JP2022109238A - Rule watch system or the like - Google Patents

Abstract

To provide a rule watch system and a rule watch method for reducing complexity of grasping information on rule formation.SOLUTION: In a rule watch system 10, a crawler server 9 includes collection means 2 for collecting rule information 13 composed of information on rule formation including regulations and standardization disclosed on the Internet on the basis of a collection condition 2a, and translation means 3 for translating the collected rule information into a prescribed language on the basis of a translation condition 3a, a server 1 includes simplification means 7 for simplifying the rule information 13 to concise information, and an SNS server 14 includes contribution means 6 for contributing the concise information to an SNS so as to make an SNS user monitor the rule formation.SELECTED DRAWING: Figure 2

Description

The present invention relates to a rule watch system and the like for monitoring information related to rule formation. Furthermore, it relates to a rule watch system using SNS.

Patent Literature 1 discloses an information processing device and the like capable of suitably presenting information on pharmaceutical affairs or medical regulations. The information processing method collects regulatory information related to pharmaceutical affairs or medical regulations published on the Internet with reference to acquisition rules indicating procedures for acquiring the regulatory information, Related information related to the information is added, and the regulation information to which the related information is added is output to the user.

In addition, in solving global social issues, there is a growing recognition that the conventional approach of focusing on the individual and short-term thinking cannot be adequately tackled. In Approach is now required. However, there tends to be a lack of platforms for companies, researchers, and citizens to deal with social issues with an Outside-in Approach that transcends fields.

JP 2020-190766 A

Many people and companies will be affected by the formation of rules including legal regulations and standardization, but there are few opportunities for such people and companies to be involved in the formation of rules. In addition, the information related to rule formation has various languages, styles, etc. in countries around the world, and it is troublesome to monitor and check them.

SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide a rule watch system or the like that reduces the complexity of grasping information related to rule formation.

(1) The rule-watching method of the present invention is a rule-watching method executed by one or more computers in an environment open to the public via the Internet based on collection conditions including pre-registered collection destinations. collecting rule information including information on rule formation such as issues, human rights issues, laws and regulations or standardization; forming concise information based on predetermined information obtained from the rule information; and a step of making the initial posting to an SNS site for posting the information as the initial posting.

"Information on rule formation" is information on domestic and foreign rule formation, such as environmental issues, human rights issues, standardization of technology, and laws and regulations. For example, it is information about social issues sent by NGOs, companies, etc., and new technologies and services that address them. For example, information on rules, regulations, standards, and arrangements for legal regulation and standardization. For example, information collected at the stage of arousal of public opinion, the stage of involvement of drafting bodies, the stage of legislation by parliament, the stage of administrative orders, and the stage of judicial decisions. is.
Also, for example, standardization agreements refer to things (products of production activities) and non-things (organizations, (responsibility authority, system, method, etc.). Also, it does not have to be directly related to rule formation. For example, it may include information that was not ultimately related to rule formation, and may be information that may be related to rule formation at the time of collection. Furthermore, it is a concept that includes values and information that can be converted into information related to rule formation. For example, greenhouse gas emissions, emission reduction targets, years for targets, etc.
"Rule information" includes information about rule formation, and further includes, for example, text data, file information, a keyword (text) for identifying a document file from within a web page, and a including metadata (for example, HTML tag information) to be used.
"Concise information" is information formed based on predetermined information extracted and acquired from the rule information website, and technical information and academic information websites in addition to the rule information. For example, the publication date, title, and country/organization name where the content was published. In addition to these, for example, at least one of place names, person names, and keywords extracted from the content may be included. Furthermore, for example, at least one of the URL of the WEB site, an abstract, and a part of the abstract may be included.

(2) Such a rule watch method comprises the steps of sorting the collected rule information into predetermined categories based on sorting conditions, and forming the concise information from the sorted rule information. It is preferable to be

(3) Further, in order to align the languages after the selecting step, if the collected rule information includes a language different from the predetermined language, the step of translating into the predetermined language based on translation conditions is selected. It is preferably provided before the step.

(4) In addition, at least the number of user comments, the number of reactions, the number of clicks on a link for accessing the corresponding rule information, and the number of unfolded display corresponding to the posted concise information. It preferably comprises the step of measuring the prominence of said corresponding rule information on a one-by-one basis.

(5) Further, it is preferable to include the step of judging the degree of progress of the rule formation based on the organization information including the organization from which the rule information is collected.

(6) The rule watch system of the present invention collects information on rule formation such as environmental issues, human rights issues, laws and regulations, and standardization published via the Internet based on collection conditions including pre-registered collection destinations. a crawler server comprising: collecting means for collecting rule information including rule information; selection means for selecting rule information related to a predetermined category from the rule information obtained based on selection conditions, simplification means for forming concise information based on predetermined information acquired from the selected rule information, and the rule information managing a server equipped with progress measuring means for measuring the progress of the rule formation based on organizational information including the organization from which the information is collected, and an SNS site for posting the concise information as the first post; and the number of comments and reactions of the user corresponding to the posting means that makes the initial posting and the concise information posted, the number of clicks on the link for accessing the corresponding rule information, and the folding display. and an SNS server comprising an attention level measuring means for measuring an attention level of the corresponding rule information based on at least one of the number of released rules.

"Organizational information" is information about an organization that collects rule information. For example, if the collected rule information is website content, the organization name that created the website content, This is a concept that includes information such as organization names. Furthermore, it is a concept that includes information that can be converted into an organization name.
"Collecting means" corresponds to step S1 (see FIG. 4) in the embodiment.
"Translation means" corresponds to step S3 (see FIG. 4) in the embodiment.
"Sorting means" corresponds to step S5 (see FIG. 6) in the embodiment.
"Simplified means" corresponds to step S6 (see FIG. 6) in the embodiment.
"Posting means" corresponds to step S11 (see FIG. 6) in the embodiment.
In the embodiment, step v3 (see FIG. 14) corresponds to the 'attention degree measuring means'.
"Progress measuring means" corresponds to step w2 (see FIG. 15) in the embodiment.

(7) The server of the present invention is a server that is provided with an SNS site for posting as the first post, forms the information to be posted, and has a collection condition including a pre-registered collection destination. Based on the selection conditions, rule information including information related to rule formation such as environmental issues, human rights issues, laws and regulations, and standardization collected through the Internet and published via the Internet and a simplification means for forming concise information based on predetermined information obtained from the selected rule information.

