FIG. 7 ), the data creation unit 15 creates data for a condition change screen for changing the settings of the attribute item corresponding to the pressed condition change button B2. The data output unit 16 outputs the data of the condition change screen to the output device 3. The output device 3 displays a condition change screen (not shown). While viewing the condition change screen displayed on the output device 3, the user performs an operation on the input device 2 to change the settings of the attribute item corresponding to the pressed condition change button B2. The condition change unit 17 changes the settings of the attribute item included in the second attribute information X22 of the third search condition X3 in accordance with the user's operation on the input device 2.

[0062] When the third search criteria X3 are changed, the selection unit 14 reselects proposed appliances Eb that satisfy the changed third search criteria X3 from the multiple current appliances E1, E2, .... The data creation unit 15 creates data for a list screen that shows a list of the proposed appliances Eb reselected by the selection unit 14. The data output unit 16 outputs the data for the list screen created based on the changed third search criteria X3 to the output device 3.

[0063] The search system 10 includes the condition change unit 17, which allows the search results to be confirmed while changing the search conditions, and allows the suggested appliances Eb to be extracted flexibly.

[0064] (2.5.7) Condition Update Unit The condition update unit 18 updates the second search conditions X2 stored in the storage unit 11 based on the history of changes to the third search conditions X3. By including the condition update unit 18, the search system 10 can update the second search conditions X2 to suit actual operations.

[0065] Furthermore, it is preferable that the condition update unit 18 has a learning model M1 constructed by machine learning, and that the learning model M1 receives a history of changes to the third search conditions X3 and updates the second search conditions X2 stored in the storage unit 11. By including the learning model M1, the search system 10 improves the accuracy of updating the second search conditions X2.

[0066] Specifically, the storage unit 11 stores data on the change history of the third search conditions X3 made by the condition change unit 17. The change history of the third search conditions X3 is a change history of the attribute items included in the second attribute information X22 of the third search conditions X3. The learning model M1 then updates the second attribute information X22 (see FIG. 4 ) of the second search conditions X2 stored in the storage unit 11 based on the data on the change history of the third search conditions X3. For example, if the change history of the third search conditions X3 shows a high frequency of changes that result in the second attribute information X22 becoming a specific setting, the learning model M1 updates the second search conditions X2 so that the second attribute information X22 becomes a specific setting.

[0067] For example, the learning model M1 is preferably constructed by machine learning such as deep learning using a neural network. Alternatively, the learning model M1 may use other algorithms such as a support vector machine.

[0068] (3) Search Method The search method by the above-described search system 10 can be summarized as shown in the flowchart of Fig. 8. This search method may be realized by a computer system executing a program.

[0069] The search method includes a first acquisition step S1, a second acquisition step S2, a selection step S3, a data creation step S4, and a data output step S5, with a plurality of current appliances E1, E2, . . . as search targets.

[0070] In the first acquisition step S1, the first acquisition unit 12 acquires first search conditions X1. The first search conditions X1 are search conditions set for a plurality of classification items for classifying a plurality of current appliances E1, E2, ....

[0071] In the second acquisition step S2, the second acquisition unit 13 acquires data of the second search criteria X2 from the storage unit 11. The second search criteria X2 are search criteria set for some of the multiple classification items.

[0072] In the selection step S3, the selection unit 14 selects a current appliance that satisfies a third search condition X3 consisting of a part of the first search condition X1 and the second search condition X2 from the multiple current appliances E1, E2, ... as a proposed appliance Eb (specific target object).

[0073] In the data creation step S4, the data creation unit 15 creates data (list data) for a list screen G2 that displays a list of the suggested instruments Eb.

[0074] In the data output step S5, the data output unit 16 outputs the data of the list screen G2.

[0075] The above-described search method, like the search system 10, can reduce the time required to narrow down search results from multiple objects.

[0076] (4) First Modification A search device 1A of the first modification includes an update determination unit 19 instead of the condition update unit 18 of the search device 1, as shown in FIG.

[0077] The update determination unit 19 determines, based on the history of changes to the third search conditions X3, whether to update the second search conditions X2 stored in the storage unit 11. For example, if the change history of the third search conditions X3 shows a high frequency of changes that result in the second attribute information X22 becoming a specific setting, the update determination unit 19 determines to update the second search conditions X2 so that the second attribute information X22 becomes a specific setting.

[0078] When the update determination unit 19 determines that the second search criteria X2 should be updated, the data creation unit 15 creates announcement data to prompt the user to update the second search criteria X2. The data output unit 16 outputs the announcement data to the output device 3. In this embodiment, the announcement data is screen data, and the output device 3 displays the announcement data. When the administrator or user checks the announcement data displayed on the output device 3, they take action to update the second search criteria X2.

[0079] In this modified example, the administrator or user can be prompted to take action to update the second search criteria X2.

[0080] (5) Second Modification The first search criteria X1 do not have to be stored in the storage unit 11. The first acquisition unit 12 may acquire the data of the first search criteria X1 directly from the input device 2.

