JP6019304B1 - Problem solving support system - Google Patents

Abstract

[PROBLEMS] To realize innovation creation support by effectively presenting solution concepts to innovators. A mining step for extracting a character string from information on a newly artificially created creation acquired by voice input or manual input, and each reference character string acquired in advance are classified into two or more types. And a search step for searching for one or more solution concepts based on the relationship between the solution concept and the reference character string corresponding to the character string extracted in the mining step with reference to the relationship with each solution concept. [Selection] Figure 3

Description

  The present invention relates to a problem solving support system and method, and a problem solving support program suitable for efficiently providing a concept for solving a conventional problem in a newly created artificially created product.

  Innovation is broadly classified into two types: needs-first-innovation that is created based on market needs, and seeds-first-innovation that connects technology seeds to social value. In particular, the latter seeds-first-innovation means that even if the seeds of the technology itself are superior technologies that are inventive compared to the conventional technology, unless they are to be accepted in the real world, that is to say firmly to the needs of the market. Unless it is a link, it is hard to say that innovation is true.

  In other words, from R & D to commercialization and mass dissemination, the so-called Death Valley and Darwin Sea stand out. And if this is overcome, the seeds of the technology that has been created will develop into social value and become a true innovation.

  In particular, such innovations can be born not only from large corporations, but also from small and medium enterprises and by extension, individual inventors. In the process of creating this innovation, there are problems that become obstacles to meeting the demands from the market, and it is often created by clearing those problems. By using the solution concept to clear this problem as a hint, innovation by innovators will be realized. Conversely, by effectively presenting the optimal solution concept for solving the problem to the innovator, it is also possible to support the creation of innovation by the innovator.

  A system that supports innovation creation has been proposed in the past (see, for example, Patent Document 1). This patent document 1 is a technology based on the premise that input character information is grouped and problem analysis is performed by a problem analysis method, and not only the idea creation process but also the scenario is finally generated. Is disclosed.

JP 2005-284548 A

  However, according to the technology disclosed in Patent Document 1 described above, there is a problem in that it is not always possible to effectively present a solution concept to an innovator, and innovation creation support cannot be realized.

  Therefore, the present invention has been devised in view of the above-described problems, and its purpose is to realize innovation creation support by effectively presenting a solution concept to an innovator. To provide a possible problem solving support system and method, and a problem solving support program.

The problem-solving support system according to the present invention includes a mining means for extracting a character string from information on a newly artificially created creation obtained by voice input or manual input, each reference character string acquired in advance, and 2 Referring to three steps or more association degree between each resolution concept classified above species, based on three or more stages of association degree between the reference string and resolution concept corresponding to the extracted character string by the mining means And a search means for searching for one or more solution concepts.

The problem solving support system according to the present invention includes a mining means for extracting a plurality of character strings from information on a newly artificially created product acquired by voice input or manual input, and a plurality of reference characters acquired in advance. Reference is made to three or more levels of association with each solution concept for combinations between columns, and 3 with each solution concept for combinations between a plurality of reference character strings corresponding to a plurality of character strings extracted by the mining means. And a search means for searching for one or more solution concepts based on the degree of association at a stage or higher .

A problem solving support method to which the present invention is applied includes a mining step of extracting a character string from information on a newly artificially created creation obtained by voice input or manual input by a problem solving support system; reference character string and are classified into two or more by referring to three or more levels of association degree between each resolution concept, reference character string corresponding to the character string extracted in the mining step and solutions concept with three or more stages of And a search step for searching for one or more solution concepts by a problem solving support system based on the degree of association .

Problem solving support method according to the present invention, a mining extracting the voice input or manual new plurality of character strings from the information on artificially created by the creations acquired by the input problem solving support system, previously obtained Each of the combinations between the plurality of reference character strings corresponding to the plurality of character strings extracted in the mining step is referred to with reference to three or more levels of association with each solution concept for the combination between the plurality of reference character strings. And a search step of searching for one or more solution concepts by a problem solving support system based on three or more levels of association with the solution concept.

The problem-solving support program to which the present invention is applied includes a mining step for extracting a character string from information on a newly artificially created product acquired by voice input or manual input, and each reference character string acquired in advance. Referring to three steps or more association degree between each resolution concept classified into two or more, based on three or more stages of association degree between the reference string and resolution concept corresponding to the character string extracted in the mining step And a search step for searching for one or more solution concepts.

A problem-solving support program to which the present invention is applied includes a mining step for extracting a plurality of character strings from information about a newly artificially created product acquired by voice input or manual input, and a plurality of reference items acquired in advance. Referencing 3 or more levels of association with each solution concept for combinations between character strings, and 3 with each solution concept for combinations between a plurality of reference character strings corresponding to a plurality of character strings extracted in the mining step. A search step for searching for one or more solution concepts is executed by a computer based on the degree of association at one or more stages .

  According to the present invention having the above-described configuration, it is possible to immediately select a solution concept corresponding to the character string obtained by analyzing the basic information and output it. As a result, innovation creation support can be realized.

  In addition to this, according to the present invention, it is possible to understand which operator's business the idea is compatible with by grasping the output similarity for each operator. As a result, the user or the client can understand that there is a particular need in a business operator whose idea is highly similar. That is, the user or the client can understand that the idea should be sold to a business operator having a high degree of similarity.

