Analysis System

Abstract

To provide an analysis system, a method, a server and a program for efficiently performing business analysis in comparatively short time.SOLUTION: An analysis program of an analysis system executes: factor analysis processing of extracting a first patent factor given to patent information, detecting a second patent factor approximated to the first extracted patent factor, giving arbitrary weighting to the first and second patent factors, and giving a score to a nominal person of the patent information to which the first and second patent factors are given to which the weighting is given on the basis of the weighting; and clustering processing of extracting a business operator to whom an arbitrary industry classification is given on the basis of financial information, grasping the industry classification to which the arbitrary weighting is given of the industry classification given to the extracted business operator as a value chain label, and on the other hand, giving the value chain label to the patent information whose nominal person is the extracted business operator by collating the patent information with the financial information to grasp the patent information to which the value chain label is given as a cluster.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to an analysis system, a server, a program, and an analysis method, and in particular to an analysis system, a server, a program, and an analysis method that includes a server that can access patent information and financial information including at least industry classification, and a user terminal connected to the server via a network, and that performs analysis based on the patent information and financial information based on a user request via the user terminal. [Background technology]

[0002] When a business develops a new business, it may take the approach of analyzing the market to discover needs, comparing those needs with the seeds that the business possesses, and planning a business that matches those needs and seeds.

[0003] Patent Document 1 discloses a technology that stores market needs and business seeds, identifies businesses that fit these needs and seeds, and then selects from the identified businesses the business that fits the direction that the business strategy should take. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2009-20712 A Summary of the Invention [Problem to be solved by the invention]

[0005] Incidentally, when a business operator conducts a business analysis such as developing a new business or analyzing its business position, a method may be adopted in which market needs are analyzed, the competitive situation in the market is analyzed, and the value chain in that market is analyzed, and then the information necessary for realizing or analyzing the business is processed.

[0006] When this type of information is processed, for example, by a consulting firm that engages in consulting work, it is necessary to collect a huge amount of data and perform, for example, multivariate analysis based on the collected data. This type of work is cumbersome and time-consuming, and can take an enormous amount of time, up to several months.

[0007] In particular, when there is a possibility that intangible assets such as intellectual property are included as business assets, it is easy to imagine that the difficulty of analyzing and evaluating them would lead to an increase in cumbersome work, increased costs, and longer work hours.

[0008] The present invention has been made in consideration of the above circumstances, and provides an analysis system that can perform business analysis efficiently and in a relatively short time. M The objective of the present invention is to provide [Means for solving the problem]

[0009] The analysis system according to the present invention for achieving the above-mentioned object includes a server that can access patent information and financial information including at least an industrial classification, and a user terminal connected to the server via a network, and performs an analysis based on the patent information and the financial information based on a user request via the user terminal, in which the server executes a factor analysis process of extracting a first patent factor assigned to the patent information, detecting a second patent factor similar to the extracted first patent factor, assigning arbitrary weights to the first patent factor and the second patent factor, and assigning a score based on the weighting to the holder of the patent information to which the weighted first patent factor and the second patent factor have been assigned, and a clustering process of extracting businesses to which an arbitrary industrial classification has been assigned based on the financial information, grasping the industrial classification to which an arbitrary weight has been assigned among the industrial classifications assigned to the extracted businesses as a value chain label, while comparing the patent information with the financial information and assigning a value chain label to patent information to which the extracted businesses are assigned, and grasping the patent information to which the value chain label has been assigned as a cluster.

[0010] According to this method, a factor analysis process is performed based on the patent factors assigned to the patent information, and a clustering process is performed based on the patent information and financial information, so that business analysis can be performed efficiently and in a relatively short time, even when intangible assets such as intellectual property disclosed in the patent information are included as business assets.

[0011] This analysis system outputs the results of factor analysis processing and clustering processing.

[0012] The first patent factor and the second patent factor extracted or detected by this analysis system are at least one of patent classification, abstract information, and use information, and the patent information is searched for by the user based on any search condition via the user terminal.

[0013] The industry classifications processed by this analysis system are those that include NACE codes.

