Information processing device, information processing method, and program

Abstract

This information processing device is provided with an identification means that identifies one or a plurality of technical features of a target technology, and an output means that outputs information about a target issue, which is an issue obtained by searching a reference data group on the basis of at least one of the one or a plurality of technical features identified by the identification means and is related to the at least one technical feature.

Description

Information processing device, information processing method, and program

[0001] The present disclosure relates to an information processing device, an information processing method, and a program.

[0002] There are known technologies that support the formulation of business strategies that leverage the strengths of a target company. For example, Patent Literature 1 discloses a technology that compares the company's own resource information with that of competitors for a given product and calculates information on the company's superiority.

[0003] Japanese Patent Application Publication No. 2004-302694

[0004] The technology described in Patent Document 1 registers business opportunity definition information for each product, compares the company's own resource information and competitors' resource information for a specific product extracted from the registered products, and calculates information regarding the company's superiority.

[0005] On the other hand, there is also the possibility that the technology of the target company can be effectively applied to a product market that was not anticipated in advance. In this regard, the technology described in Patent Document 1 has a problem in that, although it is possible to output information about products that the target company has already manufactured or is already aware of, it is not possible to output information about products that the target company has not anticipated in advance.

[0006] The present disclosure has been made in consideration of the above-mentioned problems, and one exemplary purpose thereof is to provide a technology that can output issues related to a target technology, regardless of whether the target technology has already been applied to a product.

[0007] An information processing device according to an exemplary aspect of the present disclosure includes an identification means for identifying one or more technical features possessed by a target technology, and an output means for outputting information relating to a target problem, which is a problem obtained by searching a reference data group based on at least one of the one or more technical features identified by the identification means, and which is related to at least one of the technical features.

[0008] An information processing method according to an exemplary aspect of the present disclosure includes a computer identifying one or more technical features possessed by a target technology, and outputting information relating to problems related to at least one of the identified one or more technical features, the problems being obtained by searching a reference data group based on at least one of the identified one or more technical features.

[0009] A program according to an exemplary aspect of the present disclosure causes a computer to perform a process of identifying one or more technical features possessed by a target technology, and a process of outputting information regarding issues related to at least one of the identified one or more technical features, which issues are obtained by searching a reference data group based on at least one of the identified one or more technical features.

[0010] According to one exemplary aspect of the present disclosure, an exemplary effect is achieved in that a technology can be provided that outputs issues related to a target technology, regardless of whether the target technology has already been applied to a product.

[0011] FIG. 1 is a block diagram showing a configuration of an information processing device according to the present disclosure. FIG. 2 is a flow diagram showing a flow of an information processing method according to the present disclosure. FIG. 3 is a block diagram showing a configuration of an information processing device according to the present disclosure. FIG. 4 is a flow diagram showing a flow of an information processing method according to the present disclosure. FIG. 5 is a diagram for explaining an information processing method according to the present disclosure. FIG. 6 is a diagram showing an example of information output by an information processing device according to the present disclosure. FIG. 7 is a diagram showing an example of information output by an information processing device according to the present disclosure. FIG. 8 is a diagram showing an example of information output by an information processing device according to the present disclosure. FIG. 9 is a diagram showing an example of information output by an information processing device according to the present disclosure. FIG. 10 is a block diagram showing an example of information output by an information processing device according to the present disclosure.

[0012] The following are examples of embodiments of the present invention. However, the present invention is not limited to the exemplary embodiments shown below, and various modifications are possible within the scope of the claims. For example, embodiments obtained by appropriately combining the technical means employed in the exemplary embodiments shown below may also be included in the scope of the present invention. Furthermore, embodiments obtained by appropriately omitting some of the technical means employed in the exemplary embodiments shown below may also be included in the scope of the present invention. Furthermore, the effects mentioned in the exemplary embodiments shown below are examples of effects expected in the exemplary embodiments, and do not define the scope of the present invention. In other words, embodiments that do not exhibit the effects mentioned in the exemplary embodiments shown below may also be included in the scope of the present invention.

[0013] [First Exemplary Embodiment] A first exemplary embodiment, which is an example of an embodiment of the present invention, will be described in detail with reference to the drawings. This exemplary embodiment is a basic form for each of the exemplary embodiments described below. Note that the scope of application of each technical means employed in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technical means employed in this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical obstacles arise. Furthermore, each technical means shown in the drawings referenced to explain this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical obstacles arise.

[0014] (Overview of Information Processing Device 1) First, an overview of the information processing device 1 according to this exemplary embodiment will be described. As an example, the information processing device 1 identifies one or more technical features of a target technology owned by a target company, and outputs information regarding issues related to at least one of the one or more technical features. Here, the information regarding the issues may also include information regarding issues of products to which the target technology owned by the target company has not yet been applied. In other words, the information regarding the issues may also include issues related to application fields (applied products) that the target company has not anticipated, even though the target technology owned by the target company is applicable.

[0015] The information processing device 1 configured as described above can provide a technology that outputs problems related to a target technology, regardless of whether the target technology has already been applied to a product. More specifically, even for products that the target company does not manufacture or do not consider, it can output problems that can be solved by the target technology owned by the target company, thereby providing information that is useful for the business strategy of the target company.

[0016] (Configuration of information processing device 1) Next, the configuration of the information processing device 1 according to this exemplary embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the configuration of the information processing device 1. As shown in Fig. 1, the information processing device 1 includes an identification unit 11 and an output unit 12.

[0017] (Identification unit 11) The identification unit 11 identifies one or more technical features possessed by the target technology. As an example, the identification unit 11 refers to target data TD related to the target technology and identifies one or more technical features indicated in the target data TD. As an example, the identification unit 11 may: determine whether or not a predetermined keyword is included in the target data TD, and if the keyword is included, identify a technical feature associated with the keyword as a technical feature possessed by the target technology.

[0018] As another example, the identification unit 11 may: input target data related to the target technology into a language model that has been trained in advance to extract one or more technical features of the target technology from the target data TD related to the target technology; and identify the technical features of the target technology by referring to the output data from the language model.

[0019] Note that specific examples of target data TD related to the target technology do not limit this exemplary embodiment, but as an example, the target data TD may include data in any format, such as technical specifications, technical reports, papers, and various reports related to the target technology.

[0020] (Output unit 12) The output unit 12 outputs information regarding a target problem, which is a problem obtained by searching the reference data group RD based on at least one or more technical features identified by the identification unit 11, and which is a problem related to at least one of the technical features.

[0021] Here, the reference data group RD includes, as an example, various public information that can be acquired via a communication line, etc. Specific examples of the reference data group RD do not limit the present exemplary embodiment, but may include, as examples: Various documents issued by the government or public agencies Writings created by various industry associations Writings created by mass media Writings uploaded to SNS (social networking services) Writings created by research companies, etc.