It is a figure which shows the structural example of the problem-solving assistance system to which this invention is applied. It is a figure which shows the block structure of an electronic device. It is a figure which shows the consulting business in which the problem-solving support program to which this invention is applied is used. It is a flowchart of the processing operation of the problem solving support program to which the present invention is applied. It is a schematic diagram which shows the connection of the abstracted solution concept. It is another figure regarding the consulting business in which the problem-solving support program to which this invention is applied is used. It is a figure which shows the example which considers the acquired provider information in the step which searches for a search solution based on the basic basic information of seeds. It is a figure which shows the example which refers also to the basic information of seeds, when calculating a similarity. It is a figure which shows the example which inputs a constraint condition on the user side via an operation part. It is a schematic diagram which shows the relationship of the combination of the character string for a reference, and a solution concept. It is a figure which shows the example which considers to what extent the character string analyzed from the basic information respond | corresponds with the reference character string. It is a figure which shows the example which searches the structure of concrete invention based on the character string extracted from basic information, or the proposed solution concept.

  Hereinafter, a problem solving support system to which the present invention is applied will be described in detail with reference to the drawings.

  A problem solving support system 1 to which the present invention is applied is embodied by a configuration as shown in FIG. 1, for example. The problem solving support system 1 includes a mobile terminal 11 for a user who uses the system, and a server 13 connected to the mobile terminal 11 via a public communication network 12.

  The public communication network 12 is an Internet network or the like that connects the mobile terminals 11 and the server 13 via a communication line. Incidentally, when the portable terminal 11 is operated in a certain narrow area, the public communication network 12 may be configured by a LAN (Local Area Network). The public communication network 12 may be a so-called optical fiber communication network. The public communication network 12 is not limited to a wired communication network, and may be realized by a wireless communication network.

  The mobile terminal 11 is, for example, a mobile phone, a smartphone, a tablet terminal, a wearable terminal, a notebook personal computer (PC), or the like, and is a device that can communicate through the public communication network 12 based on at least a user operation. is there. The portable terminal 11 is a device that can be carried by the user at all times, but is not limited to this, and is a concept that includes all electronic devices such as a desktop PC. .

  The portable terminal 11 communicates via the public communication network 12 when installing package software sold at a store without downloading a problem solving support program to be described later via the public communication network 12. It may be a device that does not perform. In the following example, a case where a smartphone is applied to the mobile terminal 11 will be described as an example.

  FIG. 2 shows a specific configuration example of the mobile terminal 11. The portable terminal 11 includes a ROM (Read Only Memory) 22, a RAM (Random Access Memory) 23 as a work area used for storing and developing data, and a CPU (Central Processing) for controlling the entire portable terminal 11. Unit) 24, an operation unit 25 for inputting various control commands via operation buttons, a keyboard, and the like, an output I / F 16 for controlling display of various information, a hard disk, etc. A storage unit 27 for storing a program for performing a search to be performed, and a data input / output unit for inputting data into the portable terminal 11 from the outside or outputting data generated in the portable terminal 11 to the outside 29 are connected to the internal bus 21, respectively. Further, a communication I / F 28 and a voice input unit 31 are connected to the internal bus 21. The output I / F 16 is connected to a display unit 26 as a monitor that actually displays information.

  The ROM 22 stores a program for controlling hardware resources of the entire mobile terminal 11. The RAM 23 temporarily stores various commands for controlling the hardware resources of the entire mobile terminal 11.

  The CPU 24 is a so-called central processing unit for controlling each component mounted in the mobile terminal 11 by transmitting a control signal via the internal bus 21. Further, the CPU 24 transmits various control commands via the internal bus 21 in accordance with user operations via the operation unit 25.

  The operation unit 25 is embodied by a touch panel or the like, and information related to a problem that the user actually wants to solve is input, and an execution command for executing the problem solving support program is input from the user. When the execution command is input by the user, the operation unit 25 notifies the CPU 24 of this. Upon receiving this notification, the CPU 24 reads the program from the storage unit 27 and executes it.

  The output I / F 16 is configured by a graphic controller that creates a display image based on control by the CPU 24. The display unit 26 connected to the output I / F 16 is realized by, for example, a liquid crystal display (LCD).

  When the storage unit 27 is composed of a hard disk, based on control by the CPU 24, predetermined information is written to each address and read out as necessary. The storage unit 27 stores a problem solving support program for executing the present invention. This program is read by the CPU 24 and executed.

  The communication I / F 28 is mounted with a line control circuit for connecting to the public communication network 12, a signal conversion circuit for performing data communication with other terminal devices, and the like. The communication I / F 28 converts various commands from the internal bus 21 and sends them to the public communication network 12 side. When data is received from the public communication network 12, the communication I / F 28 performs predetermined conversion processing on the received data. To the internal bus 21 or the CPU 24.

  The data input / output unit 29 is connected to a cord or the like for USB connection with an electronic device such as a PC. Data can be input / output to / from an external device via the data input / output unit 29.

  The voice input unit 31 is a device for converting voice input from a user into electronic data.

  A predetermined database is constructed in the server 13. Information sent via the public communication network 12 is stored in this database. Further, the server 13 transmits the accumulated information to the mobile terminal 11 through the public communication network 12 based on a request from the mobile terminal 11.

  Note that any one or more components in the mobile terminal 11 or the server 13 may be controlled by artificial intelligence. The specific application method of artificial intelligence to the present invention may be based on any one or more of all known information related to artificial intelligence.

  The problem solving support system 1 to which the present invention is applied is executed via a problem solving support program installed in the mobile terminal 11. That is, the user operates the mobile terminal 11 and performs various problem solving through the problem solving support program installed therein. This problem solving support program is used as support software for a user to create innovation as an innovator himself as shown in FIG. The problem solving support program is not limited to the case where it is installed on the mobile terminal 11 and used. The problem solving support program is stored in the server 13 and accessed from the mobile terminal 11 each time the server 13 is used. Of course, you may do it.