[0014] In order to achieve the above-mentioned object, the analysis system of the present invention comprises a server that can access patent information and financial information including at least industry classification, and a user terminal connected to the server via a network, and performs analysis based on the patent information and financial information based on a user request via the user terminal, and the server extracts businesses to which an arbitrary industry classification has been assigned based on the financial information, and performs a clustering process to extract businesses for which there is no patent information in which the business is the owner from the businesses extracted by comparing the patent information with the financial information, and assigns arbitrary indicators based on the financial information and identifies the businesses to which indicators have been assigned as a cluster.

[0015] The indicators provided by this analysis system may be divided into a number of stages according to the degree of maturity of the operator's business.

[0016] In order to achieve the above object, the server according to the present invention is a server that accesses patent information and financial information including at least an industrial classification, and performs an analysis based on the patent information and the financial information, and performs a factor analysis process of extracting a first patent factor assigned to the patent information, detecting a second patent factor similar to the extracted first patent factor, assigning arbitrary weightings to the first patent factor and the second patent factor, and assigning a score based on the weightings to the holder of the patent information to which the weighted first patent factor and the second patent factor have been assigned, and a clustering process of extracting businesses to which an arbitrary industrial classification has been assigned based on the financial information, grasping the industrial classification to which an arbitrary weighting has been assigned among the industrial classifications assigned to the extracted businesses as a value chain label, while comparing the patent information and the financial information, assigning a value chain label to patent information to which the extracted businesses are assigned, and grasping the patent information to which the value chain label has been assigned as a cluster.

[0017] The program of the present invention for achieving the above-mentioned object is a program that accesses patent information and financial information including at least an industrial classification, and performs an analysis based on the patent information and the financial information, and executes a factor analysis process of extracting a first patent factor assigned to the patent information, detecting a second patent factor similar to the extracted first patent factor, assigning arbitrary weightings to the first patent factor and the second patent factor, and assigning a score based on the weightings to the holder of the patent information to which the weighted first patent factor and the second patent factor have been assigned, and a clustering process of extracting businesses to which an arbitrary industrial classification has been assigned based on the financial information, grasping the industrial classification to which an arbitrary weighting has been assigned among the industrial classifications assigned to the extracted businesses as a value chain label, while comparing the patent information and the financial information, assigning a value chain label to patent information to which the extracted business is the holder, and grasping the patent information to which the value chain label has been assigned as a cluster.

[0018] The program may be implemented based on artificial intelligence techniques.

[0019] The analysis method according to the present invention for achieving the above object is an analysis method using an analysis system that includes a server that can access patent information and financial information including at least an industrial classification, and a user terminal connected to the server via a network, and performs an analysis based on the patent information and the financial information based on a user request via the user terminal, and extracts a first patent factor assigned to the patent information, detects a second patent factor that is similar to the extracted first patent factor, performs a factor analysis process in which arbitrary weights are assigned to the first patent factor and the second patent factor, and scores are assigned to the holders of the patent information to which the weighted first patent factor and the second patent factor are assigned based on the weights, extracts businesses to which arbitrary industrial classifications are assigned based on the financial information, and recognizes the industrial classifications to which arbitrary weights are assigned as value chain labels among the industrial classifications assigned to the extracted businesses, while performing a clustering process in which a value chain label is assigned to patent information to which the extracted businesses are assigned by comparing the patent information and the financial information, and recognizes the patent information to which the value chain labels are assigned as clusters. Effect of the Invention

[0020] According to the present invention, business analysis can be performed efficiently and in a relatively short time. [Brief description of the drawings]

[0021] [Figure 1] 1 is a diagram illustrating an overview of an analysis system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram for explaining an outline of the configuration of a first database and a second database of the analysis system according to the present embodiment. [Diagram 3] FIG. 2 is a block diagram for explaining an outline of the configuration of a computer in the analysis system according to the present embodiment. [Figure 4] FIG. 2 is a block diagram illustrating an outline of the configuration of a storage unit of a server in the analysis system according to the present embodiment. [Diagram 5]10 is a flowchart outlining the process of the factor analysis processing unit of the server of the analysis system according to the present embodiment. [Figure 6] FIG. 11 is a block diagram for explaining an outline of the processing of a clustering processing unit of the server of the analysis system according to the present embodiment. [Figure 7] 13 is a flowchart outlining the processing of a clustering processing unit of a server in the analysis system according to the present embodiment. [Figure 8] FIG. 13 is a diagram for explaining an outline of the processing of a clustering processing unit of the server of the analysis system according to the present embodiment. [Figure 9] 13 is a flowchart outlining the processing of a clustering processing unit of a server in the analysis system according to the present embodiment. [Figure 10] FIG. 13 is a diagram for explaining an outline of the processing of the output unit of the server of the analysis system according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] Next, an analysis system according to an embodiment of the present invention will be described with reference to FIGS.