[0022] As an example, the reference data group RD described above includes text data that explicitly or implicitly expresses a problem, and the output unit 12 can be configured to acquire the target problem by comparing a phrase representing one or more technical features identified by the identification unit 11, or a phrase obtained by expanding the phrase, with the text data included in the target data group RD.

[0023] Here, examples of "text data explicitly expressing a problem" include: Text data containing direct language or expressions related to the problem. Examples of "text data implicitly expressing a problem" include: Text data that does not contain direct language or expressions related to the problem but contains language that alludes to the problem or metaphors related to the problem. Data that does not contain direct language or expressions related to the problem but can identify the problem by referencing it in combination with other text data or information. Furthermore, the above-mentioned problem refers to a problem that is desirable to overcome in a certain product or technical field, such as "water bottles are easily broken" or "customer data is difficult to view." However, these examples do not limit the present exemplary embodiment.

[0024] The output unit 12 may also be configured to acquire the target problem obtained by performing a search on technical fields that have some of the multiple technical features identified by the identification unit 11 but do not have other technical features. For example, if the technical features identified by the identification unit 11 are feature A "heat retention," feature B "vacuum," and feature C "durability," the output unit 12 may be configured to acquire (identify) the target problem by performing a search on technical fields that have feature A "heat retention" and feature B "vacuum," but do not have feature C "durability."

[0025] (Effects of information processing device 1) As described above, the information processing device 1 is configured to identify one or more technical features possessed by the target technology, and output information about a target problem that is obtained by searching a reference data group based on at least one of the identified one or more technical features, and that is a problem related to at least one of the identified technical features.

[0026] According to the information processing device 1 configured as described above, it is possible to output issues related to a target technology, regardless of whether the target technology has already been applied to a product.

[0027] (Flow of Information Processing Method S1) Next, the flow of information processing method S1 according to this exemplary embodiment will be described with reference to Fig. 2. Fig. 2 is a flow diagram showing the flow of information processing method S1. As shown in Fig. 2, information processing method S1 includes a specification process (step) S11 and an output process (step) S12.

[0028] (Step S11) In step S11, the identifying unit 11 identifies one or more technical features of the target technology. The specific processing by the identifying unit 11 has been described above, and therefore will not be described here.

[0029] (Step S12) In step S12, the output unit 12 outputs information about a target problem that is obtained by searching the reference data group RD based on at least one of the one or more technical features identified in step S11 and is a problem related to at least one of the technical features. The specific processing by the output unit 12 has been described above, so a description thereof will be omitted here.

[0030] (Effects of information processing method S1) As described above, information processing method S1 employs a configuration that identifies one or more technical features possessed by the target technology, and outputs information relating to a target problem, which is a problem obtained by searching a reference data group based on at least one of the identified one or more technical features, and which is related to at least one of the identified technical features.

[0031] According to the information processing method S1 configured as described above, it is possible to output problems related to the target technology, regardless of whether the target technology has already been applied to a product.

[0032] Second Exemplary Embodiment A second exemplary embodiment, which is an example of an embodiment of the present invention, will be described in detail with reference to the drawings. Components having the same functions as those described in the above exemplary embodiment will be denoted by the same reference numerals, and their description will be omitted as appropriate. The scope of application of each technical means employed in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technical means employed in this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical hindrance occurs. Furthermore, each technical means shown in each drawing referenced to describe this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical hindrance occurs.

[0033] (Configuration of Information Processing Device 1A) The configuration of the information processing device 1A according to this exemplary embodiment will be described with reference to Fig. 3. Fig. 3 is a block diagram showing the configuration of the information processing device 1A. As shown in Fig. 3, the information processing device 1A includes a control unit 10, a storage unit 20, a communication unit 30, and an input / output unit 40.

[0034] (Communication Unit 30) The communication unit 30 communicates with devices external to the information processing device 1A. As an example, the communication unit 30 communicates with one or more servers (servers 51, 52, 53, ... in FIG. 3 ) connected to the information processing device 1A via a network N. The communication unit 30 transmits data supplied from the control unit 10 to the outside, and supplies data received from the servers 51, 52, 53, ... to the control unit 10. Note that the specific configuration of the network N does not limit the present exemplary embodiment, and examples include a wireless local area network (LAN), a wired LAN, a wide area network (WAN), a public line network, a mobile data communication network, or a combination of these networks.

[0035] (Input / Output Unit 40) The input / output unit 40 is configured to include at least one of input / output devices such as a keyboard, a mouse, a display, a printer, and a touch panel. Alternatively, the input / output unit 40 may be configured to be connected to input / output devices such as a keyboard, a mouse, a display, a printer, and a touch panel. In this configuration, the input / output unit 40 accepts various types of information input to the information processing device 1A from the connected input devices. Furthermore, the input / output unit 40 outputs various types of information to connected output devices under the control of the control unit 10. An example of the input / output unit 40 is an interface such as a USB (Universal Serial Bus).

[0036] (Storage Unit 20) The storage unit 20 stores various types of data referenced by the control unit 10 and various types of data generated by the control unit 10. As an example, the storage unit 20 stores the following: target data TD, technical features TF, words WD, extended words EWD, issue information PI, market information MI, and language model LM.

[0037] Here, the target data TD is data that is referenced by the identification unit 11 (described later) in order to identify one or more technical features of the target technology. As an example, as described in the exemplary embodiment 1, the target data TD may include data in any format, such as technical specifications, technical reports, papers, and various reports related to the target technology.

[0038] The technical feature TF is a technical feature identified by the identification unit 11 with reference to the target data TD. In this exemplary embodiment, the technical feature TF may be one or more.

[0039] The term WD is one or more terms expressing one or more technical features identified by the identification unit 11. As an example, the term WD is a term extracted by the identification unit 11 from the target data TD and used to identify the technical feature. As another example, the term WD may be a term not included in the target data TD but associated by the identification unit 11 with the identified one or more technical features.

[0040] The expanded phrase EWD is a phrase obtained by expanding the above-mentioned phrase WD by the expansion unit 14, which will be described later. The expanded phrase EWD includes, for example, at least one of synonyms, similar words, hypernyms, hyponyms, phrases expressing effects, and phrases expressing functions of the phrase WD. The expansion process by the expansion unit 14 will be described later.

[0041] The problem information PI is information indicating a problem obtained by the search unit 15 searching the reference data group RD based on at least one or more technical features identified by the identification unit 11, which will be described later. The problem information PI is also information indicating a problem related to at least one of the technical features. The search process by the search unit 15 and specific examples of problem information will be described later. In this exemplary embodiment, the "problem" may be expressed as an "unmet need," but this term does not limit this exemplary embodiment.