(8) Such a server preferably comprises progress determination means for determining the progress of rule formation based on organization information including an organization from which the rule information is collected.

(9) The SNS server of the present invention is an SNS server that manages an SNS site for posting as the first post, and is collected based on collection conditions including pre-registered collection destinations, and via the Internet. From the rule information including information on rule formation such as environmental issues, human rights issues, laws and regulations, standardization, etc., which are published on the It is characterized by comprising posting means for posting concise information formed by acquiring predetermined information to the SNS site as the initial posting.

(10) Such an SNS server preferably comprises request means for requesting the addition of the collection destination so as to make the user of the SNS make a request.
"Request means" corresponds to step T1 (see FIG. 11) in the embodiment.

(11) Further, it is preferable to have a forum forming means for forming a forum in which specific users of the SNS can comment on the predetermined rule information so that users of the SNS can create the forum.
"Forum forming means" corresponds to step U4 (see FIG. 12) in the embodiment.

(12) In addition, at least one of the number of comments corresponding to the posted concise information, the number of reactions, the number of clicks on the link for accessing the corresponding rule information, and the number of times the folded display is canceled. It is preferable to further include attention measuring means for measuring the attention of the concise information based on.

(13) A server program of the present invention is a server program that is provided with an SNS site for posting as the first posting and that forms the information to be posted, wherein Rule information that is collected based on collection conditions including destination and published via the Internet, including information on rule formation such as environmental issues, human rights issues, laws and regulations or standardization, is classified into predetermined categories based on selection conditions , and the selected rule information is formed into concise information.

(14) Such a server program preferably determines the degree of progress of rule formation based on organization information including an organization from which the rule information is collected.

(15) The SNS program of the present invention is an SNS server program used as an SNS server for managing an SNS site for posting as the first posting and for posting the information to be posted to the SNS site, the computer 2, collect based on collection conditions including pre-registered collection destinations, and select from rule information including information on rule formation such as environmental issues, human rights issues, laws and regulations, standardization, etc. published via the Internet Selecting rule information related to a predetermined category based on conditions, and posting concise information formed by acquiring predetermined information from the selected rule information to the SNS site as the first post. is characterized by

(16) Such an SNS program includes the number of comments corresponding to the posted concise information, the number of reactions, the number of clicks on the link for accessing the corresponding rule information, and the number of times the folding display is canceled. Preferably, the degree of attention of the corresponding rule information is measured based on at least one of them.

(17) Such a rule-watching method is a rule-watching method executed by one or more computers, and includes technical information related to the practical application of technology, such as press releases or technology investments related to science and technology. a step of collecting the technical information and the academic technical information from the Internet based on pre-registered collection conditions including a collection destination of academic information related to technological progress such as related papers or patent documents; and the rule information; a step of acquiring co-occurring word groups from the collected technical information and academic technical information, and calculating similarity among information in the rule information, the technical information and the academic information based on the degree of similarity of the respective co-occurring word groups; obtaining the degree.

“Information on the practical application of technology” refers to information for the practical application of knowledge in a specific field and methods of applying scientific knowledge to engineering, not at the stage of experiments or theory, but in terms of actual use and usefulness. This is information about what to do. For example, there are press releases on company technology, information on company technology posted on the company's website, and information posted on the website of a technology fund, such as a public-private fund. Also, it does not have to be directly related to the practical application of the technology. For example, it may include information that was not ultimately relevant to the commercialization of the technology, and may be information that, at the time it was collected, may be relevant to the commercialization of the technology. Furthermore, it is a concept that includes values and information that can be converted into information on the practical application of technology. For example, it includes the personnel, funds, and time required for practical application of the technology, as well as information on the development of elemental technologies required for practical application.

"Technical information" includes information about the practical application of technology, and further includes text data and file information, including keywords (text) for identifying document files from within web pages, document files , including metadata (for example, HTML tag information) associated with the .

"Information on technological progress" includes academic information necessary for the practical application of technology, including natural sciences such as astronomy, physics, chemistry, geology, and biology, as well as mechanical engineering, civil engineering, electronic engineering, etc. It is the information of documents such as published papers, published patents and utility models in the field of engineering. Also, it does not have to be directly related to technological progress. For example, it may include information that was not ultimately related to technological progress, and may be information that may be related to technological progress at the time of collection. Furthermore, the information does not have to be the latest papers/documents, and may include information on past papers/documents that have been found to be used in a specific technology. Furthermore, it is a concept that includes values and information that can be converted into information on technological progress. For example, public-private fund press releases and public offering information.

"Scholarly information" includes information on the progress of technology, and further includes text data, file information, keywords (text) for identifying document files from within web pages, and It includes associated metadata (for example, HTML tag information) and the like.

(18) Further, the degree of similarity is indicated by the thickness or length of a line connecting similar display elements among the display elements respectively indicating the rule information, the technical information, and the academic information, and the degree of similarity is indicated by the display unit of the user terminal. preferably comprising the step of displaying the

(19) A step of sorting the collected rule information, technical information and academic information into predetermined categories based on sorting conditions; Alternatively, it is preferable to include the step of displaying a graph having an axis showing the categories and a time axis.

(20) Another aspect of the rule-watching method of the present invention is a rule-watching method executed by one or more computers, wherein rule information, scientific Based on pre-registered collection conditions, including collection destinations for technical information related to the practical application of technology, such as technology-related press releases or technology investment, and academic information related to technological progress, such as scientific and technological papers or patent documents. , collecting the rule information, the scientific and technical information, and the academic information from the Internet; obtaining co-occurring word groups from the rule information, the collected technical information, and the academic technical information; and obtaining a degree of similarity between information in the rule information, the technical information, and the academic information based on the degree of similarity of word groups.

(21) The user terminal of the present invention includes rule information related to rule formation such as environmental issues, human rights issues, laws and regulations or standardization, technical information related to practical use of technology such as press releases or technology investment related to science and technology It is a user terminal that is communicatively connected to a server that collects academic information on the progress of technology such as papers or patent documents related to operation input information acquisition means for acquiring operation input information including a country name or a technical theme name by user operation; and the rule information, the technical information, or the rule information created by the server and corresponding to the operation input information and a display unit for displaying a screen showing the number of academic information in chronological order.