  The innovation creation process starts when the user inputs information about a newly created creation.

  Examples of information entered by this user include social needs, problems, previously proposed prior art, issues to be solved, composition of newly created inventions, seeds of ideas, idea concepts, Actions and effects are all expressed in sentences, character strings, languages, etc. that can be converted into text data. Information input from the user in this way is hereinafter referred to as basic information.

  The user manually inputs the basic information through the operation unit 25 in the mobile terminal 11 or inputs the basic information by voice through the voice input unit 31. In this input, basic information created in another mobile terminal 11 or an electronic device such as a PC may be input from the data input / output unit 29. Further, text data created by the user in another mobile terminal 11 or an electronic device such as a PC may be transmitted via the public communication network 12 to the mobile terminal 11 in which the problem solving support program is actually installed.

  The basic information transmitted or input in this way is stored in the storage unit 27.

  After the basic information is input in this way, the problem solving support program actually executes the processing operation. The processing operation flow of this problem solving support program is shown in FIG.

  The problem solving support program analyzes the basic information input in step S11. (Step S12). For this analysis, any existing text mining technology, data mining technology, language analysis processing technology, or the like may be used.

  Next, this problem-solving support program extracts character strings from the basic information to be analyzed in any one or more units among all grammatical structural units such as words, morphemes, phrases, and clauses. For example, “For a patent specification analysis display device capable of counting and displaying the degree of limitation of the invention defined in the claims of the patent specification, the degree of limitation of the invention is displayed with higher accuracy. If there is text data such as “Purpose”, “Patent specification”, “Claims”, “Definition”, “Invention”, “Limitation degree”, “Count”, “Display”, Character strings such as “patent specification analysis display device”, “with high accuracy”, “target”, and the like are extracted.

  Alternatively, the basic information may be input as keywords or words in pieces. For example, if “pet pet wipe” is input, the character strings “pet” and “butt wipe” can be extracted. In addition to the concept and configuration of the invention, the basic information may include a problem to be solved. For example, when “cheap and easy to make” is entered, by analyzing this by text mining, the structure in grammar like “cheap”, “cheap”, “make”, “easy to make”, etc. Character strings are extracted from one unit over one or more units.

  Next, the problem solving support program moves to step S13, and starts searching for a solution concept highly related to the character string extracted in step S12. Before this search is performed, the mobile terminal 11 preliminarily associates a reference character string with an abstract solution concept (hereinafter referred to as a solution concept) that is classified into two or more types as shown in FIG. Get it.

  The solution concept is an abstracted concept for solving a problem. The solution concepts A1, A2, A3, B1, B2, B3, C1, C2, C3,... Are defined in advance on the system side. This solution concept is a concept that includes all known problem-solving methods such as equivalent transformation theory, TRIZ (including classical TRIZ as well as any advanced TRIZ), ARIZ, QFD, Taguchi method, etc. . Examples of this solution concept include, for example, the 40 principles of classical TRIZ, segmentation (subdivision), asymmetry, reverse (reverse), dynamics, feedback, nesting structure, preemption action, It is equivalent to isotropy, mechanical vibration, conversion of harm into profits (turning into disaster and making fortune).

  The portable terminal 11 acquires associations indicating the degree to which such character strings and solution concepts are related to each other. As a method of expressing this association, for example, a reference character string and a solution concept connected by an arrow as shown in FIG. 5 are linked to each other, and a reference character string and a solution concept that are not connected by an arrow are You may make it express in the form which is not mutually linked. For example, the solution concept A2 may be expressed in the form of being linked to the reference character strings c11 and a21 but not linked to other solution concepts. That is, in this case, the presence / absence of the association between the reference character string and the solution concept is digitally expressed by a binary value of true or false.

  An analog expression method may be adopted as a method for expressing other associations. For example, the solution concept B3 is associated with the reference character strings a21 and b21 at a rate of 80%, the reference character string c11 is 60%, the reference character string b11 is 45%, and the reference character string c21 is 24%, the reference character string a11 may be expressed as an association degree such as 0%. For example, as reference character strings, for “strength” and “weight”, segmentation (subdivision) may be expressed as a solution concept with an association degree of 80%. When the characteristic to be improved is “strength” and the characteristic to be deteriorated is “weight” in the principle of 40 inventions of classic TRIZ, segmentation (subdivision) has been conventionally used as a solution concept. This is because it has been advocated.

  When the reference character string is “wipe ass”, as a solution concept, the relevance of the “disposable” solution concept such as toilet paper may be set as high as 90%. Good.

  The portable terminal 11 stores the association between the reference character string and the solution concept in its storage unit 27 or the like before the analysis in step S13 so that it can be read at any time. At this time, if the association between the reference character string and the solution concept is not stored in its own storage unit 27, it is stored in the server 13, and this server 13 is accessed when actually executing step S13. You may make it perform by doing.

  After shifting to step S13, the problem solving support program performs an operation of selecting one or more solution concepts from the character string extracted from the basic information analyzed in step S12.

  Regarding the selection of the solution concept from the character string extracted from the basic information, the association between the reference character string acquired in advance and the solution concept may be referred to. For example, if the character string analyzed from the basic information is “strength”, if the link between the reference character string and the solution concept is referred to, the “strength” is highly related to segmentation (segmentation). ). For this reason, segmentation (subdivision) having high association with the analyzed character string “strength” is searched as a solution concept.