[0042] The market information MI is information relating to the size of one or more markets related to the issue information PI. As an example, the market information MI is acquired by the acquisition unit 13 that executes an acquisition process with reference to the issue information PI. Specific examples of the market information MI will be described later.

[0043] The language model LM is, for example, a language model that has been trained in advance (by machine learning) to reference input data including a directive and output output data including a response to the directive. The storage unit 20 stores, for example, a plurality of parameters that define the language model LM. These parameters are, for example, parameters trained in advance by the machine learning (parameters that have undergone an update process by machine learning), but this does not limit the present exemplary embodiment. Note that the language model may be a language model executed in another information processing device that is external to the information processing device 1A. In this configuration, the language model LM does not need to be stored in the storage unit 20. The information processing device 1A transmits input data to the language model via the communication unit 30 and receives output data from the language model via the communication unit 30.

[0044] (Control Unit 10) As shown in FIG. 3, the control unit 10 includes an acquisition unit 13, an expansion unit 14, and a search unit 15 in addition to the identification unit 11 and output unit 12 included in the information processing device 1.

[0045] (Acquisition unit 13) The acquisition unit 13 acquires various data referenced by each unit included in the control unit 10. As an example, the acquisition unit 13 acquires target data TD and provides the acquired target data TD to the identification unit 11. The acquisition unit 13 also acquires selection information indicating a selection made by a user who viewed a report RP (described later) from the input / output unit 40 and provides the acquired selection information to each unit included in the control unit 10.

[0046] The acquisition unit 13 may also be configured to acquire information (market information MI) about one or more markets related to the issue indicated by the issue information PI identified by the search unit 15 described below, and provide the acquired market information to each unit included in the control unit 10. Here, the acquisition unit 13 may be configured to acquire market information MI including information about the size of one or more markets related to the issue indicated by the issue information PI.

[0047] (Identification Unit 11) As described in Exemplary Embodiment 1, the identification unit 11 identifies one or more technical features TF possessed by the target technology. As an example, the identification unit 11 refers to target data TD related to the target technology, and identifies one or more technical features TF indicated in the target data TD. As an example, the identification unit 11 may: determine whether or not a predetermined keyword is included in the target data TD, and if the keyword is included, identify a technical feature associated with the keyword as a technical feature TF possessed by the target technology.

[0048] As another example, the identification unit 11 may: input target data related to the target technology into a language model that has been trained in advance to extract one or more technical features of the target technology from the target data TD related to the target technology; and identify the technical features TF of the target technology by referring to the output data from the language model.

[0049] Note that specific examples of target data TD related to the target technology do not limit this exemplary embodiment, but as an example, the target data TD may include data in any format, such as technical specifications, technical reports, papers, and various reports related to the target technology.

[0050] Furthermore, the identification unit 11 identifies one or more terms WD that express one or more technical features TF identified by the identification unit 11, and stores the identified terms WD in the storage unit 20. As an example, the terms WD are terms extracted by the identification unit 11 from the target data TD and used to identify the technical features TF. As another example, the terms WD may be terms that are not included in the target data TD and that the identification unit 11 associates with the identified one or more technical features TF.

[0051] (Expansion Unit 14) The expansion unit 14 generates expanded terms (also referred to as expanded terms) EWD by expanding the terms WD representing one or more technical features identified by the identification unit 11. As an example, the expansion unit 14 may acquire at least one of synonyms, similar words, hypernyms, hyponyms, terms expressing effects, and terms expressing functions of the above-mentioned terms WD, and use the acquired terms as the expanded terms EWD. For example, the expansion unit 14 may: generate "sound insulation," "soundproof," "insensible to hear," etc. as expanded terms EWD for the term WD "vacuum"; generate "heat insulation," "heat shielding," etc. as expanded terms EWD for the term WD "cold insulation"; and generate "unbreakable," "long-lasting," "unbreakable," etc. as expanded terms EWD for the term WD "durability." However, these specific examples do not limit the present exemplary embodiment. The above-described language model LM may be used in the word expansion process by the expansion unit 14. In this case, the expansion unit 14 may be configured to: generate input data including a word WD and a directive to output synonyms, similar words, hypernyms, hyponyms, words expressing effects, and words expressing functions of the word WD, and acquire an expanded word EWD by referring to output data output by the language model LM to which the generated input data has been input.

[0052] (Search unit 15) The search unit 15 executes a search process to search the reference data group RD based on at least one of the one or more technical features TF identified by the identification unit 11, and acquires, as a result of the search process, problem information PI indicating problems related to at least one of the technical features TF. Here, the search process may use a term WD representing one or more technical features TF identified by the identification unit 13, or may use an extended term EWD obtained by expanding the term WD.

[0053] Although a specific example of the search process by the search unit 15 does not limit this exemplary embodiment, as an example, the reference data group RD may include text data that explicitly or implicitly expresses a problem, and the search unit 15 may acquire the problem information PI by comparing a phrase WD that represents one or more technical features TF identified by the identification unit 11, or an extended phrase EWD obtained by expanding the phrase WD, with the text data included in the reference data group RD.

[0054] As another example, the identification unit 11 may identify multiple technical features TF possessed by the target technology, and the search unit 15 may acquire the problem information PI by searching for technical fields that have some technical features (e.g., TF1 and TF2) but not other technical features (e.g., TF3) among the multiple technical features (e.g., TF1, TF2, and TF3) identified by the identification unit 11. For example, if the technical features TF identified by the identification unit 11 are feature A "heat retention," feature B "vacuum," and feature C "durability," the output unit 12 may acquire (identify) the problem information PI by searching for technical fields that have feature A "heat retention" and feature B "vacuum," but do not have feature C "durability."

[0055] Furthermore, the identification unit 11 may be configured to acquire the problem information PI by using a language model LM. As an example, the identification unit 11 may be configured to: input input data including search conditions (search processing conditions) expressed using phrases WD representing one or more technical features TF identified by the identification unit 11, or extended phrases EWD obtained by expanding the phrases WD, into the language model LM; and identify (acquire) problem information PI indicating problems related to at least any of the technical features TF, with reference to output data output by the language model LM.

[0056] Here, the search conditions may be conditions optimized by the language model or another trained machine learning model. As an example, the language model or the machine learning model may be trained in advance using training data including pairs of search conditions and correct labels associated with the search conditions. In other words, the search unit 15 may be configured to optimize the search processing conditions based on a pre-trained machine learning model.