"Input information acquisition means" corresponds to step S13 (see FIG. 19) in the embodiment.
In the embodiment, step S19 (see FIG. 23) corresponds to the 'operation input information obtaining means'.
"Co-occurrence word acquisition means" corresponds to step S12 (see FIG. 18) in the embodiment.
"Similarity acquisition means" corresponds to step S14 (see FIG. 19) in the embodiment.
In the embodiment, step S15 (see FIG. 19) corresponds to the 'importance degree acquisition means'.
In the embodiment, step S17 (see FIG. 19) corresponds to the 'person/organization importance degree means'.
"Screen creating means" corresponds to step S16 (see FIG. 19) in the embodiment.
In the embodiment, step S21 (see FIG. 23) corresponds to the 'collection number acquisition means'.
In the embodiment, step S22 (see FIG. 23) corresponds to the 'collection screen acquisition means'.
"Display means" corresponds to step S23 (see FIG. 23) in the embodiment.

The rule watch system and the like of the present invention can facilitate grasping of information regarding rule formation. In addition, it is possible to easily grasp the trend of technology investment and technology development in each country, and to easily grasp the relationship between rule information, technical information, and academic information.

FIG. 1 is a schematic diagram showing the environment in which the rule watch system of the present invention is used. FIG. 2 is a functional block diagram showing one embodiment of the rule watch system. FIG. 3a is a schematic diagram showing an example of the hardware configuration of a server, and FIG. 3b is a schematic diagram showing an example of the hardware configuration of a user terminal. FIG. 4 is a flow chart showing an embodiment of the processing flow of the server. FIG. 5 is a schematic diagram showing how publication dates are arranged in a predetermined format. FIG. 6 is a flow chart showing an embodiment of the processing flow of the server. FIG. 7 is a schematic diagram showing the data structure of a sorting table showing sorting conditions. FIG. 8 is a schematic diagram showing the data structure of a classification table indicating classification conditions. FIG. 9 is a schematic diagram showing an embodiment of a screen displayed on a user terminal of an SNS user. FIG. 10 is a schematic diagram showing one embodiment of a screen showing a state in which the screen of FIG. 9 is folded and displayed. FIG. 11 is a flow chart showing an embodiment of the process flow of the SNS server. FIG. 12 is a flow chart showing an embodiment of the process flow of the SNS server. FIG. 13 is a schematic diagram showing an embodiment of the entire screen displayed on the user terminal of the SNS user. FIG. 14 is a flow chart showing an embodiment of the process flow of the SNS server. FIG. 15 is a flow chart showing an embodiment of the processing flow of the server. FIG. 16 is a schematic diagram showing an example of stages of progress of rule formation. FIG. 17 is a functional block diagram showing another embodiment of the rule watch system. FIG. 18 is a flow chart showing an embodiment of the processing flow of the server and analysis server. FIG. 19 is a flow chart showing an embodiment of the processing flow of the analysis server. FIG. 20 is a correlation diagram showing the relationship among rule information, technical information and academic information. FIG. 21 is a schematic diagram illustrating an embodiment of a display element, a link display element, a person/organization display element, and a person link display element. FIG. 22 is a person correlation diagram showing the relationship among rule information, technical information, academic information, and person/organization information. FIG. 23 is a flow chart showing an embodiment of the processing flow of the user terminal and analysis server. FIG. 24 is a schematic diagram showing an embodiment of a trend screen displayed on a user terminal. FIG. 25 is a schematic diagram showing another embodiment of the trend screen displayed on the user terminal

[1. Outline explanation]
First, the rule watch system of the present invention will be explained using FIG. A rule watch system (hereinafter referred to as system) 10 shown in FIG. collect from Generally, the information 13 on rule formation is complicated with various formats and the content is specialized, so it tends to be known only to a limited number of people or difficult to understand. be.

The present system 10 simplifies information 13 regarding domestic and foreign rule formation, and posts the information 13 to a SNS (social network service) site 14a prepared for posting the information 13. FIG. In general, SNS has functions such as transmission, sharing, and diffusion of information. Therefore, it is possible to encourage companies, researchers, and citizens as users 15 in various positions belonging to the SNS to deal with social issues with an Outside-in Approach that transcends cross-cutting fields.

In addition, the user 15 can easily access the information 13 related to rule formation, send comments, and share/spread the comments/information 13 . For example, the content of comments on a specific rule formation, the expression of attitudes by reactions, and the number of comments indirectly indicate reactions such as interest, suspicion, and caution toward the rule formation. By observing the reaction of these SNS users 15, it is possible to notice important signs of rule formation, such as whether the rule formation should be welcomed or rule formation that requires vigilance. Formation can be monitored.

(Rule watch system 10)
A system 10 according to one embodiment of the present invention is described using the functional block diagram of FIG. The system 10 shown in FIG. 2 includes a crawler server 9 that collects rule information 13 on the Internet 12, a server 1 that acquires the rule information collected by the crawler server 9, and the server 1 connected to the Internet 12 (a communication network). ) and the SNS server 14 communicably connected thereto. In this embodiment, an administrator terminal 10a (see FIG. 1) operated by an administrator is communicably connected to the system 10. FIG. The administrator terminal 10a transmits modifications of programs, conditions, etc. by the administrator to the crawler server 9, the server 1, and the SNS server 14. FIG.
In this embodiment, the first storage unit 7 and the second storage unit 8 are provided as external data servers.

(collection destination 11)
In this embodiment, the collection destination 11 (see FIG. 1) corresponds to, for example, major national parliaments, administrative branches, the Supreme Court, the United Nations, research institutes, and WEB sites of major NGOs. In addition, academic information, technology investment information, and WEB sites of companies judged to be involved in rule formation may be included.

(Rule information 13)
The rule information 13 includes, for example, text data, image data, moving image (video) data, voice (recorded data) data published on the website of the collection destination 11, SNS, etc., as well as files thereof, text files, and images. Files, motion picture (video) files, audio (recorded data) files, etc. are included. In addition, transcription information from e-mail magazines and video/audio data may be included.

[2. Each configuration]
(server 1)
An embodiment of the crawler server 9 is shown in FIG. The crawler server 9 is, for example, a personal computer in this embodiment. The crawler server 9 shown in FIG. 2 comprises collection means 2 and translation means 3 .

(Collection means 2)
The collection means 2 collects the rule information 13 based on the collection conditions 2a (see FIG. 4). The collecting means 2 is called a crawler, for example, and collects text data from predetermined sites such as WEB sites and SNS. The text data includes text content of the website and metadata. The metadata is not displayed to the viewer of the content on the web browser, and includes, for example, the title, the length of the content document, the author, the name of the organization, the date of publication, the date and time of creation, the date and time of update, keywords, the summary of the content document, It contains information such as an abbreviated version of the summary.