[0023] 1 is a diagram for explaining an outline of an analysis system according to the present embodiment. As shown in the figure, an analysis system 10 mainly comprises a first database 21, a second database 22, a server 30, and a plurality of user terminals 40, which are connected to each other via an Internet network 200 so as to be accessible to each other.

[0024] In this embodiment, the first database 21 and the second database 22 are deployed at database management providers 1a and 1b, respectively, the server 30 is deployed at a service provider 2 that provides a service of performing analysis based on patent information and financial information, and the user terminals 40 are deployed at multiple users 3 who use the service provided by the service provider 1.

[0025] 2 is a block diagram illustrating an outline of the configuration of the first database 21 and the second database 22. As shown in the figure, the first database 41 stores patent information D1 in this embodiment.

[0026] Patent information D1 is information about patent documents relating to inventions for which a patent application has been filed or a patent right has been registered, and includes patent factors including at least patent classifications such as IPC and F-terms, summary information, or use information relating to the use of the invention, as well as attributes of the patent applicant or patent owner, disclosure of the invention (claims, detailed description of the invention, drawings, etc.), etc.

[0027] Here, patent classification refers to classifying patent documents according to their technical content, and assigning each classified patent document a combination of symbols and numbers as a string of symbols and numbers. For example, if the technical content of a patent document is "electronic commerce," it will be assigned the number "G06Q30 / 00."

[0028] In this embodiment, the patent information D1 is updated at appropriate times.

[0029] In this embodiment, financial information D2 is stored in the second database 22. This financial information D2 is information related to the finances of the business operator, and includes, in addition to industry classifications such as NACE codes and SIC codes, the sales of the business operator, the investment situation, the form of the business operator, and stages, which are a plurality of stages (indicators) classified according to the degree of maturity of the business if the business operator is a so-called startup.

[0030] Here, the industrial classification is a classification of the economic activities of a business operator, and a combination of numbers is assigned as a code to each classified economic activity. For example, the economic activities of an electric power supplier operating an electric power supply business can be classified into the economic activities of "power generation," "power transmission," "sales," and "maintenance," and each classified economic activity is assigned a code such as "3511," "3512," "3513," and "3514."

[0031] In this embodiment, the investment status includes various information such as the investment size, the investor, the investment destination, and the investment form such as M&A investment or minority investment in which less than half of the shares are acquired.

[0032] In this embodiment, the type of business operator includes, for example, a classification of business operators, such as whether the business operator is a startup or not. Here, in this embodiment, a startup refers to, for example, a business operator that has been established within x years, has a sales scale below a certain level, and is unlisted.

[0033] In this embodiment, the stages are divided into four stages: a "seed stage," an "early stage," a "middle stage," and a "later stage."

[0034] In this embodiment, this financial information D2 is updated at appropriate times.

[0035] In this embodiment, the server 30 and the user terminal 40 are implemented by computers having substantially the same hardware configuration, for example, desktop or notebook computers.

[0036] 3 is a block diagram illustrating an outline of the configuration of a computer. As shown in the figure, the computer mainly comprises a processor 101, a memory 102, a storage 103, a transmission / reception unit 104, and an input / output unit 105, which are electrically connected to each other via a bus 106.

[0037] The processor 101 is an arithmetic unit that controls the operation of the computer, controls the transmission and reception of data between each element, and performs processes required for executing programs.

[0038] In this embodiment, the processor 101 is, for example, a CPU (Central Processing Unit), and executes programs stored in a storage 103 (to be described later) and deployed in a memory 102 to perform various processes.

