Search system, search method, and program

Abstract

The present disclosure addresses of the problem of providing a search system, a search method, and a program which make it possible to increase the possibility of indicating a useful search result even when a search condition includes dimensions. In a search system (10), a first acquisition unit (12) acquires data of first search conditions (X1) which have been set for a plurality of classification items including dimensions. A second acquisition unit (13) acquires, from a storage unit (11), data of a second search condition (X2) which has been set for an allowable range of dimensions. A selection unit (14) selects, from a plurality of objects, specific objects which, among the plurality of objects, meet the first search conditions (X1) and the second search condition (X2). A data creation unit (15) creates list data which indicate 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 in Patent Document 1 mentioned above, even if the dimensions of a product (object) are included in the search criteria, useful search results cannot be displayed if there are no products with the same dimensions as the search criteria in the search targets.

[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 increase the likelihood of displaying useful search results even when dimensions are included in the search criteria.

[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 of first search conditions set for multiple classification items including dimensions. The second acquisition unit acquires data of second search conditions set for the allowable range of the dimensions from a storage unit that pre-stores the second search conditions. The selection unit selects objects that satisfy the first search conditions and the second search conditions as specific objects 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 for first search conditions set for multiple classification items including dimensions. The second acquisition step acquires data for second search conditions set for an acceptable range of the dimensions from a storage unit that pre-stores second search conditions. The selection step selects objects that satisfy the first search conditions and the second search conditions as specific objects 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 of an embodiment. FIG. 2 is a diagram showing appliance information in the search system of the same. FIG. 3 is a diagram showing first search conditions in the search system of the same. FIG. 4 is a diagram showing second search conditions in the search system of the same. FIG. 5 is a diagram showing a setting screen in the search system of the same. FIG. 6 is a diagram for explaining the process of selecting a suggested appliance in the search system of the same. FIG. 7 is a diagram for explaining the process of selecting a suggested appliance in the search system of the same. FIG. 8 is a diagram showing a list screen in the search system of the same. FIG. 9 is a diagram showing a size change screen in the search system of the same. FIG. 10 is a flowchart showing a search method of an embodiment. FIG. 11 is a block diagram showing a search system of 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 including dimensions. The second acquisition unit 13 acquires data on second search criteria X2 set for an acceptable range of dimensions from a storage unit 11 that pre-stores the second search criteria X2. The selection unit 14 selects, from the multiple objects, objects that satisfy the first search criteria X1 and the second search criteria X2 as specific 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 the first search criteria X1 and the second search criteria X2. The first search criteria X1 set dimensions, and the second search criteria X2 set an allowable range for the dimensions. As a result, the search system 10 can extract objects with dimensions that fall within the allowable range of the second search criteria X2, even if the search targets do not contain objects with the same dimensions as the first search criteria X1. Therefore, the search system 10 can increase the likelihood of displaying useful search results, even if the search criteria include dimensions.

[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, E3, E4, E5, ... (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. 8 ). 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 "dimensions," "functions," "color," "material," and "price" of a lighting fixture.

[0027] In the attribute item "dimensions", dimensional values ​​such as the long side, short side, and diameter of the external shape of the lighting fixture are set.

[0028] 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.

[0029] (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.

[0030] 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.

[0031] (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.

[0032] (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, ....

[0033] 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.

[0034] (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.

[0035] 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.

[0036] 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.

[0037] (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.

[0038] The storage unit 11 stores data of the first search criteria X1 and the second search criteria X2.

[0039] (First Search Condition) The first search condition X1 is set based on the existing fixture Ea. As shown in FIG. 3 , the first search condition X1 includes basic information X11 and attribute information X12 of the existing fixture Ea, which is an existing lighting fixture. The first search condition X1 sets classification items (basic items and attribute items) of the existing fixture Ea. The data of the first search condition X1 is created, for example, by the user operating the input device 2 and stored in the memory unit 11.

[0040] 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.

[0041] The attribute information X12 is information for further narrowing down the 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 attribute information X12 includes attribute items such as the dimensions, function, color, material, and price of the existing fixture Ea.