[0081] The attribute items included in the first attribute information X12 of the first search condition X1 and the attribute items included in the second attribute information X22 of the second search condition X2 may all be different, all be the same, or some may be the same.

[0082] The current appliances E1, E2, ..., which are the targets, the proposed appliance Eb, which is the specific target, and the existing appliance Ea may be appliances other than lighting appliances (such as air conditioning-related appliances, housing / facility-related appliances, cooking / housework-related appliances, and management / operation-related appliances). "Air conditioning-related appliances" include air conditioners, ventilation fans, air vents, air purifiers, etc. "Housework / facility-related appliances" include fire alarms, intercoms, electric blinds, electric curtains, etc. "Cooking / housework-related appliances" include dishwashers, dish dryers, washing machines, clothes dryers, etc. In other words, the search system 10 can be used when proposing a renewal to replace an existing appliance with one of multiple current appliances that are currently on sale.

[0083] It is not essential that the search device 1, 1A include the storage unit 11, and the storage unit 11 may be provided outside the search device 1, 1A. In this case, the storage unit 11 is preferably a server device communicably connected to the search device 1, 1A via a network or the like. That is, the first acquisition unit 12 and the second acquisition unit 13 acquire the first search criteria X1 and the second search criteria X2, respectively, via a network or the like.

[0084] The functions of the search system 10 may be embodied as a search method, a computer program, or a recording medium on which a computer program is recorded.

[0085] (6) Summary A search system (10) of a first aspect according to the above-described embodiment searches for a plurality of objects (E1, E2, ...). The search system (10) includes a first acquisition unit (12), a second acquisition unit (13), a selection unit (14), a data creation unit (15), and a data output unit (16). The first acquisition unit (12) acquires data on first search criteria (X1) set for a plurality of classification items for classifying the plurality of objects (E1, E2, ...). The second acquisition unit (13) acquires data on second search criteria (X2) from a storage unit (11) that pre-stores second search criteria (X2) set for some of the plurality of classification items. A selection unit (14) selects, as specific objects (Eb), objects that satisfy third search conditions (X3) consisting of at least a part of the first search conditions (X1) and the second search conditions (X2) from the plurality of objects (E1, E2, ...). A data creation unit (15) creates list data (G2) that shows a list of the specific objects (Eb). A data output unit (16) outputs the list data (G2).

[0086] The above-described search system (10) can reduce the time required to narrow down search results from multiple objects (E1, E2, . . . ).

[0087] In the search system (10) of the second aspect according to the above-described embodiment, in the first aspect, the first search criteria (X1) include basic information (X11) for narrowing down search results from a plurality of objects (E1, E2, ...) and first attribute information (X12) for further narrowing down search results from objects among the plurality of objects (E1, E2, ...) that satisfy the basic information (X11). The second search criteria (X2) include second attribute information (X22) for further narrowing down search results from objects among the plurality of objects (E1, E2, ...) that satisfy the basic information (X11). It is preferable that the third search criteria (X3) include the basic information (X11) and the second attribute information (X22).

[0088] The above-described search system (10) can reduce the time required to narrow down search results from multiple objects (E1, E2, . . . ).

[0089] It is preferable that the search system (10) of the third aspect according to the above embodiment further comprises a condition change unit (17) that changes the third search condition (X3) in the first or second aspect.

[0090] The above-described search system (10) can confirm search results while changing search conditions, and can flexibly extract specific objects (Eb).

[0091] In the third aspect, the search system (10) of the fourth aspect according to the above-described embodiment preferably further comprises a condition update unit (18) that updates the second search conditions (X2) stored in the memory unit (11) based on a history of changes to the third search conditions (X3).

[0092] The above-mentioned search system (10) can update the second search criteria (X2) to suit actual operations.

[0093] In the search system (10) of the fifth aspect according to the above-described embodiment, in the fourth aspect, the condition update unit (18) preferably has a learning model (M1) constructed by machine learning. The learning model (M1) receives a history of changes to the third search conditions (X3) and updates the second search conditions (X2) stored in the memory unit (11).

[0094] The above-described search system (10) can improve the accuracy of updating the second search criteria (X2).

[0095] In the search system (10) of the sixth aspect according to the above-described embodiment, in the third aspect, it is preferable that the search system (10) further includes an update determination unit (19) that determines whether to update the second search criteria (X2) stored in the storage unit (11) based on a history of changes to the third search criteria (X3). When the update determination unit (19) determines that the second search criteria (X2) should be updated, the data creation unit (15) creates announcement data to prompt the user to update the second search criteria (X2). The data output unit (16) outputs the announcement data.

[0096] The above-described search system (10) can prompt the administrator or user to take action to update the second search criteria (X2).

[0097] In the search system (10) of the seventh aspect according to the above-described embodiment, in any of the first to sixth aspects, the first search condition (X1) is preferably set based on an existing appliance (Ea), and the second search condition (X2) is preferably set based on a request for a proposed appliance (Eb) to replace the existing appliance (Ea).