The collection conditions 2a are stored in the memory of the crawler server 9 (see FIG. 3a). The collection condition 2a describes the URL of the site to be collected. For information to be collected, for example, text information, title, organization name, and release date, whether to be obtained from the content of the website or from the metadata is determined for each site according to the collection condition 2a.

(translation means 3)
The translation means 3 translates the rule information 13 into a predetermined language based on the translation conditions 3a. Then, the translated rule information 13 is stored in the first storage unit 7 . In this embodiment, languages other than English are translated into English. As the translation means 3, a conventionally known translation program may be used. As translation means, translation into other languages such as Japanese may be used. The rule information 13 collected from all over the world is translated into a predetermined language, that is, a common language. Based on the common language, a series of processes after the selection means 4 are performed.

(Translation condition 3a)
The translation conditions 3a are stored in the storage section of the server 1 (see FIG. 3a). The translation condition 3a includes, for example, a dictionary table for translating technical terms. In addition, it includes a dictionary table for eliminating fluctuations in organization names and their abbreviations, a dictionary table for eliminating fluctuations in national federations and country names, and so on.

(server 1)
An embodiment of the server 1 is shown in FIG. The server 1 is, for example, a personal computer in this embodiment. The server 1 shown in FIG. 2 comprises sorting means 4 and simplification means 5 . Furthermore, in this embodiment, cleansing means 17 , tag means 18 and progress determination means 29 are provided.

(Sorting means 4)
A selection means 4 selects rule information related to a predetermined category from the translated rule information 13 based on a selection condition 4a.

(Selection condition 4a)
The selection conditions 4a are stored in the storage unit of the server 1 (see FIG. 3a). A keyword for sorting is registered in the sorting condition 4a. In this embodiment, the selection conditions 4a are created in the language to be translated, that is, in English.

(Simplified means 5)
A simplification means 5 forms concise information 5 a based on predetermined information obtained from the selected rule information 13 .

(Cleansing means 17)
The cleansing means 7 performs data cleansing processing. From the data containing the rule information 13 stored in the second storage unit 8, duplications, inconsistencies in notation, etc. are searched for, and deletion, correction, normalization, etc. are performed. Note that errors may be searched for and deleted, corrected, or normalized.

(Tag means 18)
The tag means 18 classifies the keywords acquired by the simplification means 5 into predetermined topics based on the classification conditions 18a. Next, the rule information 13 is tagged with topics and stored in the second storage unit 8 .

(Progress determination means 29)
The progress determination unit 29 determines the progress of rule formation based on the organization (reference numeral 25d in FIG. 9) that is the collection destination 11 of the rule information 13 (see FIG. 1).

(SNS server 14)
The SNS server 14 is, for example, a personal computer in this embodiment. The SNS server 14 manages the SNS site 14a (see FIG. 1). The SNS server 14 includes posting means 6 , forum forming means 19 , requesting means 20 and attention measuring means 28 .

(SNS site 14a)
SNS is an abbreviation for social networking service. Usually, it is a membership-based service of a WEB site where users can interact with each other. A typical SNS can have a page on which a person's profile and photos are posted. The page has a message function, a chat function, a group function (refer to forums such as reference numeral 43a in FIG. 13) in which information and files can be exchanged only among specific friends. In addition, there is a diary function that can limit the range to be disclosed, and functions can be expanded by installing applications. It should be noted that the user may be required to perform a predetermined registration before using the service.
The SNS site 14a used in this embodiment is a site on the WEB where users can interact with each other. For example, a function of commenting on the concise information 5a (see reference numeral 27a in FIG. 9), a function of selecting pre-registered comments that the user may be concerned about (see reference numeral 27b in FIG. 9), and other It has a function of sharing on SNS (see symbol 27c in FIG. 9) and a function of reacting to comments or brief information 5a (see symbol 27d in FIG. 9).

(Posting means 6)
The posting means 6 posts brief information 5a as the first post to the SNS site 14a for each category selected by the selecting means 4. - 特許庁The first posting means setting up a thread on the SNS site 14a. In this embodiment, the posting means 6 puts up concise information 5a as a thread for each category.

(Forum formation means 19)
The forum forming means 19 forms a forum in which specific SNS users 15 and 15 can comment based on the forum forming operation of the SNS user 15 .

(Request means 20)
The request means 20 transmits the addition of the desired collection destination of the rule information 13 to the crawler server 9 based on the request operation of the SNS user 15 . The addition of the collection destination may be transmitted to the administrator terminal 10a and transmitted to the crawler server 9 after confirmation by the administrator.

(Attention measuring means 28)
The attention degree measuring means 28 measures the number of comments and reactions by the user 15 corresponding to the posted concise information 5a, the number of clicks on the link for accessing the corresponding rule information, and the cancellation of the folding display (see FIG. 10). Based on at least one of the determined numbers, the degree of attention of the corresponding rule information is measured.

(User terminal 16)
The user terminal 16 has a display section 16a. In this embodiment, it is a smart phone, for example. A mobile phone, a tablet terminal, a personal computer, or the like may be used.

(Display unit 16a)
As the display unit 16a, for example, a device that displays a screen such as a liquid crystal display (LCD), a plasma display (PDP: plasma display panel), or an organic EL (EL: electroluminescence) is used. The user 15 can operate the user terminal 16 by pressing and touching the display section 16a with a finger or the like. Through the operation, the user terminal 16 can acquire information (to be described later) to be input via the user 15 .

[3. Hardware configuration]
Next, the hardware configuration of the server 1, the crawler server 9 and the SNS server 14, that is, the servers 1, 9, 14 and 45 (described later with reference to FIG. 17) will be described with reference to FIG. 3a. Further, the hardware configuration of the user terminal 16 will be described with reference to FIG. 3b.

(Hardware configuration of server 1 (9, 14, 45))
The servers 1, (9, 14, 45) of this embodiment use personal computers, for example. The personal computer comprises a CPU 30, as shown in FIG. 3a. A memory 31 , a connection port 33 for connecting/reading a recording device 32 and the like, and a communication circuit 34 for communicating with the outside via a network are connected to the CPU 30 via a bus line 35 . The memory 31 stores the conditions 4a, (2a, 3a), a server program 36 (36a to m) for processing the system of the present invention, a browser program 37, and an OS 38 (operating system). .