[0057] The search unit 15 may also be configured to: search the reference data group RD using a term indicating the problem indicated by the problem information PI or an expanded term obtained by expanding the term by the expansion unit 14, and acquire, as a result of the search, information on the size of one or more markets related to the problem indicated by the problem information PI via the acquisition unit 13. The search unit 15 may then be configured to generate a report RP including the problem indicated by the problem information PI and information on the size of the markets.

[0058] Furthermore, the search unit 15 may be configured to: cluster, for each of the multiple expanded phrases EWD, data included in the reference data RD that is related to or matches the expanded phrase; identify whether the relationship or match between the expanded phrase and the data is a positive relationship or match or a negative relationship or match; and generate display data that includes the expanded phrase and at least a portion of the data in a manner that enables identification of whether the relationship or match is a positive relationship or match or a negative relationship or match. Furthermore, the display data may be included in a report RP, which will be described later.

[0059] Here, a positive match refers to a relationship that is positively associated with the phrase, such as, for example, text data for the phrase "durability" or an expanded phrase, "I like this water bottle because it's durable." A negative match refers to a relationship that is negatively associated with the phrase, such as, for example, text data for the phrase "durability" or an expanded phrase, "I don't like this water bottle because it's fragile." However, these examples do not limit the present exemplary embodiment. Note that the output unit 12 may be configured to perform some or all of the processes performed by the expansion unit 14 and the search unit 15 described above.

[0060] (Output Unit 12) The output unit 12 outputs the report RP generated by the search unit 15. Here, the report includes: - problem information PI related to a problem obtained by searching the reference data group RD based on at least one or more technical features TF identified by the identification unit 11, and related to at least one of the technical features TF; - information related to the size of one or more markets related to the problem indicated by the problem information PI. Specific examples of the report RP generated by the search unit 15 and output by the output unit 12 will be described later.

[0061] (Processing Flow by Information Processing Device 1A) Next, the processing flow by information processing device 1A will be described with reference to Fig. 4. Fig. 4 is a flow diagram showing the flow of an information processing method S1 executed by information processing device 1A.

[0062] (Step S101) First, in step S101, the acquisition unit 13 acquires target data TD. As an example, the acquisition unit 13 acquires the target data TD from an external device via the communication unit 30. Examples of the target data TD have been described above, so further description will be omitted here.

[0063] (Step S11) Subsequently, in step S11, the identification unit 11 refers to the target data TD related to the target technology acquired in step S101, and identifies one or more technical features TF indicated in the target data TD. The identification unit 11 also identifies a phrase WD expressing the one or more technical features TF. The specific processing by the identification unit 11 has been described above, and therefore a description thereof will be omitted here.

[0064] (Step S102) Subsequently, in step S102, the expanding unit 14 generates expanded phrases EWD (also referred to as expanded phrases) by expanding the phrases WD representing one or more technical features TF identified by the identifying unit 11 in step S11. The specific processing by the expanding unit 14 has been described above, and therefore will not be described here.

[0065] (Step S103) Subsequently, in step S103, the search unit 15 executes a search process to search the reference data group RD based on at least one of the one or more technical features TF identified by the identification unit 11, and acquires, as a result of the search process, problem information PI indicating a problem related to at least one of the technical features TF. The process by the search unit 15 has been described above, but here, an example of the process by the search unit 15 will be described with reference to FIG. 5 .

[0066] 5 is a diagram schematically illustrating a processing flow by the information processing device 1A. As illustrated in FIG. 5, expanded terms EWD representing technical features TF are acquired through the processing of steps S101, S11, and S102. The search unit 15 executes the search process by comparing the expanded terms EWD with the reference data RD.

[0067] As shown in FIG. 5, the reference data RD includes, for example, multiple data groups (data groups 1 to 9 in FIG. 5), and the search unit 15 can be configured to generate categorized reference data CRD by categorizing the data included in these data groups into multiple categories prior to the search process. The search unit 15 can then perform the search process by comparing the reference data CRD for each category with the expanded terms EWD. By categorizing the reference data RD in this way in advance, the search process can be performed with high accuracy.

[0068] 5 do not limit the present exemplary embodiment, but examples include: Data group 1: data published by governments and public agencies Data group 2: data published by industry associations, NPOs, etc. Data group 3: data published by companies that have the problem Data group 4: data published by mass media Data group 5: data published by electronic bulletin boards, blogs, social networking services, etc. Data group 6: data published as summary articles on the Internet Data group 7: data published by research companies Data group 8: data published by competitors of companies that have the target technology Data group 9: data published by competitor researchers of researchers of companies that have the target technology Product evaluation data (reviews and word-of-mouth) published by e-commerce sites, etc. may also be used as data groups.

[0069] In addition, examples of each category include: Category 1: Data related to industrial and sector challenges and efforts to resolve them; Category 2: Data related to management and business challenges and efforts to resolve them; Category 3: Data related to reactions and opinions of the general public, experts, and individuals; Category 4: Data related to market size, growth rate, regulations, trends of each company, etc.; Category 5: Data related to competing products and services; Category 6: Data related to competing technologies.

[0070] (Step S104) In step S104, the acquisition unit 13 acquires information (market information MI) about one or more markets related to the issue indicated by the issue information PI acquired by the search unit 15 in step S103. Here, the market information MI may include information about the size of one or more markets related to the issue.

[0071] The specific acquisition process by the acquisition unit 13 does not limit this exemplary embodiment, but as an example, the acquisition unit 13 may identify one or more products or technology fields related to the issue indicated by the issue information PI and acquire information regarding the market size of the product or technology field (also referred to as market size information).

[0072] (Step S105) Subsequently, in step S105, the search unit 15 generates a report RP including the issue information PI acquired in step S103 and the information on the market size acquired in step S104.

[0073] The search unit 15 may be configured to use a language model LM in the process of generating the report PR. As an example, the search unit 15 may be configured to generate input data including: the issue information PI acquired in step S103 and information on the market size acquired in step S104; the type of graph to be used in the report RP; supplementary information to be included in the report RP (for example, the analysis report summary ARS1 and case study collection CE1 described below); and an instruction to create the report RP, and input the generated input data into the language model. The search unit 15 can use the output data of the language model LM as the report RP.

[0074] (Step S106) In step S106, the output unit 12 outputs the report generated in step S105. As an example, the output unit 12 outputs the generated report RP to the outside of the information processing device 1A via the input / output unit 40 or the communication unit 30.

[0075] A specific example of the structure of the report RP will be described later, but as an example, the report RP may be structured to include text data and images so that it can be visually presented to the user.

[0076] The above-described steps S102 to S106 correspond to step S12 described in exemplary embodiment 1. The above-described steps S102 to S106 may be configured to be executed by the output unit 12.

[0077] (Specific Example of Report RP) Next, a specific example of the report RP output by the output unit 12 will be described.