  In addition, when the character string analyzed from the basic information is “wipe body”, there is no exact reference character string, but when “wipe ass” exists as a reference character string, refer to this, As a solution concept, “disposable” may be searched and presented. In this way, even if the character string from the basic information and the reference character string do not completely match, as long as they partially match at the “wipe” as in this example, the reference character string is associated with the reference character string. You may make it search for a solution concept with high property.

  Furthermore, the character string analyzed from the basic information is “body wash”, and even if there is no reference character string that completely or partially matches this, There are similarities in semantic concepts. The similarity of the semantic concept may be set in advance on the system side, and a solution concept that is highly related to the reference character string having the high similarity may be searched.

  That is, the character string analyzed from the basic information is not only whether the reference character string and the character partially or completely match, but also the degree of similarity of the semantic concept, as well as the character string from the basic information. If the reference character string has some correspondence, a solution concept that is highly related to the reference character string may be searched.

  The above-described operation is performed not only for one character string analyzed from the basic information but also for a plurality of other character strings. As a result, not only one solution concept but also a plurality of solution concepts may be selected.

  The method for discriminating a solution concept having a higher association with the analyzed character string is not limited to the method described above. For example, the association degree may be set in advance between the reference character string and the solution concept. In such a case, for each solution concept, “segmentation (subdivision)” is 84%, “asymmetry” is 25%, and “reverse” is 61% of “strength” as a reference character string. The degree of association is set in advance between the reference character string and the solution concept, such as “dynamicity” of 77% and “feedback” of 43%. Then, when the reference character string “strength” is selected according to the character string analyzed from the basic information, it may be determined that the character string is related by the above-described% of the association degree. A solution concept having an association degree equal to or higher than a predetermined threshold may be selected.

  Note that the data on the association between the reference character string and the solution concept may be downloaded on the mobile terminal 11 side, or may be stored in the server 13 at all times, and the server may be used as necessary. 13 may be read out or downloaded to the portable terminal 11.

  That is, the problem solving support program can immediately select a solution concept corresponding to the character string obtained by analyzing the basic information and output it. The output of the solution concept may be displayed on the display unit 26 via the output I / F 16 or may be transmitted to the outside via the data input / output unit 29. The output of the solution concept may be stored in the server 13 from the public communication network 12 via the communication I / F 28, or may be transmitted to another portable terminal 11.

  The user uses the solution concept output in this way as a hint, and uses his creativity to create an invention. After the idea is born in this way, the operation phase shifts to that shown in FIG.

  The user analyzes the idea created in this way, understands it deeply from various viewpoints, and performs formalization of the created idea and the situation surrounding it. In this formalization work, in addition to the composition of the idea and the main concept, the social needs and problems behind the idea, the previously proposed prior art, the issues to be solved, the effects, etc. Are expressed by sentences or character strings that can be converted into text data. This formalized situation is hereinafter referred to as idea information. Incidentally, basic information may be applied as it is as the idea information.

  Next, the user inputs this idea information into the mobile terminal 11 in which the problem solving support program is actually installed (step S14). The idea information may be input by the user himself / herself directly inputting text data via the operation unit 25 or the voice input unit 31, or the text data of the idea information created in another mobile terminal 11 may be input as data. It may be input from the output unit 29. The text data of the idea information created by the user in another mobile terminal 11 may be transmitted via the public communication network 12 to the mobile terminal 11 in which the problem solving support program is actually installed.

  The text data of the idea information transmitted or input in this way is stored in the storage unit 27.

  The problem solving support program proceeds to step S15 and analyzes the text data of the idea information as shown in FIG. For this analysis, any existing text mining technology, data mining technology, language analysis processing technology, or the like may be used.

  Next, the problem solving support program extracts a character string from the analyzed text data in any one or more units among all grammatical structural units such as words, morphemes, phrases, and clauses. A specific method for extracting the character string is the same as in step S12.

  Next, the problem solving support program moves to step S16, and obtains text data relating to information of another business operator. The information on the other business here is patent information, business information, management information, business information, etc. of a company different from the client (hereinafter collectively referred to as business information). Such company information may be acquired from a website on which, for example, a patent publication is published, or may be acquired from a website on which information on the company is described. The business operator information may be acquired from text data described in an electronic book or an electronic magazine, or text data stored in a purchased recording medium. Further, the business operator information may be text data manually input by the user himself / herself or others, or may be obtained by any other method.

  The problem solving support program proceeds to step S17 and similarly analyzes text data using the text mining technique for the business operator information. For this analysis, any existing text mining technology, data mining technology, language analysis processing technology, or the like may be used. Also in step S17, the problem solving support program extracts a character string from the analyzed text data in any one or more units among all grammatical structural units such as words, morphemes, phrases, and clauses. A specific method for extracting the character string is the same as in step S12. This company information may be acquired and analyzed not only for one company but also for a plurality of companies.

  Next, the process proceeds to step S18, and the problem solving support program compares the character string of idea information and the character string of business operator information obtained in this way, and calculates the degree of similarity between them. This similarity is calculated by comparing the number of partially matching character strings, the number of completely matching character strings, and the partially matching dependency between the character string of idea information and the character string of business operator information. And the number of completely matching dependencies. At this time, a concept dictionary or the like may be referred to as necessary. In addition to this, it may be based on the similarity of semantic concepts existing behind character strings. It may be possible to freely change which item is weighted on the user side or the system side.

  The problem solving support program seeks the degree of similarity between the character string of idea information and the character string of business operator information. As a result, the similarity is calculated for each company, such as Company A: 27%, Company B: 74%, Company C: 58%, Company D: 40%,.