[0039] The memory 102 includes a main storage device configured as a volatile storage device such as a dynamic random access memory (DRAM), and an auxiliary storage device configured as a non-volatile storage device such as a flash memory or a hard disk drive (HDD).

[0040] This memory 102 is used as a working area for the processor 101, and also stores a basic input / output system (BIOS) that is executed when the computer 100 is started up, various setting information, and the like.

[0041] The storage 103 stores programs, information used in various processes, etc. The configuration of the storage 103 will be described later.

[0042] The transceiver 104 connects the computer 100 to a network such as the Internet, and may include a short-range communication interface such as Bluetooth (registered trademark) or BLE (Bluetooth Low Energy).

[0043] The input / output unit 105 is an interface to which input / output devices are connected, and examples of these input / output devices include a keyboard, a mouse, and a display.

[0044] The bus 106 transmits, for example, address signals, data signals, and various control signals between the processor 101, memory 102, storage 103, transmission / reception unit 104, and input / output unit 105 that are connected thereto.

[0045] 4 is a block diagram illustrating an outline of the configuration of the storage 103 of the server 30. As shown in the figure, the storage 103 includes an analysis program 50.

[0046] In this embodiment, this analysis program 50 is implemented by a screen interface that is displayed on the displays of the server 30 and the user terminal 40 and enables input and output of information at the server 30 and the user terminal 40, and includes a factor analysis processing unit 51, a clustering processing unit 52, and an output unit 53.

[0047] In this embodiment, the factor analysis processing unit 51 is a module that assigns a score to the holder (patent applicant or patent owner) of patent information D1 searched for by a user 3 via a user terminal 40 based on any search criteria (e.g., “power supply”).

[0048] 5 is a flowchart outlining the processing of the factor analysis processing unit 51. When the user 3 searches for patent information D1 based on any search condition via the user terminal 40, this factor analysis processing unit 51 extracts any patent classification assigned to the searched patent information D1 as a first patent classification in step S1, as shown in the figure.

[0049] In this embodiment, if a plurality of patent classifications are assigned to the patent information D1, the assigned plurality of patent classifications may be extracted as the first patent classification.

[0050] Next, in step S2, a patent classification similar to the patent classification extracted as the first patent classification is detected as the second patent classification. For example, if "G06Q30 / 00" (electronic commerce) is extracted as the first patent classification, "G06Q20 / 00" (payment architecture, etc.) is detected as the second patent classification.

[0051] In this embodiment, a plurality of patent classifications may be detected as second patent classifications according to the extracted first patent classification.

[0052] Then, in step S3, weights are assigned to the extracted first patent classification and the detected second patent classification based on an arbitrary viewpoint. For example, if the viewpoint is a main patent classification related to billing processing technology in electronic commerce, weights are assigned to patent classifications in order of their proximity to this viewpoint.

[0053] Furthermore, in step S4, the holder (patent applicant or patent owner) of the patent information D1 to which the weighted first and second patent classifications have been assigned is extracted, and a score is assigned to the extracted holder based on the assigned weighting.

[0054] For example, if the first patent classification is weighted at "6" and the second patent classification is weighted at "3," and a given business is the holder of seven patents assigned to the first patent classification and three patents assigned to the second patent classification, the business will be assigned a score of "54."

[0055] In this embodiment, the clustering processing unit 52 shown in Figure 4 is a module that assigns a value chain label to patent information D1 or assigns a stage to an arbitrary business operator, and thereby grasps the patent information D1 to which a value chain label has been assigned or the business operator to which a stage has been assigned as a cluster.

[0056] 6 is a block diagram for explaining an outline of the processing of the clustering processing unit 52. As shown in the figure, the clustering processing unit 52 executes a first processing S10 and a second processing S20.

[0057] 7 is a flowchart outlining the first process S10 of the clustering processing unit 52. In the first process S10, when the user 3 searches for businesses based on an arbitrary NACE code from within the financial information D2 via the user terminal 40, as shown in the figure, in step S11, businesses based on the arbitrary NACE code are extracted.