[0078] (Example 1) FIG. 6 is a diagram illustrating a report RP1, which is an example of a report RP output by the output unit 12. Report RP1 is a report that presents "market segments and their sizes that can be solved by the target technology." As shown in FIG. 6, report RP1 includes a graph GL1 that represents the size of each of one or more markets indicated by the market size information acquired in step S104. As shown in FIG. 6, by displaying the market size in a graph (a pie chart in the example of FIG. 6), the relative sizes of multiple markets can be visually presented to the user. In addition, in the example shown in FIG. 6, report RP1 includes amounts indicating the size of each market and the total size of the markets. This configuration allows the size of each market to be presented to the user in an appropriate manner. In addition, in the example shown in FIG. 6, report RP1 includes the compound annual growth rate (CAGR) of each market and the total size of the markets. This configuration allows the growth rate of each market and the total size of the markets to be presented to the user in an appropriate manner.

[0079] The search unit 15 can generate such a report RP1 by executing a search process based on each assignment with reference to the target data RD.

[0080] 6 may be configured to accept a selection instruction from a user. The acquisition unit 13 may be configured to function as a first acquisition means for acquiring selection information indicating which market the user has selected from among the multiple markets indicated in the report RP1. The search unit 15 may then update the report RP1 to include an analysis related to the market indicated by the user's selection instruction acquired by the acquisition unit 13. The output unit 12 may be configured to output the updated report RP1.

[0081] 7 is a diagram showing an updated report RP1 output by the output unit 12 when the selection information selects the water bottle market. As shown in FIG. 7, the updated report RP1 includes an analysis report summary ARS1 relating to the water bottle market as an analysis related to the water bottle market.

[0082] (Example 2) FIG. 8 illustrates a report RP2, an example of a report RP output by the output unit 12. Report RP2 is a report presenting "Unmet Needs and Importance in the Water Bottle Market." As illustrated in FIG. 8 , report RP2 includes a graph GL2 representing one or more issues related to at least one or more markets, including the issue identified by the search unit 15. As an example, the issues shown in report RP2, "Inner bottles break easily," "Drinks get cold quickly," and "Water bottles are heavy," are all issues identified by the search unit 15 in step S103. As illustrated in FIG. 8 , by displaying the issues in a graph (a pie chart in the example of FIG. 8 ), the relative importance of multiple issues can be visually presented to the user. The search unit 15 may be configured to determine the proportion of each issue in the graph based on the amount of data (text data) associated with the issue.

[0083] The search unit 15 can generate such a report RP1 by executing a search process based on each assignment with reference to the target data RD.

[0084] (Example 3) FIG. 9 is a diagram showing report RP3, an example of report RP output by the output unit 12. Report RP3 is a report that describes "Background of the unmet need for easily breaking inner bottles." As shown in FIG. 9, report RP3 includes a graph GL3 that represents factors related to one or more issues, including the issue identified by the search unit 15 in step S103. As shown in FIG. 9, by displaying the factors in a graph (a pie chart in the example of FIG. 9), the relative importance of multiple factors can be visually presented to the user. Note that the search unit 15 may be configured to determine the proportion of each factor in the graph depending on the amount of data (text data) related to the factor.

[0085] 9 may be configured to accept a selection instruction from the user. The acquisition unit 13 may be configured to function as a second acquisition unit that acquires selection information indicating which factor the user selected from the multiple factors indicated in the report RP3. The search unit 15 may then update the report RP3 to include cases related to the factor indicated by the user's selection instruction acquired by the acquisition unit 13. The output unit 12 may be configured to output the updated report RP3.

[0086] 10 is a diagram showing an updated report RP3 output by the output unit 12 when the selection information selects the factor "strong impact." As shown in FIG. 10, the updated report RP3 includes a case collection CE1 in which an inner bottle broke due to a strong impact as a case related to the factor.

[0087] (Example 4) Fig. 11 is a diagram showing report RP4, which is an example of report RP output by the output unit 12. Report RP4 is a report representing a "Comparison of technological advantages for unmet needs." As shown in Fig. 11, report RP4 includes information (comparison table GL4) regarding a comparison between a target technology (XX system technology in the example of Fig. 11) and technologies (YY system technology, ZZ system technology) of companies (Company A, Company B) different from the company (our company) that possesses the target technology, for one or more issues including the issue identified by the search unit 15 in step S103.

[0088] More specifically, report RP4 shows the results of comparing the target technology (XX system technology) with the comparison technologies (YY system technology, ZZ system technology) along multiple evaluation axes (evaluation axes A to F in the example of FIG. 11). Report RP4 also shows the relative importance of these multiple evaluation axes (issue importance in FIG. 11), the evaluation of each technology along each evaluation axis (evaluation column in FIG. 11), and the features of each technology along each evaluation axis (features X1 to X6, Y1 to Y6, Z1 to Z6 in FIG. 11).

[0089] The search unit 15 can generate such a report RP4 by executing a search process based on each assignment with reference to the target data RD.

[0090] (Example 5) FIG. 12 is a diagram showing report RP5, which is an example of report RP output by the output unit 12. Report RP5 is a report that shows "the market size of the current technology and the market share of each vendor." In other words, report RP5 is a report that shows "the market size of the current solution and the market share of each vendor." As shown in FIG. 12, report RP5 includes a graph that shows the market share of a market that has at least one of one or more issues, including the issue identified by the search unit 15 in step S103. As shown in FIG. 12, by showing the market share as a graph (a pie chart in the example of FIG. 12), the market share can be visually presented to the user.

[0091] The reports RP1 to RP5, which are examples of the report RP described above, may be configured to be displayed as a single slide, or may be configured to display the selected support by selecting a selection tab. Furthermore, the reports RP1 to RP5 may be configured to include images, sounds, and other objects other than those described above.

[0092] (Effects of Information Processing Device 1A and Information Processing Method S1A) The information processing device 1A and information processing method S1A configured as described above provide the same effects as the information processing device 1 and information processing method S1 according to exemplary embodiment 1. Furthermore, according to the information processing device 1A and information processing method S1A configured as described above, the expansion unit 14 expands the term WD, and the search unit 15 executes a search process based on the expanded term EWD, so that issues related to the target technology can be identified with high accuracy. Then, the output unit 12 configured as described above can effectively present information related to the issues to the user.

[0093] [Third Exemplary Embodiment] A third exemplary embodiment, which is an example of an embodiment of the present invention, will be described in detail with reference to the drawings. Components having the same functions as those described in the above exemplary embodiment will be denoted by the same reference numerals, and their description will be omitted as appropriate. The scope of application of each technical means employed in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technical means employed in this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical hindrance occurs. Furthermore, each technical means shown in each drawing referenced to describe this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure, to the extent that no particular technical hindrance occurs.