  The problem solving support program may display the obtained similarity calculation result on the display unit 26 via the output I / F 16 or store it in a USB memory or the like via the data input / output unit 29. It may be. The output of the solution concept may be stored in the server 13 from the public communication network 12 via the communication I / F 28, or may be transmitted to another portable terminal 11. In addition, the problem solving support program outputs not only the similarity calculation results, but also businesses with similarities that are above or below a predetermined threshold, and businesses from the top or bottom of the similarity to the predetermined rank. Also good.

  The user or the client can understand which operator's business suits the idea that has been devised by grasping the output similarity for each business operator. As a result, the user or the client can understand that the devised idea has a particular need in a business operator having a high degree of similarity. That is, the user or the client can understand that the idea that has been devised should be sold to a business operator having a high degree of similarity.

  On the other hand, as a matter of course, the user or the client may not only raise a business with a high degree of similarity but also arouse a new need to a business with a low degree of similarity. In such a case, although the sales strategy of the client is different, it is possible to take this similarity into consideration when considering which strategy to sell.

  The problem solving support program executes the above-described flow from step S15 to step S18 not only for the character string of the idea information of one idea that has been devised but also for the idea information of all other devised ideas. It will be. As a result, it is possible to obtain the degree of similarity with other companies for all idea information. As a result, the user or the client can examine not only the one idea information that has been devised, but also all the idea information that has been devised, the technology sales destination and the marketing strategy.

  The present invention is not limited to the above-described embodiment. Information on the calculated similarity may be fed back to the processing flow in step S13 to search for a further solution concept.

  For example, for a business operator whose similarity is lower than a predetermined threshold value or a business operator whose business level is higher than a predetermined threshold value, a character string obtained by analyzing the business operator information is extracted. This character string is compared with the reference character string, and the reference character string corresponding to this is specified. Then, based on the above-described step S13, a solution concept highly related to the identified reference character string is searched for and output. As a result, the user can search for a solution concept based on the provider information. In particular, since this business operator information may correspond to market needs, it is possible to search for a solution concept based on market needs.

  That is, according to the present invention, it is possible to search for a solution concept based on market needs. In other words, it is possible to support not only seeds-first innovation but also needs-first innovation. In this embodiment, the search for the solution concept via the reference character string may be performed according to any rule as long as it is based on the calculated similarity.

  Further, according to the present invention, both basic information and business operator information may be taken in and a solution concept may be searched. In such a case, the solution concept is searched based on the relevance via the reference character string in the same manner as described above. In particular, when both basic information and business operator information are taken in, it is possible to weight which information is weighted. If the basic information: company information is weighted at a ratio of 2: 1, the basic information is evaluated twice as much as the company information for the degree of association between the reference character string and the solution concept. Also good. As a result, it is possible to search for a solution concept that emphasizes more basic information.

  The association between the reference character string and the solution concept may be changed based on the calculated similarity. For example, when the percentage of businesses with a similarity equal to or greater than a predetermined value is relatively small, the one with the higher association between the two is lowered by -10 points, the one with the lower association between the two is raised by 10 points, etc. May be adjusted. If these linkages are expressed only by the true / false of the linkage, set true to false and set the combination with high selectivity among false in the conventional analysis. You may try again. By changing these settings, there is a high possibility that a different solution concept will be selected, and as a result, there is a high possibility that the user will create a different invention concept. There is a possibility that the degree of similarity becomes high. By performing such a setting change of association, an invention concept that has a high degree of similarity to the operator information is likely to appear.

  The association between the reference character string and the solution concept may be appropriately changed by considering not only the similarity but also the acquired business operator information itself. In such cases, for reference character strings that have a high degree of coincidence with the character strings extracted from the analyzed provider information, setting changes such as increasing the degree of association with the solution concept by several points or conversely decreasing the number of points You may make it do. Furthermore, returning to step S13, searching for a solution concept based on basic information increases the possibility of searching for a solution concept that better meets the needs of the market.

  In the example of FIG. 7, the acquired business operator information is taken into consideration at the stage of searching for the search solution based on the basic information of the initial seeds 41 before calculating the similarity with other business operators. In such a case, the degree of association with the solution concept may be adjusted for a reference character string having a high degree of coincidence with the character string extracted from the business operator information acquired in advance. Alternatively, a solution concept that is highly related to a reference character string having a high degree of coincidence with a character string extracted from acquired business operator information may be searched. Further, as described above, both basic information and business operator information may be taken in and a solution concept may be searched. In such a case, when both basic information and business operator information are captured, weighting as to which information is to be weighted may be performed as described above.

  Further, according to the present invention, when calculating the similarity in step S18, the basic information of the seeds 41 may be further referred to as shown in FIG. In such a case, between the character string obtained by analyzing the basic information and the character string of the operator information, the number of partially matching character strings, the number of completely matching character strings, The number of partially matching dependencies, the number of completely matching dependencies, or the similarity of the semantic concepts behind them are also reflected in the calculation of similarity. At this time, which of the similarity between the character string of the basic information and the character string of the business operator information and the similarity between the character string of the invention concept and the character string of the business operator information is prioritized or which is weighted? It can be set freely. At this time, it is also possible to extract the basic information that particularly mentions the solution problem and analyze it by text mining. Actually, in the basic information that the user has formalized, create a rule in advance in what column to describe the solution issue, search that column, and then describe the solution issue in the column as text data It will be extracted and analyzed.

  In addition, according to this invention, you may make it input which solution concept the user employ | adopted among the some solution concept output. When such solution concept adoption information is input, the problem solving support program may reflect the adoption information on the association between the reference character string and the solution concept. In other words, for the reference character string highly related to the adopted solution concept, the degree of association may be further increased by several points. Among the output solution concepts, the solution concepts that are not included in the selection information are concepts that are unlikely to be actually adopted by the user. May further reduce the relevance by several points.