[0042] In particular, the attribute item "dimension" has a dimension setting value Va1 that indicates the dimension of the existing fixture Ea. The dimension setting value Va1 includes at least one of a dimension setting value Va11 that indicates the dimension of the long side of the exterior shape of the existing fixture Ea, a dimension setting value Va12 that indicates the dimension of the short side, and a dimension setting value Va13 that indicates the diameter.

[0043] The attribute information X12 does not need to include all attribute items, but only needs to include at least the attribute item "dimensions."

[0044] The first search criteria X1 illustrated in Fig. 3 associates basic information X11 and attribute information X12 with the existing appliance Ea. Note that the first search criteria X1 illustrated in Fig. 3 includes the attribute items "dimensions," "attribute 1," "attribute 2," etc. as the attribute information X12. Note that "attribute 1," "attribute 2," etc. are attribute items other than "dimensions," and each indicates one of the attribute items such as "function," "color," "material," and "price" described above.

[0045] (Second Search Condition) The second search condition X2 is set based on the requirement for a proposed appliance Eb that can replace the existing appliance Ea. Specifically, the second search condition X2 sets a dimensional tolerance range W1 for the dimension setting value Va1 in the first search condition X1. The tolerance range W1 is set to a range that satisfies the requirement for the proposed appliance Eb, that is, that the existing appliance Ea can be replaced with the proposed appliance Eb, based on the dimensions of the embedding hole or mounting bracket of the existing appliance Ea. In other words, the tolerance range W1 is set within the range of dimensions of the proposed appliance Eb that can replace the existing appliance Ea.

[0046] In this embodiment, the second search criteria X2 associates a dimension tolerance range W1 with each of the settings of a plurality of classification items. For example, as shown in Fig. 4, the second search criteria X2 associates an upper limit parameter W11 for determining the upper limit of the dimension and a lower limit parameter W12 for determining the lower limit of the dimension as the dimension tolerance range W1 with each combination C1 of the basic items "large category," "medium category," and "small category."

[0047] 4, the target C2 included in the second search criteria X2 is a target for which the dimensional tolerance range W1 is applied, and any one of the long side, short side, or diameter of the external shape of the lighting fixture is set. The target C2 is also associated with each combination C1 of the basic items "large category," "medium category," and "small category."

[0048] The second search criteria X2 may associate classification items other than the basic items "major category," "medium category," and "minor category" with the allowable range W1.

[0049] 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.

[0050] The setting screen G1 has a plurality of setting spaces SP1 arranged vertically, each having input fields R1-R6, a radio button RB1, and a delete button B1.

[0051] In the input field R1, the setting for the basic item "large category" is input. In the input field R2, the setting for the basic item "medium category" is input. In the input field R3, the setting for the basic item "small category" is input. In the input field R4, the target C2 of the tolerance range W1 is input. In the input field R5, the upper limit parameter W11 of the tolerance range W1 is input. In the input field R6, the lower limit parameter W12 of the tolerance range W1 is input. By selecting the radio button RB1, either "%" or "mm" is selected as the unit for the upper limit parameter W11 and the lower limit parameter W12. By pressing the delete button B1, the setting space SP1 containing the delete button B1 is deleted.

[0052] When "%" is selected as the unit for the upper limit parameter W11 and the lower limit parameter W12 by the radio button RB1, the upper limit parameter W11 and the lower limit parameter W12 are set to values ​​of 0 or more and 100 or less, respectively.

[0053] When "mm" is selected as the unit for the upper limit parameter W11 and the lower limit parameter W12 by using the radio button RB1, the upper limit parameter W11 is set to a value equal to or greater than 0, and the lower limit parameter W12 is set to a value equal to or less than 0.

[0054] (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.

[0055] 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 .

[0056] (2.5.3) Selection Unit The selection unit 14 selects, as a specific object, a proposed appliance Eb that satisfies the first search criteria X1 acquired by the first acquisition unit 12 and the second search criteria X2 acquired by the second acquisition unit 13 from the multiple current appliances E1, E2, .... That is, the selection unit 14 applies the first search criteria X1 and the second search criteria X2 read from the storage unit 11 to the appliance information Y1 (see FIG. 2 ) read from the database 4, thereby selecting the proposed appliance Eb from the current appliances E1, E2, ....