In this embodiment, the server program 36 operates in cooperation with the functions of the OS 38 and the browser program 37 . The server program 36 may operate independently without using the browser program 37 and OS 38 . Conditions 4a, (2a, 3a), server program 36, browser program 37 and OS 38 are installed in memory 31 by device 32 through communication circuit 34 or through connection port 33, for example by downloading.

(Hardware Configuration of User Terminal 16)
Next, the hardware configuration of the user terminal 16 will be explained. The hardware configuration of the user terminal 16 is substantially the same as the hardware configuration of the server 1 described above. Reference numeral 36n is a user terminal program.

In the above-described hardware configuration, the functions shown in FIG. 2 are realized by using, for example, the CPU 30 and the program 36. Some or all of them are implemented by a logic circuit such as a microcomputer, or a PLC (programmable logic controller). ) may be used for sequence control.

[4. program]
(Flow chart for acquiring rule information 13)
FIG. 4 is a flowchart illustrating one embodiment of the processing of crawler program 36a used in crawler server 9 of system 10. As shown in FIG. FIG. 4 is a flowchart mainly for acquiring the rule information 13. As shown in FIG. Technical information and academic information will be described later.

(S1) The CPU 30 (see FIG. 3a) of the crawler server 9 collects rule information 13 from WEB pages published on the Internet 12 based on the collection conditions 2a. In this embodiment, text data and files are collected as the rule information 13 . Furthermore, the text information, title, organization name, and release date are extracted as collected information 2b from the text data, files, and the like. Furthermore, as the collection information 2b, the URL of the collection destination is acquired from the collection condition 2a.
Here, the text information is the text content of the WEB site, and the title is the title attached to the text data. An organization name is a subject that has disclosed text data, such as an individual, an organization, or a company. The publication date is the date on which the text data is published on the Internet.
In addition, tag information, event information, trial status information, etc. may be collected as keywords of text content.

(S2) Store the collected rule information 13 in the first storage unit 7. FIG. At this time, the collected information 2 b is stored in the first storage unit 7 in association with the collected rule information 13 .
The collection condition 2 a defines a condition for storing the collected rule information 13 in the first storage unit 7 . In this embodiment, for example, the first storage unit 7 is checked to see if the title, release date, and organization name obtained from the acquired rule information 13 all match, and if not, it is stored. This prevents collection of identical sentences.

(S3) Acquire the rule information 13 from the first storage unit 7 and translate it into English based on the translation condition 3a. Incidentally, the collected information 2b may be translated into a predetermined language. Subsequent processing takes place after translation into a common language.

Next, FIG. 5 is a schematic diagram showing how the publication date is arranged in a predetermined format. As shown in FIG. 5, various release date data 21 are arranged in a predetermined format based on a date table 22 provided for each language and stored in the first storage unit 7 . The date table 22 is included in the collection condition 2a.

(S4) Store the translated rule information 13 in the first storage unit 7. FIG.

(Flowchart for simplifying and posting rule information 13)
FIG. 6 is a flow chart showing an embodiment of processing of the server program 36 and SNS server program 36b used in the server 1 and SNS server 14, respectively. FIG. 6 is a flow chart mainly for simplifying and posting the rule information 13 .

(S5) The rule information 13 is acquired from the first storage unit 7, and the rule information 13 related to a predetermined category is selected based on the selection condition 4a.
In this embodiment, for example, the rule information 13 related to the climate crisis category is selected from the rule information 13 (see FIG. 1). The selected rule information 13 is tagged with a climate crisis tag (category) 4b (described below). The rule information 13 is divided for each category.

FIG. 7 shows the data structure of the selection table indicating the selection conditions 4a. The sorting table shown in the drawing is prepared for each category 4b. The figure shows the sorting table when the category is climate crisis.
In the selection table, one or more specific category keywords 4c are described for one category 4b (simply referred to as keyword 4c). If a specific keyword 4c exists in the text information of the rule information 13, the corresponding category 4b is determined based on the selection table. In this embodiment, the category 4b is determined by the presence of one keyword 4c in the text information of the rule information 13, and the category 4b is determined by the presence of a set of two keywords 4c. There is. Note that the category 4b may be determined based on the existence of a set of three or more keywords 4c in the text information of the rule information 13. FIG.

(S6) Returning to FIG. 6, the concise information 5a is created from the rule information 13. FIG. In this embodiment, keywords are extracted from the text information of the rule information 13 by machine learning, and a summary and text information of a predetermined number of characters at the beginning of the summary (hereinafter referred to as simplified summary text) are created.

Keywords to be extracted include the title of the rule information 13, the name of the organization as the collection destination 11, the publication date, where the article is directed (which country), and further, the name of the person extracted from the text information of the rule information 13. Names of places and organizations extracted from A plurality of personal names, place names, and organization names may be used. The URL of the collection destination 11 is acquired from the collection information 2b. In addition, the names of laws and regulations may be extracted. Note that the title, organization name, and release date may be acquired from the collected information 2b (see FIG. 4).
Machine learning, for example, is used to extract the keywords. That is, machine learning is performed to infer whether a keyword belongs to the type of keyword to be extracted. The trained calculation model can classify the keyword by analogy to which keyword type the keyword corresponds to, even if it is a word that is seen for the first time. The computational model has a function of scoring the degree of similarity as the degree of confidence in word analogy and showing it at the same time.
For example, a method for generating a computational model for extracting "organization name" will be described. First, training data is created by pairing keyword type label information with multiple data corresponding to keyword types to be classified, such as "organization name", "person's name", and "words related to law", or data that does not correspond to any of them. prepared in advance as The language data (character data) dealt with in this case cannot be interpreted by a computer (computer) as it is. When a vector of similar training data is input to the computational model, the computational model calculates and outputs the degree of confidence of matching the input vector to the classification type. The resulting output vector is a numerical value (confidence) that indicates the degree of similarity of the classification types. On the other hand, when a plurality of dissimilar learning data are input, a vector is generated that indicates that the corresponding classification does not correspond to the learning data. Regarding the output result, the calculation model is corrected and optimized so that the reliability of the paired label information for all the input data is increased. In the computational model generated in this way, selecting input data that provides an output of "organization name" with a high degree of certainty is extraction of "organization name."
Machine learning can also be performed on a general-purpose computer outside the present system at any time by preparing learning data for each keyword type. By switching the calculation model used in the present system to a separately generated calculation model with improved classification analogy accuracy, the present system can appropriately optimize keyword extraction.

In this embodiment, the concise information 5a includes the publication date, title, name of country/organization where the content was published, name of place extracted from the content, name of person, keyword, URL of the WEB site, and brief summary text. consists of Note that other information may be added.