  In the present invention, in step S13, the basic information may be extracted from the basic information, particularly any one of the problem to be solved, the solution means, and the action effect, and analyzed by text mining. Actually, in the basic information that is formalized by the user, in which column the problem to be solved, the solution, and the action and effect are described in advance, a rule is created in advance, and the problem in the column is searched after searching that column. Will be extracted as text data and analyzed. Then, a solution concept with a high degree of association may be searched for through a reference character string by using any one or more of these solution problems, solution means, and action effect analysis results. As a result, a reference character string specialized for any one or more of these solution problems, solution means, and operational effects is selected and a solution concept is searched.

  Further, at this time, as shown in FIG. 9, the constraint condition may be input via the operation unit 25 on the user side. This constraint condition places certain constraints on the solution concept to be selected, such as not selecting a solution concept that requires high cost, or not selecting a solution concept that consumes a large amount of energy. The problem solving support program defines the types of constraint conditions in advance, and arranges the solution concept in accordance with this. When a constraint condition is input from the user side, control is performed so that a solution concept under the input constraint condition is not selected. That is, according to the problem solving support program, the solution concept to be selected may be adjusted based on the input constraint condition.

  In the present invention, the search result of these search solutions, the calculation result of similarity with the business operator, and the like may be stored in the server 13. Each mobile terminal 11 accesses the server 13 in which past results are stored via the public communication network 12, thereby making it possible to refer to them.

  In the above-described embodiment, the description has been made on the assumption that the processes of steps S11 to S13 are performed on the mobile terminal 11 side, but the present invention is not limited to this, and may be performed on the server 13 side. However, any of the steps may be shared between the server 13 and the mobile terminal 11.

  Next, another embodiment of the problem solving support system 1 to which the present invention is applied will be described.

  In the example of FIG. 5, one or more reference character strings are referred to one reference character string, whereas in the example of FIG. 10, a plurality of reference character strings are connected. This refers to the relevance of each solution concept to the combination of.

  In FIG. 10, there are “dog”, “wipe off”, “polybag”, “seal”, “stick”, “cheap”, “easy to install”, etc. as reference character strings. The solution concepts A1, A2,. A solid line indicates the association, and a dotted line indicates the combination. For example, “dog” and “wiping the bottom” are connected to each other by a dotted line, and a solid line extends from there to A2 and C1. This indicates that A2 and C1 are highly related solution concepts for the combination of “dog” and “wiping butt”. In other words, if the reference character string is only “dog”, it is impossible to know what the dog wants to solve and what is the problem. On the other hand, combining `` dog '' and `` wipe ass '' will narrow down to some extent innovation for wiping the anus after the dog dung, and it is possible to narrow down the solution concept according to this It becomes. In addition to this, in the dotted line where “dog”, “wipe off the butt”, and “polybag” are combined, the solution concept of A2 and B2 is further linked to a highly related one. This means that a plastic bag is further added to the above-described dog wiping, and the solution concept for wiping the dog's buttocks using the plastic bag is further narrowed down.

  The reference character string combination described above is a noun-noun, but may be a noun-verb, such as a combination of “seal” and “paste”. By combining nouns and verbs, the proposition to be realized becomes clear like "stick a sticker". And B3 will link as a solution concept with high relevance to sticking this seal. In addition to this, if a reference character string “polybag” is further combined, the solution concept for sticking a seal to the polybag will be narrowed down. If the reference character string “cheap” is added, the solution concept for sticking the sticker on the plastic bag at a low cost will be narrowed down.

  By acquiring in advance the association of one or more solution concepts for each combination of reference character strings in the same manner as in FIG. 5 described above, the solution concept is selected from the character strings actually analyzed from the basic information. In this case, it becomes possible to refer to this. In particular, it is possible to further narrow down the intended solution concept by combining them with each other rather than the reference character string alone, and it is possible to effectively select and propose the solution concept that the user really desires. .

  In actuality, when referring to the association of one or more solution concepts for each combination of reference character strings, a plurality of character strings are extracted from the basic information. Then, a solution concept having a high association with a combination of a plurality of reference character strings corresponding to the extracted plurality of character strings is proposed. In such a case as well, as described above, the character string analyzed from the basic information is based on whether the reference character string and the character partially or completely match, not only the degree of similarity of the semantic concept but also the basic information. If the reference character string has a certain correspondence with the character string, a solution concept that is highly related to the reference character string may be searched.

  At this time, the combination between the reference character strings may be any combination of noun-verb, noun-adjective, adjective-verb, and noun-noun. When extracting a character string from basic information, a plurality of character strings composed of one or more combinations of noun-verb, noun-adjective, adjective-verb, and noun-noun as words or phrases are extracted, You may make it search for a solution concept, referring the combination of the same part of speech in the reference character string.

  When the server 13 is controlled by artificial intelligence, the association between the reference character string and the solution concept may be learned. In other words, the association between the reference character string and the solution concept as shown in FIG. 5 and the combination between the reference character string and the solution concept as shown in FIG. Go. The artificial intelligence learns based on information provided from the outside to the server 13 via the public communication network 12. The information provided from the outside to the server 13 may be transmitted from, for example, the mobile terminal 11 using this system. As a result of using the problem solving support program to which the present invention is applied by the mobile terminal 11, the relationship between the reference character string selected by the user and the solution concept, or the reference character string not selected by the user and the solution concept Past history information such as relationships is recorded on the mobile terminal 11 side. Then, the past history information is transmitted from the portable terminal 11 to the server 13. The artificial intelligence that controls the server 13 updates the association between the reference character string and the solution concept based on the transmitted past history information. That is, the relation between the reference character string selected by the user and the solution concept is updated with a high degree of association, and the relation between the reference character string not selected by the user and the solution concept is updated with a lower degree of association. For this update, a neural network or the like may be used.