[0094] (Configuration of Information Processing Device 1B) The configuration of the information processing device 1B according to this exemplary embodiment will be described with reference to FIG. 13. FIG. 13 is a block diagram showing the configuration of the information processing device 1B. As shown in FIG. 13, the information processing device 1B differs from the information processing device 1A according to the second exemplary embodiment in the following respects. That is, the information processing device 1B does not include the search unit 15 and the expansion unit 14 that are included in the information processing device 1A. In the information processing device 1B according to this exemplary embodiment, a language model LM generally performs processing that corresponds to the processing performed by the search unit 15 and the expansion unit 14 that are included in the information processing device 1A. Here, the language model LM may be configured to be included in the information processing device 1B, or may be configured to be included in a device external to the information processing device 1B.

[0095] The identification unit 13 of the information processing device 1B identifies one or more technical features TF possessed by the target technology by performing the same processing as the identification unit 13 of the information processing device 1A. As an example, the identification unit 11 refers to target data TD related to the target technology and identifies one or more technical features TF indicated in the target data TD. Furthermore, the identification unit 13 identifies one or more words or phrases WD representing the one or more technical features TF by performing the same processing as the identification unit 13 of the information processing device 1A.

[0096] Then, the identification unit 13 of the information processing device 1B generates input data including, for example: the one or more words or phrases WD; an instruction to expand the one or more words or phrases WD; an instruction to extract assignments from the reference data RD using the expanded words or phrases EWD; and an instruction to generate a report RP related to the extracted assignments, and inputs the generated input data to the language model LM. The output unit 12 then outputs the data output by the language model LM as a report RP. An example of the report RP output by the output unit 12 is as described in the second exemplary embodiment.

[0097] The above-described configuration can be realized, for example, by training the language model LM in advance using at least one of the following: training data including a word WD and an extended phrase EWD as correct answer data associated with the WD; training data including an extended phrase EWD and an assignment as correct answer data associated with the extended phrase EWD; training data including an extended phrase EWD and information as correct answer data associated with the extended phrase EWD, the information specifying a search process for extracting the assignment; training data including an assignment and a report as correct answer data associated with the assignment; and training data including an assignment and information as correct answer data associated with the assignment, the information specifying a generation process for generating the report. However, the above examples do not limit the present exemplary embodiment. The language model LM may be realized by combining multiple deep learning algorithms, and the multiple training processes performed by the language model LM may substantially include learning using the above-described training data. The language model may also be trained by a training process including unsupervised learning and semi-unsupervised learning.

[0098] [Application Examples] The information processing devices 1, 1A, and 1B (also simply referred to as information processing devices) according to the above-described embodiments can be applied to various fields. For example, the information processing devices can be suitably applied to the manufacturing industry (manufacturers), trading companies, retailers, finance, services, software and communications, mass media, and government agencies, public corporations, and organizations.

[0099] As an example, the information processing device may be configured to identify one or more technical features possessed by a target technology related to the medical / healthcare field, and output information regarding a target problem (a problem in the medical / healthcare field) that is obtained by searching a reference data group based on at least one of the identified one or more technical features and that is related to at least one of the technical features.

[0100] For example, the information processing device may be configured to: - identify one or more technical features of the target technology related to the manufacture of supplements; and - output issues regarding the supplements obtained by searching a group of reference data in the medical and healthcare fields based on at least one of the identified one or more technical features.

[0101] [Example of implementation by software] Some or all of the functions of the information processing devices 1, 1A, 1B (hereinafter also referred to as "each of the above devices") may be implemented by hardware such as an integrated circuit (IC chip), or by software.

[0102] In the latter case, each of the above devices is realized by, for example, a computer that executes instructions of a program, which is software that realizes each function. An example of such a computer (hereinafter referred to as computer C) is shown in Figure 14. Figure 14 is a block diagram showing the hardware configuration of computer C that functions as each of the above devices.

[0103] The computer C includes at least one processor C1 and at least one memory C2. The memory C2 stores a program P for causing the computer C to function as each of the above-mentioned devices. In the computer C, the processor C1 reads and executes the program P from the memory C2, thereby realizing the functions of each of the above-mentioned devices.

[0104] The processor C1 may be, for example, a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a micro processing unit (MPU), a floating point number processing unit (FPU), a physics processing unit (PPU), a tensor processing unit (TPU), a quantum processor, a microcontroller, or a combination thereof. The memory C2 may be, for example, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), or a combination thereof.

[0105] The computer C may further include a RAM (Random Access Memory) for expanding the program P during execution and for temporarily storing various data. The computer C may also include a communication interface for transmitting and receiving data to and from other devices. The computer C may also include an input / output interface for connecting input / output devices such as a keyboard, a mouse, a display, and a printer.

[0106] The program P can also be recorded on a non-transitory, tangible recording medium M that can be read by the computer C. Such a recording medium M can be, for example, a tape, a disk, a card, a semiconductor memory, or a programmable logic circuit. The computer C can acquire the program P via such a recording medium M. The program P can also be transmitted via a transmission medium. Such a transmission medium can be, for example, a communication network or broadcast waves. The computer C can also acquire the program P via such a transmission medium.

[0107] [Appendix 1] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0108] (Appendix A1) An information processing device comprising: an identification means for identifying one or more technical features possessed by a target technology; and an output means for outputting information relating to a target problem, which is a problem obtained by searching a reference data group based on at least one of the one or more technical features identified by the identification means, and which is related to at least one of the technical features.

[0109] (Supplementary Note A2) The information processing device according to Supplementary Note A1, wherein the output means outputs a report including information on the size of one or more markets related to the problem.

[0110] (Supplementary Note A3) The information processing device according to Supplementary Note A2, wherein the report includes a graph showing the size of each of the one or more markets.

[0111] (Appendix A4) The information processing device according to Appendix A3, further comprising a first acquisition means for acquiring selection information indicating which of the one or more markets the user has selected, and the output means for outputting a report including an analysis related to the market selected by the user.

[0112] (Appendix A5) The information processing device according to any one of Appendices A2 to A4, wherein the report includes a graph representing one or more issues related to at least any of the one or more markets, including the target issue.

[0113] (Supplementary Note A6) The information processing device according to any one of Supplementary Notes A2 to A5, wherein the report includes a graph showing factors related to each of one or more tasks including the target task.

[0114] (Appendix A7) The information processing device according to Appendix A6, further comprising a second acquisition means for acquiring selection information indicating which of the factors related to the one or more issues the user has selected, and the output means for outputting a report including examples related to the factor selected by the user.