(S7) The concise information 5a is linked to the rule information 13 and stored in the second storage unit 8. FIG.

(S8) Acquire the rule information 13 from the second storage unit 8 and perform data cleansing.

FIG. 8 shows the data structure of the classification table showing the classification conditions 18a. The illustrated classification table 18a consists of categories 4b, keywords 18b, and tags 18c corresponding to the keywords 18b.

(S9) Returning to FIG. 6, the keywords extracted in step S6 are classified into tags 18c indicating predetermined topics based on the classification conditions 18a.

(S10) The tagged rule information 13 is stored in the second storage unit 8. FIG.

(S11) The CPU of the SNS server 14 acquires the concise information 5a from the second storage unit 8 and posts it to the SNS site 14a as the first post. That is, on the SNS site 14a, concise information 5a is set up as a thread for each category 4b.

FIG. 9 is a schematic diagram showing one embodiment of the screen 16a displayed on the user terminal 16 of the SNS user 15. As shown in FIG. The posting screen 23 is shown in FIG. The posting screen 23 is divided into an upper stage, a middle stage, and a lower stage. The upper part is the common screen part 24 , the middle part is the extracted keyword screen part 25 , and the lower part is the summary screen part 26 .

(Common screen section 24)
The common screen portion 24 is composed of a poster screen portion 24a indicating a poster and a posting date/time screen portion 24b indicating a posting date/time. In the embodiment, the poster is an automatic posting robot (SNS server program 36b).

(Extracted keyword screen part 25)
The extracted keyword screen portion 25 includes a title screen portion 25a displaying the title of the rule information 13, a screen portion 25b indicating the release date of the rule information 13, and indicating to which country the article is directed. A screen portion 25c, a screen portion 25d showing the organization name of the rule information 13, a screen portion 25e showing the keyword 18b extracted from the rule information 13, a screen portion 25f showing the person name extracted from the rule information 13, and extraction A screen portion 25g showing the selected place name, a screen portion 25h showing the extracted organization name, a screen portion 25i showing the keyword 4c that is the basis of the selected category 4b (see FIG. 7), and reference numerals 25d to 25i. It is composed of a folding display screen portion 25j which is a clickable portion for folding and displaying the display of the screen portion.

(Title screen portion 25a)
The title screen portion 25 a is linked to the HP (homepage) of the collection destination 11 of the rule information 13 .

(Summary screen section 26)
The summary screen section 26 includes an icon screen section 26a that displays icons indicating collection destinations 11, a title screen section 26b that displays titles, a URL screen section 26c that displays URLs, and a simple screen that displays simple summary text. It consists of a section 26d, a tag screen section 26e for displaying the tag 18c (see FIG. 8), and an input screen section 26f for allowing the user to input.

The icon screen portion 26a, the title screen portion 26b, and the URL screen portion 26c are linked to the HP (homepage) of the collection destination 11. FIG.
The tag screen portion 26e sorts and displays the rule information 13 of the same tag 18c when clicked.
The input screen portion 26f is for inputting by the user 15, and a reaction to the posted rule information 13 is input. For example, we call them actions by the user.

Reference numeral 27a is a screen portion for writing comments. When the comment screen portion 27a is clicked, a comment entry column is displayed. Comments can be entered by the user 15 .

Reference numeral 27b is a concern screen portion that indicates concerns. When the user clicks on the concern screen portion 27, a plurality of comments that the user is likely to feel anxious about are listed. User 15 clicks on a comment that seems to match.
For example the comment is:
・It may not be related to the topic...
・I feel uncomfortable...
・It might be spam...
・It may be fake news...
・It might be a scam…
・This post may be banned...
-Maybe violent...
・There is a lack of information. (For example, it is written as NAN)
・Other concerns that you would like to inform the administrator

Reference numeral 27c is a share screen portion for sharing. By clicking the share screen portion 27c, the concise information 5a or information related to the concise information 5a can be shared with other SNSs registered by the user 15. FIG. For example, the information displayed on the summary screen portion 26 is shared.

Reference numeral 27d is a reaction screen portion showing reactions. When the reaction screen portion 27d is clicked, a plurality of illustration screens showing feelings that the user is likely to feel are listed. When the user 15 clicks an illustration screen that seems to match, the number of clicks is displayed together with the illustration screen. A number is added each time the same screen is clicked.
For example, the feeling shown by the illustration screen is as follows.
・Iine (as an indication of goodness)
・Horebore (as something that shows emotion)
Ahaha (as an indication of laughter)
・NICEWATCH (as an indication of the desire to pay attention as a rule watch target)
ooh (as an indication of surprise)
・Shikushiku (as an expression of sadness)
Punpun (as an expression of anger)

Posting to the SNS site 14a is performed, for example, once a day at a predetermined time. At that time, the server 1 transmits a brief summary text (see reference numeral 26d in FIG. 9) corresponding to the concise information 5a posted to the SNS user's 15 e-mail address. This notifies the user 15 of the posting. You may post multiple times in one day.

FIG. 10 is a schematic diagram showing one embodiment of a screen showing a state in which the screen of FIG. 9 is folded and displayed. Reference numeral 25k is an unfolding screen portion. When the unfolded screen portion 25k is clicked, screen portions 25d to 25i (see FIG. 9) are displayed.

(Flow chart for requesting collection destination of rule information 13)
FIG. 11 is a flow chart showing an embodiment of processing of the SNS server program 36c used in the SNS server 14. As shown in FIG. FIG. 11 is a flow chart mainly for requesting the collection destination of the rule information 13 .

(T1) The user terminal 16 transmits a form request command for adding the collection destination 11 to the SNS server 14 . For example, a button for addition may be provided on the entire screen (see FIG. 13), and a form request may be commanded by clicking the button.

(T2) A form for adding the collection destination 11 is sent from the SNS server 14 to the user terminal 16 .

(T3) The user 15 inputs information on the collection destination. The input collection destination information is transmitted to the SNS server 14 .

(T4) Information on the collection destination is transmitted to the administrator terminal 10a (see FIG. 1).

(T5) The collection destination is confirmed by the administrator.

(T6) Send the confirmed collection destination to the crawler server 9 and add it to the collection condition 2a (see FIG. 4).

(Flowchart requesting forum formation)
FIG. 12 is a flow chart showing an embodiment of processing of the SNS server program 36d used in the SNS server 14. As shown in FIG. FIG. 12 is a flow chart that mainly requests the creation of a forum. Here, first, the home screen (entire screen) will be described in order to facilitate understanding of the formation of the forum.