  By collecting such past history information from all mobile terminals 11 using this system to the server 13, the association between the reference character string and the solution concept can be learned from time to time based on a large amount of data. This makes it easier for the user to accept and provides a solution concept that is the fastest way to solve.

  It goes without saying that the association between the reference character string and the solution concept in the server 13 may be learned by the artificial intelligence implemented on the mobile terminal 11 side.

  Incidentally, external data for learning by this artificial intelligence includes not only the past history information of the mobile terminal 11 using this system described above, but also all Internet information that can be acquired via the public communication network, You may use big data. In addition, by accessing patent information that can be obtained from the Patent Information Platform of the JPO and obtaining the relationship between the character string and the solution concept from there, the association between the reference character string and the solution concept can be learned through artificial intelligence. It may be updated.

  For example, if you search on the Internet for the two strings “dog” and “wipe ass”, you will find a website that contains various solutions for wiping the anus after the dog dung. come. By acquiring text information of the solution described on the homepage and text mining it, we will find out what solution concept is supported by artificial intelligence. In such an example, when a solution that indicates that dirt does not adhere to the finger by overlapping two layers of cloth is acquired as text information, this is analyzed by text mining, and the solution concept “ If you think that it is related to “stacking multiple layers”, two reference strings “dog” and “wipe ass” and the solution concept “stacking multiple layers” Update to strengthen the linkage with “Yes”.

  According to the present invention, the correspondence between the character string analyzed from the basic information and the reference character string may be learned by artificial intelligence. This learning by artificial intelligence may be executed on either the mobile terminal 11 side or the server 13 side.

  For example, as shown in FIG. 11, when considering to what extent the character string analyzed from the basic information corresponds to the reference character string “wipe the bottom”, first, the character string “wipe the tail” is the reference character string “ It corresponds almost 100% to “wipe ass”. On the other hand, the character string “Body wipe” is 70%, the character string “Body wash” is 50%, the character string “Brushing” is 35%, and the character string “ “Feeding” may be grasped through a numerical value such as a percentage such as 5%. Based on information provided from the outside, the numerical value of the correspondence relationship may be changed, or the relationship between the new character string and the reference character string may be defined. For example, when the co-occurrence of “wipe body” and “wipe off the bottom” from information acquired from the Internet or from a document read from the outside (probability of applying for both within one homepage and within one document) is high May be configured to increase the percentage value of the correspondence relationship described above and to lower the percentage value of the correspondence relationship described above when the co-occurrence degree is low.

  The correspondence between the character string analyzed from the basic information and the reference character string is the information obtained from the Internet regarding the degree of similarity of the semantic concept as well as whether or not the characters partially or completely match. Alternatively, it may be learned by artificial intelligence from a document read from outside. For example, “wipe ass” and “feces” do not match in terms of words, but if there is a high probability of filing both within one homepage and within one document, the semantic concepts are similar and new May be registered as a word corresponding to the reference character string “wipe the bottom”.

  Further, according to the present invention, a process for prompting the user to input basic information may be introduced. The promotion of the input of the basic information may be performed according to the character string extracted by mining the basic information or the search result of the solution concept in step S13.

  For example, if the character string extracted from the basic information is simply “wipe ass” or “cheap”, the solution concept can be narrowed down without specifying what the wiping is for people, dogs, etc. There may not be. In such a case, if there is no other character string that is considered to be the target of wiping as a result of mining the basic information, the user is prompted to input further basic information in order to identify the target. May be.

  In addition, if “dog”, “wipe ass”, “polybag”, and “paste” can be extracted from the basic information, it is wiped ass for dogs and can be attached to plastic bags. Can be read. In particular, when narrowing down a solution concept having a high association with a combination of a plurality of reference character strings as shown in FIG. In this case, as a result of mining the basic information, if there is no other character string that can be considered as a solution problem, the input of further basic information may be prompted in order to identify the target. . For the determination of the presence or absence of a character string corresponding to the solution problem, for example, for each solution problem group such as “cheap”, “manufacturability”, “general versatility”, character strings indicating these are registered in advance, It may be determined whether there is a character string in the basic information that matches all or part of the registered character string.

  In addition, as a result of searching for the solution concept in step S13, when the proposed solution concept is not selected by the user, or when trying to propose a solution concept, the number exceeds the predetermined upper limit, and it is difficult to narrow down the number. In some cases, the user may be prompted to provide more detailed information.

  In the present invention, these determinations may be executed via artificial intelligence. This input promotion may be realized by displaying through the display unit 26 or may be performed by voice through a voice output unit (not shown).

  Furthermore, according to the present invention, a specific configuration of the invention may be searched and displayed based on a character string extracted from basic information or a proposed solution concept. Alternatively, a specific configuration of the invention may be searched and displayed based on both the character string extracted from the basic information and the proposed solution concept. In any case, these operations are performed through artificial intelligence.

  In such a case, the extracted character strings are “dog”, “wipe ass”, “fingertips”, “seal”, “polybag”, “efficiency of feces”, and the solution concept is “fitness” In the case of “improvement of”, it is possible to derive immediately by simply connecting the character strings until the plastic bag is pasted in a seal form when wiping the dog's bottom. In such a case, as shown in FIG. 12 (a), the artificial intelligence combines the material of the image on the Internet until the stick-shaped dog wipe 70 is attached to the plastic bag 7. Can be easily drawn.