[0058] In this embodiment, for example, only businesses that include any of "3511" (power generation), "3512" (power transmission), "3513" (sales), and "3514" (maintenance) are searched for, and businesses to which these NACE codes have been assigned are extracted.

[0059] Next, in step S12, the NACE codes assigned to the business operators are weighted based on the business operations of the extracted business operators, and the major NACE codes weighted as major NACE codes are recognized as value chain labels.

[0060] On the other hand, in step S13, as shown in FIG. 8, the patent information D1 and the financial information D2 are compared, and in step S14 shown in FIG. 7, a value chain label is assigned to the patent information D1 whose owner is a business entity extracted based on an arbitrary NACE code.

[0061] 9 is a flowchart outlining the second process S20 of the clustering processing unit 52. In the second process S20, in step S21, similar to step S11 of the first process S10, businesses are extracted based on any NACE code.

[0062] On the other hand, in step S22, as shown in FIG. 8, the patent information D1 is compared with the financial information D2, and in step S23 shown in FIG. 9, from among the businesses extracted based on an arbitrary NACE code, businesses for which there is no patent information D1 in which the extracted business is the owner are extracted.

[0063] In this embodiment, it is assumed that the business entity extracted in step S23 is a start-up.

[0064] Thereafter, in step S24, the businesses extracted in step S23 are assigned a stage, which is classified into four stages, "seed stage," "early stage," "middle stage," and "later stage," based on the financial information D2.

[0065] The output unit 53 shown in FIG. 4 is a module that outputs the results of the processing in the factor analysis processing unit 51 and the results of the processing in the clustering processing unit 52.

[0066] In this embodiment, based on the processing in the factor analysis processing unit 51 and the processing in the clustering processing unit 52, the output unit 53 outputs the results of comprehensive processing for any business operator, for example, as shown in Figure 10, with the "business scale" on the vertical axis and the "intellectual property power of the business operator" on the horizontal axis.

[0067] It is also possible to list or rank a plurality of businesses based on the results of comprehensive processing in the factor analysis processing unit 51 and clustering processing unit 52 for the plurality of businesses and output the results.

[0068] For example, based on the results of factor analysis and clustering, a score can be calculated for each cluster of business types (elements) that make up an arbitrary value chain, and the scores can be converted to one-dimensional scores using non-dominated sorting, thereby evaluating and listing the affinity of businesses, research institutions, etc. with the value chain.

[0069] On the other hand, it is also possible to output the results of the processing in each step (step S1 to step S4) of the factor analysis processing unit 51 shown in FIG. 5, the results of the processing in each step (step S11 to step S14) of the first processing S10 of the clustering processing unit 52 shown in FIG. 7, and the results of the processing in each step (step S21 to step S24) of the second processing S20 shown in FIG. 9.

[0070] Furthermore, in this embodiment, after executing processing in the factor analysis processing unit 51 or the clustering processing unit 52, the output unit 53 is also capable of outputting the results of processing based on any information contained in the patent information D1 and the financial information D2.

[0071] For example, for a cluster related to any technology that has been assigned an arbitrary value chain label through the clustering process, the total amount of investment in the businesses included in this cluster can be output, and this total amount can be understood as the expected value (market outlook) for the future market of the cluster.

[0072] Furthermore, by outputting the businesses that are investment targets included in a cluster related to a given technology that has been assigned an arbitrary value chain label through the clustering process, it is possible to understand the investment trends of those businesses in their industry competitors, etc., and thus to consider business strategies including investment strategies.

[0073] On the other hand, for businesses that have been assigned an arbitrary stage through the clustering process, the stage assigned to the business can be output, and an evaluation can be performed on businesses that are not listed as holders of patent information D1 using an estimated value based on financial information D2 relating to this stage.

[0074] In this embodiment, the analysis program 50 is implemented based on artificial intelligence technology, and in particular, the processes in the factor analysis processing unit 51 and the clustering processing unit 52 are executed by artificial intelligence technology.

[0075] In this embodiment, for example, learning data is generated based on patent information D1 and financial information D2, and a trained model is generated by performing machine learning on the generated learning data using an arbitrary value chain label as training data, and processing in the clustering processing unit 52 is performed based on this trained model.