[0115] (Supplementary Note A8) The information processing device according to any one of Supplementary Notes A2 to A7, wherein the report includes a graph showing a market share of a market having at least one of one or more problems including the target problem.

[0116] (Appendix A9) The information processing device described in any one of Appendices A2 to A8, wherein the report includes, for one or more issues including the target issue, information regarding a comparison between the target technology and a technology of a company other than the company that possesses the target technology.

[0117] (Appendix A10) An information processing device according to any one of Appendices A1 to A9, comprising an expansion means for expanding a term representing one or more technical features identified by the identification means, and the output means for outputting information relating to the problem obtained by a search using the term expanded by the expansion means.

[0118] (Supplementary Note A11) The information processing device according to any one of Supplementary Notes A1 to A10, further comprising a search unit that performs the search.

[0119] (Appendix A12) The information processing device according to Appendix A11, wherein the reference data group includes text data that explicitly or implicitly expresses a problem, and the search means acquires the target problem by comparing a phrase that represents one or more technical features identified by the identification means, or a phrase obtained by expanding the phrase, with the text data included in the reference data group.

[0120] (Appendix A13) The information processing device described in Appendix A11 or A12, wherein the identification means identifies a plurality of technical features possessed by the target technology, and the search means acquires the target problem by performing a search related to technical fields that have some of the plurality of technical features identified by the identification means and do not have other technical features.

[0121] (Supplementary Note A14) The information processing device according to Supplementary Note A12 or A13, wherein the search means optimizes search processing conditions based on a machine learning model that has been trained in advance.

[0122] (Appendix B1) An information processing method including: a computer identifying one or more technical features of a target technology; and outputting information relating to problems related to at least one of the identified one or more technical features, the problems being obtained by searching a reference data group based on at least one of the identified one or more technical features.

[0123] (Supplementary Note B2) The information processing method according to Supplementary Note B1, wherein the outputting step outputs a report including information on the size of one or more markets related to the problem.

[0124] (Supplementary Note B3) The information processing method according to Supplementary Note B2, wherein the report includes a graph showing the size of each of the one or more markets.

[0125] (Appendix B4) The information processing method described in Appendix B3, further comprising: a first acquiring step of acquiring selection information indicating which of the one or more markets the user has selected; and wherein the outputting step outputs a report including an analysis related to the market selected by the user.

[0126] (Appendix B5) The information processing method described in any one of Appendices B2 to B4, wherein the report includes a graph representing one or more issues related to at least one of the one or more markets, including the target issue.

[0127] (Supplementary Note B6) The information processing method according to any one of Supplementary Notes B2 to B5, wherein the report includes a graph showing factors related to each of one or more tasks including the target task.

[0128] (Appendix B7) An information processing method as described in Appendix B6, further comprising obtaining selection information indicating which of the factors related to the one or more issues the user has selected, and wherein the outputting step outputs a report including cases related to the factors selected by the user.

[0129] (Supplementary Note B8) The information processing method according to any one of Supplementary Notes B2 to B7, wherein the report includes a graph showing the market share of a market having at least one of one or more issues including the target issue.

[0130] (Appendix B9) An information processing method described in any one of Appendices B2 to B8, wherein the report includes information regarding a comparison between the target technology and a technology of a company other than the company that possesses the target technology, with respect to one or more issues including the target issue.

[0131] (Appendix B10) An information processing method described in any one of Appendices B1 to B9, further comprising expanding a term representing one or more technical features identified in the identifying step, and wherein the outputting step outputs information relating to the problem obtained by a search using the term expanded in the expanding step.

[0132] (Supplementary Note B11) The information processing method according to any one of Supplementary Notes B1 to B10, further comprising a search step of performing the search.

[0133] (Appendix B12) An information processing method as described in Appendix B11, wherein the reference data group includes text data that explicitly or implicitly expresses a problem, and the searching step acquires the target problem by comparing a phrase that represents one or more technical features identified in the identifying step, or a phrase obtained by expanding that phrase, with the text data included in the reference data group.

[0134] (Appendix B13) An information processing method as described in Appendix B11 or B12, wherein the identifying step identifies a plurality of technical features possessed by the target technology, and the searching step acquires the target problem by performing a search related to technical fields that have some of the plurality of technical features identified in the identifying step and do not have other technical features.

[0135] (Supplementary Note B14) The information processing method according to Supplementary Note B12 or B13, wherein the searching step optimizes search processing conditions based on a machine learning model that has been trained in advance.

[0136] (Appendix C1) A program that causes a computer to execute the following processes: a process of identifying one or more technical features of a target technology; and a process of outputting information about problems that are obtained by searching a reference data group based on at least one of the identified one or more technical features and that are related to at least one of the identified technical features.

[0137] (Supplementary Note C2) The program according to Supplementary Note C1, wherein the outputting process outputs a report including information on the size of one or more markets related to the problem.

[0138] (Appendix C3) The program according to Appendix C2, wherein the report includes a graph showing the size of each of the one or more markets.

[0139] (Appendix C4) The program described in Appendix C3, further executing a first acquisition process to acquire selection information indicating which of the one or more markets the user has selected, and wherein the output process outputs a report including an analysis related to the market selected by the user.

[0140] (Appendix C5) The program described in any one of Appendices C2 to C4, wherein the report includes a graph representing one or more issues related to at least one of the one or more markets, including the target issue.

[0141] (Appendix C6) The program according to any one of Appendices C2 to C5, wherein the report includes a graph showing factors related to each of one or more tasks including the target task.

[0142] (Appendix C7) The program described in Appendix C6 further executes a second acquisition process to acquire selection information indicating which of the factors related to the one or more issues the user selected, and the output process outputs a report including cases related to the factors selected by the user.

[0143] (Appendix C8) The program according to any one of appendices C2 to C7, wherein the report includes a graph showing the market share of a market having at least one of one or more issues including the target issue.

[0144] (Appendix C9) The program described in any one of Appendices C2 to C8, wherein the report includes information regarding a comparison between the target technology and a technology of a company other than the company that possesses the target technology, with respect to one or more issues including the target issue.

[0145] (Appendix C10) A program described in any one of Appendices C1 to C9, further executing an expansion process to expand a term representing one or more technical features identified in the identification process, and wherein the output process outputs information regarding the problem obtained by a search using the term expanded by the expansion means.

[0146] (Supplementary Note C11) The program according to any one of Supplementary Notes C1 to C10, further executing a search process for performing the search.

[0147] (Appendix C12) The program described in Appendix C11, wherein the reference data group includes text data that explicitly or implicitly expresses the problem, and the searching process acquires the target problem by comparing a phrase that represents one or more technical features identified by the identification means, or a phrase obtained by expanding that phrase, with the text data included in the reference data group.