[0057] Specifically, the selection unit 14 applies the allowable range W1 of the second search condition X2 to the dimension setting value Va1 (see FIG. 3) set in the attribute information X12 of the first search condition X1.

[0058] The selector 14 sets the upper limit dimension Vb1 by applying the upper limit parameter W11 to the dimension setting value Va1. If the unit of the upper limit parameter W11 is "%, the upper limit dimension Vb1 = Va1 W11 / 100. If the unit of the upper limit parameter W11 is "mm", the upper limit dimension Vb1 = Va1 + W11.

[0059] The selector 14 sets the lower limit dimension Vc1 by applying the lower limit parameter W12 to the dimension setting value Va1. If the unit of the lower limit parameter W12 is "%, the lower limit dimension Vc1 = Va1 W12 / 100. If the unit of the lower limit parameter W12 is "mm", the lower limit dimension Vc1 = Va1 + W12 (W12 is a value less than or equal to 0).

[0060] The selection unit 14 then selects, as the proposed appliance Eb, an current appliance from among the current appliances E1, E2, ... that satisfies the following search conditions J1, J2. Search condition J1: Satisfies the basic information X11 (see FIG. 3) of the first search condition X1 and the attribute 1, attribute 2, attribute 3, ... (attribute items other than "dimension") of the attribute information X12 (see FIG. 3). Search condition J2: The attribute item "dimension" is set to a value within a range equal to or less than the upper limit dimension Vb1 and equal to or greater than the lower limit dimension Vc1.

[0061] For example, assume that the current fixtures that satisfy search condition J1 are recessed base lights. In this case, the object C2 that the selection unit 14 should refer to in the second search condition X2 is the "long side" and the "short side." In other words, the selection unit 14 selects, as proposed fixtures Eb, current fixtures whose long side and short side dimensions satisfy search condition J2 from among the current fixtures that satisfy search condition J1.

[0062] FIG. 6 is a graph plotting points corresponding to current fixtures that satisfy search criteria J1 on a plane with the horizontal axis representing the long side dimension and the vertical axis representing the short side dimension. In other words, FIG. 6 shows a distribution of points corresponding to current fixtures that satisfy search criteria J1. In FIG. 6, the dimension setting value Va11 represents the long side dimension setting value, and the dimension setting value Va12 represents the short side dimension setting value. Search criteria J2, determined from the first search criteria X1 and the second search criteria X2, are as follows: the upper limit dimension Vb1 of the long side of the recessed base light is the upper limit dimension Vb11, the lower limit dimension Vc1 of the long side is the lower limit dimension Vc11, the upper limit dimension Vb1 of the short side is the upper limit dimension Vb12, and the lower limit dimension Vc1 of the short side is the lower limit dimension Vc12. In FIG. 6, two current fixtures, E3 and E7, satisfy search criteria J2, and the selection unit 14 selects the current fixtures E3 and E7 as proposed fixtures Eb.

[0063] Alternatively, assume that the current fixtures that satisfy search condition J1 are downlights. In this case, the object C2 that the selection unit 14 should refer to in the second search condition X2 is "diameter." That is, the selection unit 14 selects, as proposed fixtures Eb, current fixtures whose diameter dimension satisfies search condition J2 from among the current fixtures that satisfy search condition J1.

[0064] FIG. 7 is a graph plotting points corresponding to current fixtures that satisfy search condition J1 on a linear axis representing the diameter. In other words, FIG. 7 shows a distribution of points corresponding to current fixtures that satisfy search condition J1. In FIG. 7, the dimension setting value Va13 represents the diameter setting value. Furthermore, as search condition J2 determined by first search condition X1 and second search condition X2, the upper limit dimension Vb1 of the downlight diameter is set to upper limit dimension Vb13, and the lower limit dimension Vc1 of the diameter is set to lower limit dimension Vc13. In FIG. 7, of the multiple current fixtures, two current fixtures, E5 and E11, satisfy search condition J2, and the selection unit 14 selects current fixtures E5 and E11 as proposed fixtures Eb.