[0076] As a method for performing machine learning, various algorithms such as neural networks, random forests, and SVM (Support Vector Machine) are appropriately used.

[0077] A service provider 2 equipped with a server 30 storing such an analysis program 50 provides a service of performing analysis based on patent information D1 and financial information D2 using the analysis system 10 to a user 3 via a user terminal 40 by subscription, download or other method.

[0078] User 3 can use analysis system 10 to perform analysis based on factor analysis processing and analysis based on clustering processing, as well as to perform analysis by correlating factor analysis processing with clustering processing.

[0079] In this manner, according to the analysis system 10 of this embodiment, a factor analysis process is performed based on the patent classification assigned to the patent information D1, and a clustering process is performed based on the patent information D1 and the financial information D2. Therefore, even if the intangible asset of intellectual property disclosed in the patent information D1 is included as a business asset, business analysis can be performed efficiently and in a relatively short time.

[0080] On the other hand, even if the intellectual property disclosed in the patent information D1 is not included as a business asset, clustering processing is performed based on the financial information D2, so that business analysis can be performed efficiently and in a relatively short time, just as in the case where the intellectual property is included as a business asset.

[0081] The analysis system 10 of this embodiment is expected to be used for various purposes as follows.

[0082] For example, it is possible to explore new business development themes by extracting value chains that are highly compatible with any technology or intellectual property desired by user 3, who is a business operator, and then considering which markets to enter from among the extracted value chains.

[0083] For example, an M&A strategy can be formulated for a specific market, in which candidate M&A targets are considered from the perspective of vertical integration and horizontal division of labor, based on any technology or intellectual property desired by User 3, a business operator.

[0084] For example, we can formulate research and development strategies and intellectual property strategies, such as considering the research and development strategies and intellectual property strategies necessary when carrying out M&A from the perspective of vertical integration and horizontal division of labor.

[0085] For example, technology clustering can be combined with inventor network analysis to develop a roadmap for R&D strategies.

[0086] For example, when a startup (or venture) proposes an alliance with a major corporation, it can use this to present an objective comparative advantage.

[0087] For example, in the case of developing a new business, it can be used to identify personnel with knowledge of complementary technologies and know-how from the perspective of vertical integration and horizontal division of labor.

[0088] For example, when considering starting a business based on a seed idea, it can be used to search for entrepreneurs, such as identifying the people and organizations that are likely to make the business successful.

[0089] For example, it can be used to identify key engineers at a technology venture company and then conduct due diligence on that company.

[0090] The present invention is not limited to the above-described embodiment, and various modifications are possible without departing from the spirit of the invention.

[0091] In the above embodiment, the server 30 accesses the second database 22 in which financial information D2 including the investment status, business form, startup stage, etc. is stored. However, the server 30 may be configured to access a database in which startup information including these pieces of information is stored separately from the financial information D2.

[0092] In the above embodiment, the case where the patent factor to be extracted or detected is the patent classification has been described, but abstract information or use information may be extracted or detected as the patent factor.

[0093] In the above embodiment, the case where the server 30 is provided at the service provider 2 has been described, but the server 30 may be a server implemented in a cloud environment. [Explanation of symbols]

[0094] 2. Service providers 3 Users 10 Analysis System 21 Database No. 1 22 Second Database 30 Servers 40 User terminal 50 Analysis Program (Program) 51 Factor analysis processing unit 52 Clustering Processing Unit 53 Output section D1 Patent Information D2 Financial information

Claims

[Claim 1] An analysis system comprising a server that can access patent information and financial information including at least an industry classification, and a user terminal connected to the server via a network, the analysis system executing an analysis based on the patent information and the financial information based on a user request via the user terminal, The server, Extracting businesses to which any of the industrial classifications are assigned based on the financial information; extracting, from the business operators extracted by comparing the patent information with the financial information, business operators for which there is no patent information in which the business operator is the owner; a clustering process for extracting the businesses for which no patent information exists, and then assigning stages as a plurality of indicators classified according to the degree of maturity of the business when the business is a start-up, which are included in the financial information, to the businesses for which no patent information exists based on the financial information, and grasping the businesses for which no patent information exists to which the stages have been assigned as a cluster; An analysis system that runs

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