  Artificial intelligence then reads the character strings “fingertip” and “efficiency of feces” and the solution concept of “improvement of fit”, and adds further configuration to the wiping body 70. . As shown in FIG. 12 (b), grooves 76, 77, and 78 that fit the fingertip are provided from the fingertip and fit, and for the right hand, the index finger is in the groove 78, the middle finger is in the groove 77, and the ring finger is in the groove 76. Artificial intelligence itself thinks that the efficiency of the dog's excretion is improved by fitting and fitting. Artificial intelligence extracts information from the word fit, for example from the Internet, and finds that there is an encircling body that surrounds the object in order to realize fit, and this encircling body is only for fingers I can find it. And it can be extracted as a well-known technique from the Internet or the like that a seal body may be formed in a groove shape to surround the finger.

  In this way, the finally completed configuration shown in FIG. 12B is displayed on the display unit 26. When the user understands the displayed form, the concept can be summarized and commercialized.

1 Problem Solving Support System 7 Plastic Bag 11 Mobile Terminal 12 Public Communication Network 13 Server 21 Internal Bus 22 ROM
23 RAM
24 CPU
25 Operation unit 26 Display unit 27 Storage unit 29 Data input / output unit 31 Voice input unit 41 Seeds

Claims (17)

A mining means for extracting a character string from information on a newly artificially created creation obtained by voice input or manual input;
Reference character strings and solution concepts corresponding to the character strings extracted by the mining means by referring to three or more degrees of association between each reference character string acquired in advance and each solution concept classified into two or more types And a search means for searching for one or more solution concepts based on three or more levels of association . A mining means for extracting a plurality of character strings from information on a newly artificially created creation obtained by voice input or manual input;
Referencing three or more levels of association with each solution concept for a combination between a plurality of reference character strings acquired in advance, and between a plurality of reference character strings corresponding to the plurality of character strings extracted by the mining means A problem-solving support system comprising search means for searching for one or more solution concepts based on three or more levels of association with each solution concept for the combination. The problem solving support system according to claim 1, wherein the mining means and the search means are provided in a portable information terminal. The mining means extracts a plurality of character strings composed of one or more combinations of noun-verb, noun-adjective, adjective-verb, and noun-noun as words or phrases,
The search means includes three or more stages of each solution concept for a combination between a plurality of reference character strings composed of one or more combinations of noun-verb, noun-adjective, adjective-verb, and noun-noun . 4. The problem solving support system according to claim 2, wherein the degree of association is referred to. The problem solving support system according to any one of claims 1 to 4, wherein the mining means and / or the search means are controlled by artificial intelligence. A server capable of wireless communication with the portable information terminal via a communication network;
The problem solving support system according to claim 3, wherein the server records the association degree to be referred to and transmits the association degree to the portable information terminal. Said server is controlled by artificial intelligence, characterized in that on the basis of the information provided from the outside, it acquires the relationship between the character string and solution concept, which is trained to reflect the association degree should see above The problem solving support system according to claim 6. The problem solving support system according to claim 6 or 7, wherein the server learns a correspondence relationship between a character string controlled by artificial intelligence and extracted by the mining means and the reference character string. The search means is controlled by artificial intelligence, and historical history information related to the relationship between the reference character string selected by the user and the solution concept is provided from the outside, and learning is performed to reflect this in the relevance to be referred to. problem solving support system according to any one of claims 1 to 5, characterized in that. The search means is controlled by artificial intelligence, and learns a correspondence relationship between the character string extracted by the mining means and the reference character string. The problem solving support system described. The search means is controlled by artificial intelligence, and searches for the configuration of the invention based on the character string extracted by the mining means and / or the searched solution concept, and displays it. Or the problem-solving support system according to item 2. The apparatus further comprises input promoting means for prompting a user to input information related to creation according to a character string extracted by the mining means or a search result of a solution concept by the search means. The problem solving support system according to any one of 1 to 11. The problem solving support system according to claim 12, wherein the input promoting means is controlled by artificial intelligence. A mining step of extracting a character string by a problem solving support system from information on a newly artificially created creation obtained by voice input or manual input;
A reference character string and a solution concept corresponding to the character string extracted in the mining step, with reference to three or more levels of association between each reference character string acquired in advance and each solution concept classified into two or more types And a search step for searching for one or more solution concepts by a problem solution support system based on three or more levels of association . A mining step of extracting a plurality of character strings from the information on a newly created artificially created product obtained by voice input or manual input by a problem solving support system ;
A combination between a plurality of reference character strings corresponding to a plurality of character strings extracted in the mining step with reference to three or more levels of association with each solution concept for a combination between a plurality of reference character strings acquired in advance And a search step for searching for one or more solution concepts by a problem solution support system based on three or more levels of association with each solution concept. A mining step of extracting a character string from information on a newly artificially created creation obtained by voice input or manual input;
A reference character string and a solution concept corresponding to the character string extracted in the mining step, with reference to three or more levels of association between each reference character string acquired in advance and each solution concept classified into two or more types A problem-solving support program that causes a computer to execute a search step for searching for one or more solution concepts based on three or more levels of association . A mining step of extracting a plurality of character strings from information on a newly artificially created creation obtained by voice input or manual input;
A combination between a plurality of reference character strings corresponding to a plurality of character strings extracted in the mining step with reference to three or more levels of association with each solution concept for a combination between a plurality of reference character strings acquired in advance A problem-solving support program that causes a computer to execute a search step for searching for one or more solution concepts based on three or more levels of association with each solution concept.

Images