[0065] For example, there may be no current appliances E1, E2, ... with dimensions identical to the dimension set value Va1 set in the first search condition X1. Furthermore, the dimension set value Va1 set in the first search condition X1 may contain an error due to a measurement error or measurement error when measuring the dimensions of the existing appliance Ea. Furthermore, if the manufacturer of the existing appliance Ea is different from the manufacturer of the current appliances E1, E2, ..., the standard dimensions of each manufacturer may differ. Even in such cases, the selection unit 14 can easily select a useful proposed appliance Eb from multiple current appliances E1, E2, ... by setting an allowable range W1 for the dimension set value Va1. In other words, the search system 10 equipped with the selection unit 14 can increase the likelihood of displaying useful search results even when dimensions are included in the search conditions.

[0066] (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.

[0067] Specifically, the data creation unit 15 creates data for a list screen G2 shown in Fig. 8 as the list data. On the list screen G2, two current appliances E3 and E7 (specific objects) are displayed as proposed appliances Eb. The list screen G2 associates the two current appliances E3 and E7 with the settings of the attribute items of the current appliances E3 and E7, respectively. The attribute items associated on the list screen G2 include at least "dimensions."

[0068] The list screen G2 has selection buttons B2 corresponding to the three current appliances E3, E7, which are the proposed appliances Eb, arranged in association with each other.

[0069] The list screen G2 has a condition change button B3 arranged corresponding to each attribute item.

[0070] (2.5.5) Data Output Unit The data output unit 16 outputs data of the list screen G2 (see FIG. 8 ) 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 E3 and E7 are proposed appliances Eb that can replace the existing appliance Ea.

[0071] Furthermore, the user selects the selection button B2 corresponding to the current fixture to be adopted from the two current fixtures E3 and E7 displayed as the proposed fixture Eb, thereby determining from among the current fixtures E3 and E7 the lighting fixture to replace the existing fixture Ea.

[0072] (2.5.6) Condition Modification Unit The condition modification unit 17 can modify the dimensional tolerance range W1. Specifically, the condition modification unit 17 can modify the upper limit parameter W11 and the lower limit parameter W12.

[0073] Specifically, when the user presses the condition change button B3 (condition change button B31) corresponding to the attribute item "dimensions" on the list screen G2 (see FIG. 8), the data creation unit 15 creates a dimension change screen G3 shown in FIG. 9. The data output unit 16 outputs the data of the dimension change screen G3 to the output device 3. The output device 3 displays the dimension change screen G3. The user operates the input device 2 while viewing the dimension change screen G3 displayed on the output device 3.

[0074] The dimension change screen G3 has input fields R11-R13, a radio button RB11, an apply button B11, and a cancel button B12.

[0075] The dimension set value Va1 is input into the input field R11. The upper limit parameter W11 of the allowable range W1 is input into the input field R12. The lower limit parameter W12 of the allowable range W1 is input into the input field R13. By selecting the radio button RB11, either "%" or "mm" is selected as the unit of the upper limit parameter W11 and the lower limit parameter W12.

[0076] Then, when the Apply button B11 is pressed, the inputs in the input fields R11-R13 and the radio button RB11 are confirmed. Once the settings on the dimension change screen G3 are confirmed, the condition change unit 17 sets a new upper limit dimension Vb1 by applying the upper limit parameter W11 in the input field R12 to the dimension setting value Va1 in the input field R11. The condition change unit 17 also sets a new lower limit dimension Vc1 by applying the lower limit parameter W12 in the input field R13 to the dimension setting value Va1 in the input field R11. That is, the condition change unit 17 changes the search criteria J2 by ​​setting the new upper limit dimension Vb1 and the new lower limit dimension Vc1. The selection unit 14 then reselects proposed appliances Eb that satisfy the changed search criteria J2 from the current appliances that satisfy the search criteria J1. The data creation unit 15 creates data for a list screen that displays a list of the proposed appliances Eb reselected by the selection unit 14. The data output unit 16 outputs to the output device 3 the data of the list screen created based on the changed search criteria J2.

[0077] When the cancel button B12 is pressed, the inputs in the input fields R11-R13 and the radio button RB11 are reset.