FIG. 13 is a schematic diagram showing an embodiment of the entire screen displayed on the user terminal 16 of the SNS user 15. As shown in FIG. The whole screen 40 is shown in FIG. The entire screen 40 is divided into left and right. It consists of a right screen 41 and a left screen 42 . The right screen 41 displays the post screens 23 in chronological order. When the right screen 41 is scrolled downward, the posting screen 23a posted in the past is displayed.

(Left outer surface portion 42)
The left screen 42 consists of a common screen portion 42a and a forum screen portion 42b.

(Common screen section 42a)
The outline home characters in the common screen portion 42a indicate that the home screen (entire screen) is currently selected. For example, when the event calendar 42b is selected, the calendar is displayed on the right screen 41 (not shown).

(Forum screen portion 42b)
The forum screen portion 42b displays an already launched forum. The forum screen portion 42b includes a rule trend screen portion 43a, a social issue screen portion 43b, a project screen portion 43c, and an expert screen portion 43d.

(Rule trend screen section 43a)
In this embodiment, four forums are set up as the rule trend screen portion 43a. Each forum is organized by category 4b (see FIG. 8). For example, when Climate Crisis is clicked, brief information 5a (see FIG. 6) with Climate Crisis as a category is displayed. These forums are set up by administrators. In addition, the SNS user 15 may launch.

(Social issue screen part 43b)
The social issue screen portion 43b is a forum launched by the SNS user 15. FIG. This is a room where SNS users 15, 15 discuss common issues. For example, clicking on ESG/Investment Responsibility/Social Impact Investment in the figure displays a chat room on the right screen 41 .

(Project screen portion 43c)
The project screen portion 43c is a forum formed when, for example, a forum formed in the social issue screen portion 43b is discussed between users and a specific project is tackled.

(Expert screen section 43d)
The expert screen portion 43d is a forum for discussion between the SNS user 15 and experts.

Returning to FIG. 12, (U1) the user terminal 16 transmits a form request command for forming a forum to the SNS server 14 .

As shown in FIG. 13, the + display screen section (see reference numeral 39) on the right side of the social issue screen section 43b, the project screen section 43c, and the expert screen section 43d is an additional screen for requesting the formation of a forum. 39. By clicking on the add screen portion 39, a form request is commanded.

Returning to FIG. 12 again, (U2) the SNS server 14 transmits a form for forming a forum to the user terminal 16 .

(U3) The user 15 inputs information for forming the forum. The entered information is transmitted to the SNS server 14 .
For example, the information to be entered is as follows.
・Forum name ・Forum description ・Set the public range of the forum
・How the content will be viewed (for example, whether forum members are restricted or access is restricted)
・Participation method (invitation system, invitation and request, or whether anyone can participate)

(U4) Display a new forum.

(Flowchart for judging attention level of rule information 13)
FIG. 14 is a flow chart showing an embodiment of processing of the SNS server program 36e used in the SNS server 14. FIG. FIG. 14 is a flowchart mainly for judging the degree of attention.

(v1) Each time the SNS user 15 takes an action, the user terminal 16 sends that action to the SNS server 14 . The SNS server 14 receives the action.
For example, when a comment is entered in the comment screen portion 27a, the reaction screen portion 27d is clicked, the link 26c (see FIG. 9) for accessing the corresponding rule information 13 is clicked, or the folding is canceled. , the SNS server 14 receives the information that it happened.

(v2) Count (add) the number of comments, the number of reaction clicks, the number of link clicks, and the number of unfolding.

(v3) The degree of attention is determined based on any one of the number of comments, the number of reaction clicks, the number of link clicks, and the number of unfolding. For example, in the present embodiment, when the total number of comments, reaction clicks, link clicks, and unfolding counts is 10 or less, it is given low attention, up to 100 is given medium attention, and when it exceeds 1000, it is given great attention. These threshold values may be changed. Also, the number of comments, the number of reaction clicks, the number of link clicks, and the number of unfolding may be weighted so that the influence of one of them is greater. Furthermore, one, two, or three of the number of comments, the number of reaction clicks, the number of link clicks, and the number of unfolding may be used to determine the degree of attention. In that case, the above-described threshold value and weighting may be applied to each item to be added or to a plurality of items to be added.

(v4) transmit the degree of attention to the user terminal 16; The degree of attention is displayed on the display unit 16a of the user terminal.

(Flowchart for judging the progress of rule formation)
FIG. 15 is a flow chart showing an embodiment of processing of the server program 36f used in the server 1. FIG. FIG. 15 is a flowchart mainly for judging the progress of rule formation.

(w1) Acquire the organization name 25d (see FIG. 9) that manages the rule information 13 from the concise information 5a.

FIG. 16 is a schematic diagram showing an example of stages of progress of rule formation. The rule-making stage is divided into the first stage of social issues R1, the next stage R2 of the drafting organization, the next stage R3 of parliament, the next stage R4 of administration, and the last stage R5 of courts. Divide. It is determined that the degree of progress is higher from R1 to R5.

(Social issue stage R1)
Stage R1 of the social issue is a stage in which public opinion is aroused. At this stage, NGOs, companies, etc. are disseminating social issues and corresponding new technologies and services. For example, an NGO, a company, or the like becomes an organization for judging the degree of progress. It is progress R1.

(Step R2 for drafting bodies)
The drafting agency phase R2 is the phase in which the drafting bodies are involved. It is the stage where a bill is created as a policy of the government, with the involvement of influential politicians in policy, and diplomatic/external pressure from diplomatic channels. It is also at the stage of holding study sessions with bureaucrats and establishing a committee of experts. Furthermore, petitions and signatures are delivered to lawmakers, and the bill is being drafted. As a bill-making body, for example, the government, study groups with bureaucrats, committees of experts, members of the legislature who drafted the bill, etc., will be organizations for judging the degree of progress. This is progress R2.

(Parliamentary Stage R3)
The parliamentary stage R3 is the legislative stage. For example, the review/amendment of bills by subcommittees and the deliberation of bills by plenary sessions. For example, a subcommittee, a plenary session, etc. will be an organization for judging the degree of progress. This is progress R3.

(Administrative stage R4)
The administrative stage R4 is a stage issued as an order by the administrative authorities. For example, soliciting and replying to public comments, orders, regulations, and subsidies accompanying laws. For example, the government becomes an organization for judging the degree of progress. This is progress R4.