[0098] The above-described search system (10) makes it easier to extract a suggested tool (Eb) that meets a request from a plurality of objects (E1, E2, . . . ).

[0099] It is preferable that the search system (10) of the eighth aspect of the above-mentioned embodiment, in any of the first to seventh aspects, further comprises an input device (2) that creates data of at least the first search criteria (X1) based on user operation.

[0100] The above-described search system (10) can set a first search condition (X1).

[0101] It is preferable that the search system (10) of the ninth aspect of the above-mentioned embodiment, in any of the first to eighth aspects, further comprises an output device (3) that receives the list data (G2) and presents the list data (G2) to the user.

[0102] The above-described search system (10) can present search results to a user.

[0103] The search method of the tenth aspect according to the above-described embodiment includes a first acquisition step (S1), a second acquisition step (S2), a selection step (S3), a data creation step (S4), and a data output step (S5). The first acquisition step (S1) acquires data on first search conditions (X1) set for a plurality of classification items for classifying a plurality of objects (E1, E2, ...). The second acquisition step (S2) acquires data on second search conditions (X2) from a storage unit (11) that pre-stores second search conditions (X2) set for some of the plurality of classification items. The selection step (S3) selects, as specific objects (Eb), objects that satisfy third search conditions (X3) consisting of at least a portion of the first search conditions (X1) and the second search conditions (X2) from the plurality of objects (E1, E2, ...). The data creation step (S4) creates list data (G2) showing a list of the specific objects (Eb). The data output step (S5) outputs the list data (G2).

[0104] The above-described search method can reduce the time required to narrow down search results from multiple objects (E1, E2, . . . ).

[0105] A program according to an eleventh aspect of the above-described embodiment causes a computer system to execute the search method according to the tenth aspect.

[0106] The above-described program can reduce the time required to narrow down search results from multiple objects (E1, E2, . . . ).

[0107] 10 Search system 12 First acquisition unit 13 Second acquisition unit 14 Selection unit 15 Data creation unit 16 Data output unit 17 Condition change unit 18 Condition update unit 19 Update determination unit 2 Input device 3 Output device E1, E2, ... Current appliance (object) Eb Proposed appliance (specific object) G2 List screen (list data) M1 Learning model X1 First search condition X11 Basic information X12 First attribute information X2 Second search condition X22 Second attribute information X3 Third search condition S1 First acquisition step S2 Second acquisition step S3 Selection step S4 Data creation step S5 Data output step

Claims

1. A search system for searching multiple objects, a first acquisition unit that acquires data of a first search condition set for a plurality of classification items for classifying the plurality of objects; a second acquisition unit that acquires data of the second search conditions from a storage unit that stores in advance second search conditions set for some of the plurality of classification items; a selection unit that selects, as a specific object, an object that satisfies a third search condition consisting of at least a part of the first search condition and the second search condition from the plurality of objects; a data creation unit that creates list data indicating a list of the specific objects; a data output unit that outputs the list data. Search system.

2. the first search criteria include basic information for narrowing down search results from the plurality of objects, and first attribute information for further narrowing down the search results from objects among the plurality of objects that satisfy the basic information, the second search criteria include second attribute information for further narrowing down the search results to objects that satisfy the basic information among the plurality of objects; The third search condition includes the basic information and the second attribute information. The search system of claim 1.

3. The third search condition change unit is further provided. The search system of claim 1.

4. The system further includes a condition update unit that updates the second search conditions stored in the storage unit based on a history of changes to the third search conditions. The search system according to claim 3.

5. the condition update unit has a learning model constructed by machine learning, The learning model receives a history of changes to the third search conditions and updates the second search conditions stored in the storage unit. The search system according to claim 4.

6. an update determination unit that determines whether to update the second search conditions stored in the storage unit based on a history of changes to the third search conditions; the data creation unit creates announcement data for prompting a user to update the second search conditions when the update determination unit determines that the second search conditions should be updated; The data output unit outputs the announcement data. The search system according to claim 3.

7. the first search condition is set based on an existing appliance; The second search condition is set based on a request for a proposed appliance to replace the existing appliance. The search system according to any one of claims 1 to 6.

8. The system further includes an input device that creates at least the first search condition data based on a user operation. The search system according to any one of claims 1 to 6.

9. an output device that receives the list data and presents the list data to a user; The search system according to any one of claims 1 to 6.

10. A search method for searching multiple objects, a first acquisition step of acquiring data of first search conditions set for a plurality of classification items for classifying the plurality of objects; a second acquisition step of acquiring data of the second search conditions from a storage unit that pre-stores second search conditions set for some of the plurality of classification items; a selection step of selecting, as a specific object, an object that satisfies a third search condition consisting of at least a part of the first search condition and the second search condition from the plurality of objects; a data creation step of creating list data indicating a list of the specific objects; a data output step of outputting the list data. How to search.

11. A program for causing a computer system to execute the search method of claim 10.