[0078] The search system 10 includes the condition change unit 17, which allows the search results to be confirmed while changing the dimensional tolerance range W1, and thus allows for flexible extraction of the proposed appliance Eb.

[0079] Furthermore, when a condition change button B3 corresponding to an attribute item other than "dimensions" is pressed on the list screen G2, the data creation unit 15 may create data for an attribute change screen for changing the setting of the attribute item corresponding to the pressed condition change button B3. In this case, the data output unit 16 outputs data for the attribute change screen to the output device 3. The output device 3 displays the attribute change screen. While viewing the attribute change screen displayed on the output device 3, the user performs an operation on the input device 2 to change the setting of the attribute item corresponding to the pressed condition change button B3. The condition change unit 17 changes the setting of the attribute item of the first search condition X1 in response to the user's operation on the input device 2. That is, the condition change unit 17 changes the above-mentioned search condition J1 by changing the setting of the attribute item of the first search condition X1. Then, the selection unit 14 reselects proposed appliances Eb that satisfy the search condition J2 from the current appliances that satisfy the changed search condition J1. The data creation unit 15 creates data for a list screen showing a list of proposed appliances Eb reselected by the selection unit 14. The data output unit 16 outputs to the output device 3 the data of the list screen created based on the changed search criteria J1.

[0080] The search system 10 includes the condition change unit 17, which allows the search results to be confirmed while changing the first search conditions X1, and allows for flexible extraction of suggested appliances Eb.

[0081] Note that the condition change unit 17 does not change the allowable range W1 and the first search condition X1 stored in the memory unit 11, but rather changes the allowable range W1 and the first search condition X1 read from the memory unit 11 and used by the selection unit 14.

[0082] (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 dimensional tolerance range W1. That is, 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 tolerance range W1 used by the selection unit 14. By including the condition update unit 18, the search system 10 can update the second search conditions X2 to suit actual operations.

[0083] 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 dimensional tolerance range W1 and updates the second search conditions X2 stored in the storage unit 11. By providing the learning model M1, the search system 10 improves the accuracy of updating the second search conditions X2.

[0084] Specifically, the storage unit 11 stores data on the change history of the dimensional allowable range W1 made by the condition modification unit 17. The change history of the allowable range W1 is the change history of the upper limit parameter W11 and the lower limit parameter W12 made by the condition modification unit 17. The learning model M1 then updates the upper limit parameter W11 and the lower limit parameter W12 (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 allowable range W1. For example, if the change history of the allowable range W1 shows a high frequency of changes that result in the upper limit parameter W11 and the lower limit parameter W12 becoming specific settings, the learning model M1 updates the second search conditions X2 so that the upper limit parameter W11 and the lower limit parameter W12 become specific settings.

[0085] 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.

[0086] (3) Search Method The search method by the above-described search system 10 can be summarized as shown in the flowchart of Fig. 10. This search method may be realized by a computer system executing a program.

[0087] 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.

[0088] In the first acquisition step S1, the first acquisition unit 12 acquires first search criteria X1. The first search criteria X1 are search criteria set for a plurality of classification items including dimensions.

[0089] 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 the dimensional tolerance range W1.

[0090] In the selection step S3, the selection unit 14 selects an existing appliance that satisfies the first search condition X1 and the second search condition X2 from the plurality of existing appliances E1, E2, . . . as a proposed appliance Eb (specific object).

[0091] 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.

[0092] In the data output step S5, the data output unit 16 outputs the data of the list screen G2.

[0093] The above-described search method, like the search system 10, can increase the likelihood of showing useful search results even if dimensions are included in the search criteria.

[0094] (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.

[0095] The update determination unit 19 determines whether to update the second search criteria X2 stored in the storage unit 11 based on the history of changes to the dimensional tolerance range W1 made by the condition modification unit 17. That is, the update determination unit 19 determines whether to update the second search criteria X2 stored in the storage unit 11 based on the history of changes to the tolerance range W1 used by the selection unit 14. For example, if the change history of the dimensional tolerance range W1 shows a high frequency of changes that result in the upper limit parameter W11 and the lower limit parameter W12 becoming specific settings, the update determination unit 19 determines to update the second search criteria X2 so that the upper limit parameter W11 and the lower limit parameter W12 become specific settings.