[0148] (Appendix C13) The program described in Appendix C11 or C12, wherein the identifying process identifies a plurality of technical features possessed by the target technology, and the searching process acquires the target issue by performing a search for technical fields that have some of the plurality of technical features identified by the identifying process and do not have other technical features.

[0149] (Supplementary Note C14) The program according to Supplementary Note C12 or C13, wherein the search process optimizes search process conditions based on a machine learning model that has been trained in advance.

[0150] [Appendix 2] This disclosure includes the techniques described in the following appendices. However, the present invention is not limited to the techniques described in the following appendices, and various modifications are possible within the scope of the claims.

[0151] (Appendix D1) An information processing device comprising at least one processor, the at least one processor executing: an identification process for identifying one or more technical features of a target technology; and an output process for outputting information relating to a target problem, which is a problem obtained by searching a reference data group based on at least one of the one or more technical features identified by the identification process, and which is related to at least one of the technical features.

[0152] (Supplementary Note D2) The information processing device according to Supplementary Note D1, wherein the output process outputs a report including information on the size of one or more markets related to the problem.

[0153] (Supplementary Note D3) The information processing device according to Supplementary Note D2, wherein the report includes a graph representing the size of each of the one or more markets.

[0154] (Appendix D4) The information processing device described in Appendix D3, further comprising: a first acquisition process for acquiring selection information indicating which of the one or more markets the user has selected; and an output process for outputting a report including an analysis related to the market selected by the user.

[0155] (Appendix D5) The information processing device described in any one of Appendices D2 to D4, wherein the report includes a graph representing one or more issues related to at least one of the one or more markets, including the target issue.

[0156] (Appendix D6) The information processing device according to any one of appendices D2 to D5, wherein the report includes a graph showing factors related to each of one or more tasks including the target task.

[0157] (Appendix D7) An information processing device as described in Appendix D6, further comprising a second acquisition means for acquiring selection information indicating which of the factors related to the one or more issues the user has selected, and the output means for outputting a report including cases related to the factor selected by the user.

[0158] (Supplementary Note D8) The information processing device according to any one of Supplementary Notes D2 to D7, wherein the report includes a graph showing the market share of a market having at least one of one or more problems including the target problem.

[0159] (Appendix D9) An information processing device described in any one of Appendices D2 to D8, wherein the report includes information regarding a comparison between the target technology and a technology of a company other than the company that possesses the target technology, with respect to one or more issues including the target issue.

[0160] (Appendix D10) An information processing device described in any one of Appendices D1 to D9, further performing an expansion process to expand a term representing one or more technical features identified by the identification process, and the output process outputs information regarding the problem obtained by a search using the term expanded by the expansion means.

[0161] (Supplementary Note D11) The information processing device according to any one of Supplementary Notes D1 to D10, further executing a search process for performing the search.

[0162] (Appendix D12) An information processing device as described in Appendix D11, wherein the reference data group includes text data that explicitly or implicitly expresses a problem, and the search process acquires the target problem by comparing a phrase that represents one or more technical features identified by the identification process, or a phrase obtained by expanding that phrase, with the text data included in the reference data group.

[0163] (Appendix D13) An information processing device as described in Appendix D11 or D12, wherein the identification process identifies a plurality of technical features possessed by the target technology, and the search process acquires the target issue by performing a search for technical fields that have some of the plurality of technical features identified by the identification process and do not have other technical features.

[0164] (Supplementary Note D14) The information processing device according to Supplementary Note D12 or D13, wherein the search process optimizes conditions for the search process based on a machine learning model that has been trained in advance.

[0165] The information processing device may further include a memory, and the memory may store a program for causing the at least one processor to execute each of the processes.

[0166] REFERENCE SIGNS LIST 1, 1A, 1B ... Information processing device 11 ... Identification unit 12 ... Output unit 13 ... Acquisition unit 14 ... Expansion unit 15 ... Search unit

Claims

1. An information processing device comprising: an identification means for identifying one or more technical features of a target technology; and an output means for outputting information relating to a target problem which is obtained by searching a reference data group based on at least one of the one or more technical features identified by said identification means and which is a problem related to at least one of said technical features.

2. The information processing device according to claim 1, wherein the output means outputs a report including information regarding the size of one or more markets related to the issue.

3. The information processing device according to claim 2, wherein the report includes a graph showing the size of each of the one or more markets.

4. An information processing device as described in claim 3, further comprising a first acquisition means for acquiring selection information indicating which of the one or more markets the user has selected, and wherein the output means outputs a report including an analysis related to the market selected by the user.

5. An information processing device as claimed in any one of claims 2 to 4, wherein the report includes a graph representing one or more issues related to at least any of the one or more markets, the one or more issues including the target issue.

6. An information processing device according to any one of claims 2 to 5, wherein the report includes a graph showing factors relating to each of one or more tasks including the target task.

7. An information processing device as described in claim 6, further comprising a second acquisition means for acquiring selection information indicating which of the factors related to the one or more issues has been selected by the user, and wherein the output means outputs a report including examples related to the factor selected by the user.

8. An information processing device according to any one of claims 2 to 7, wherein the report includes a graph showing the market share of a market having at least one of the one or more problems including the target problem.

9. An information processing device as claimed in any one of claims 2 to 8, wherein the report includes information relating to a comparison between the target technology and a technology of a company other than the company which possesses the target technology, with respect to one or more issues including the target issue.

10. An information processing device as claimed in any one of claims 1 to 9, further comprising an expansion means for expanding a term expressing one or more technical features identified by said identification means, and said output means for outputting information relating to the problem obtained by a search using the term expanded by said expansion means.

11. The information processing device according to any one of claims 1 to 10, further comprising a search means for performing the search.

12. The information processing device of claim 11, wherein the reference data group includes text data that explicitly or implicitly expresses a problem, and the search means acquires the target problem by comparing a phrase expressing one or more technical features identified by the identification means, or a phrase obtained by expanding the phrase, with the text data included in the reference data group.

13. An information processing device as described in claim 11 or 12, wherein the identification means identifies a plurality of technical features possessed by the target technology, and the search means acquires the target issue by conducting a search relating to technical fields that have some of the plurality of technical features identified by the identification means and do not have other technical features.

14. The information processing device according to claim 12 or 13, wherein the search means optimizes search processing conditions based on a machine learning model that has been trained in advance.

15. An information processing method including the steps of: identifying one or more technical features of a target technology; and outputting information relating to issues related to at least one of the identified technical features, the issues being obtained by searching a reference data group based on at least one of the identified technical features.

16. A program causing a computer to execute the following processes: identifying one or more technical features of a target technology; and outputting information regarding issues related to at least one of the identified technical features, which are obtained by searching a reference data group based on at least one of the identified technical features.

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