[0096] 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.

[0097] In this modified example, the administrator or user can be prompted to take action to update the second search criteria X2.

[0098] (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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] (6) Summary The search system (10) of the first aspect according to the embodiment described above 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 including dimensions. The second acquisition unit (13) acquires data on second search criteria (X2) set for a dimensional tolerance range (W1) from a storage unit (11) that pre-stores the second search criteria (X2). The selection unit (14) selects an object that satisfies the first search criteria (X1) and the second search criteria (X2) from the plurality of objects (E1, E2, ...) as a specific object (Eb). The data creating section (15) creates list data (G2) showing a list of the specific objects (Eb), and the data output section (16) outputs the list data (G2).

[0103] The above-described search system (10) can increase the likelihood of displaying useful search results even when dimensions are included in the search criteria.

[0104] In the search system (10) of the second aspect of the above-described embodiment, in the first aspect, it is preferable that the second search condition (X2) corresponds to a dimensional tolerance range (W1) for each of the settings of multiple classification items.

[0105] The above-described search system (10) can increase the likelihood of displaying useful search results even when dimensions are included in the search criteria.

[0106] It is preferable that the search system (10) of the third aspect according to the above-described embodiment further comprises a condition change unit (17) that changes the allowable range (W1) in the first or second aspect.

[0107] The above-described search system (10) can confirm search results while changing the allowable range (W1), and can flexibly extract specific objects (Eb).

[0108] It is preferable that the search system (10) of the fourth aspect according to the above-described embodiment further includes a condition update unit (18) that updates the second search condition (X2) stored in the memory unit (11) based on the history of changes to the tolerance range (W1) in the third aspect.

[0109] The above-mentioned search system (10) can update the second search criteria (X2) to suit actual operations.

[0110] 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 tolerance range (W1) and updates the second search condition (X2) stored in the memory unit (11).

[0111] The above-described search system (10) can improve the accuracy of updating the second search criteria (X2).

[0112] 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 the history of changes to the allowable range (W1). 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.

[0113] The above-described search system (10) can prompt the administrator or user to take action to update the second search criteria (X2).

[0114] 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).

[0115] 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, . . . ).

[0116] 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.

[0117] The above-described search system (10) can set a first search condition (X1).

[0118] 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.

[0119] The above-described search system (10) can present search results to a user.

[0120] 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 criteria (X1) set for multiple classification items including dimensions. The second acquisition step (S2) acquires data on second search criteria (X2) set for a dimensional tolerance range (W1) from a storage unit (11) that pre-stores the second search criteria (X2). The selection step (S3) selects an object that satisfies the first search criteria (X1) and the second search criteria (X2) from multiple objects (E1, E2, ...) as a specific object (Eb). 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).

[0121] The above-described search method can increase the likelihood of showing useful search results even if the search criteria include dimensions.

[0122] 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.

[0123] The above-mentioned program can increase the likelihood of showing useful search results even when dimensions are included in the search criteria.

[0124] 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 tool (object) Eb Proposed tool (specific object) G2 List screen (list data) M1 Learning model X1 First search condition X2 Second search condition W1 Dimension tolerance 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 including dimensions; a second acquisition unit that acquires data of the second search conditions from a storage unit that stores in advance the second search conditions set for the dimensional tolerance range; a selection unit that selects an object that satisfies the first search condition and the second search condition from the plurality of objects as a specific object; 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 second search condition associates the allowable range of the dimension with each of the settings of the plurality of classification items. The search system of claim 1.

3. The device further includes a condition change unit that changes the allowable range. The search system of claim 1.

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

5. the condition update unit has a learning model constructed by machine learning, The learning model receives input of a history of changes to the tolerance range and updates the second search criteria 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 criteria stored in the storage unit based on a history of changes to the allowable range; 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 first search conditions set for a plurality of classification items including dimensions; a second acquisition step of acquiring data of the second search conditions from a storage unit that stores in advance the second search conditions set for the dimensional tolerance range; a selection step of selecting an object that satisfies the first search condition and the second search condition from the plurality of objects as a specific object; 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.