(Court Stage R5)
Court stage R5 is a stage issued as a court decision. Examples include lawsuits, judicial decisions, and judgments on legal deficiencies. For example, a court or the like becomes an organization for judging the degree of progress. This is progress R5.

Returning to FIG. 15, (w2) determine which organization name among R1 to R4 (see FIG. 16) the obtained organization name 25d corresponds to, and determine the degree of progress R1 to R4.

(w3) Store the obtained degree of progress in the second storage unit 8 . At that time, it is associated with the rule information 13 . After that, the progress is posted on the SNS site 14a together with the concise information 5a (not shown).
The obtained progress may be transmitted to the user terminal 16 and displayed on the display unit 16a. At that time, the progress may be transmitted to the user terminal 16 via the SNS server 14 .

[5. Other embodiments]
(Rule watch system 44)
FIG. 17 shows another embodiment of the system 10 previously described. FIG. 17 shows a rule watch system (hereinafter referred to as system) 44 according to another embodiment. Since the system 44 shown in FIG. 17 is substantially the same as the system 10 described above, the same parts are denoted by the same reference numerals and the description thereof is omitted. The illustration of the cleansing means 17, the tagging means 18 and the progress measuring means 29 is omitted in the figure.
For example, system 10 described above processes rule information 13 , while system 44 further processes technical information 56 and academic information 57 . That is, the processing by the collection means 2 based on the collection condition 2a and the translation means 3 based on the translation condition 3a performed in the rule information 13 are performed in the processing of the technical information 56 and academic information 57 by the system 44, respectively. In this embodiment, the collected technical information 56 and scientific information 57 are transmitted to the analysis server 45 and processed (described later).

The system 44 includes a crawler server 9 that collects rule information 13, technical information 56, and academic information 57 on the Internet 12 based on the collection condition 2a (see FIG. 4); and an analysis server 45 that acquires information 57 and is communicably connected via the Internet 12 (communication network) or the like. In this embodiment, the third storage unit 46 is further provided as an external data server.

(1) Overview The system 44 collects technical information 56 and academic information 57 from the collection destination 11 in addition to the rule information 13 . The collected information is analyzed by the analysis server 45 . As a result of the analysis, for example, the degree of similarity between each piece of information and the degree of importance of each piece of information are obtained. The result of the analysis is displayed on the display section 16a of the user terminal 16. FIG. For example, if the similarity is visualized, it is possible to grasp the relationship between each piece of information. For this reason, it facilitates prediction of academic knowledge such as technical fields necessary for rule formation, necessary technical investment fields, and necessary natural sciences. Furthermore, it facilitates grasping or predicting the relevance of the organizations and persons responsible for the necessary technology and academic knowledge.

(collection destination 11)
The collection destination 11 (see FIG. 1) of the technical information 56 includes, for example, press releases on company technology, information on company technology posted on the company's website, information on the website of a technology fund, and the like. In addition, information on websites that are judged to be related to the practical application of the technology may be included.
As the collection destination 11 (see FIG. 1) of the academic information 57, for example, published papers, published patents, utility models, etc. in natural science and engineering such as mechanical engineering, civil engineering, and electronic engineering are posted. It is the information of the WEB site which was made.

(Technical Information 56, Academic Information 57)
The technical information 56 and the academic information 57 are, for example, text data, image data, moving image (video) data, voice (recorded data) data, and files thereof published on the WEB site of the collection destination 11, SNS, etc. This includes text files, image files, motion picture (video) files, audio (recorded data) files, and the like. In addition, transcription information from e-mail magazines and video/audio data may be included.

(2) Each configuration (characteristic word acquisition means 5a)
The server 1 and the analysis server 46 of the system 44 are each equipped with a characteristic word obtaining means 5a. The feature word acquisition unit 5a acquires feature words 52 (see FIG. 18) from the selected rule information 13, technical information 56, and academic information 57, respectively. These characteristic words 52 are associated with the rule information 13 , the technical information 56 and the academic information 57 respectively, and stored in the second storage unit 8 . Note that the server 1 may also have the simplification means 5 as the feature word acquisition means 5a.

(Input information acquisition means 16b, operation input information acquisition means 16c)
The input information acquisition means 16b obtains input information linked to specific information among each of the rule information 13, the technical information 56, and the academic information 57 to be analyzed (for example, the rule information 13a in FIG. 20 described later). 67 (see FIG. 19) is acquired by the input operation of the user 15 . The acquired input information 67 is transmitted to the analysis server 45 by the user terminal 16 .
The operation input information acquisition unit 16c acquires operation input information 68 (see FIG. 23, which will be described later) input to the user terminal 16 by an input operation of the user 15. FIG. The user terminal 16 transmits the operation input information 68 to the analysis server 45 .

(analysis server 45)
The analysis server 45 includes a co-occurring word group acquisition unit 47 that acquires a co-occurring word group 53 (see FIG. 18) from characteristic words 52 of each of the acquired rule information 13, technical information 56, and academic information 57; A similarity acquisition means 48 for acquiring a similarity 54 (see FIG. 19) in the rule information 13, the technical information 56, and the academic information 57 based on the originating word group 53, and connected to information having a similarity equal to or higher than a predetermined level. importance acquisition means 49 for acquiring the importance level 55 (see FIG. 19) of the specific information 13a based on the number; screen creation means 51 for creating display elements to be displayed on the display section 16a; and

(Co-occurrence word group acquisition means 47)
The co-occurring word group acquisition means 47 acquires the co-occurring word group 53 from the feature words 52 of the rule information 13, the technical information 56, and the academic information 57, respectively.

(Similarity acquisition means 48)
The similarity acquisition means 48 acquires the similarity 54 between the information in the rule information 13 , the technical information 56 and the academic information 57 based on the degree of similarity of each co-occurring word group 53 . Furthermore, the number of information (the number of connections) having a predetermined similarity 54 is acquired. For example, in the specific rule information 13a (see FIG. 20), there are five pieces of specific technical information 56a, 56b, 56c, 56d and scientific information 57a as information having a predetermined similarity 54 relationship. That is, the specific rule information 13a is related to five pieces of information with a predetermined degree of similarity of 54, and the number of connections is five.

(Importance acquisition means 49, person/organization importance acquisition means 50)
The importance acquisition means 49 acquires the importance 55 of the corresponding information based on the number of connections (see FIG. 21) 61 . The person/organization importance acquisition unit 50 acquires the person/organization importance 66 (see FIG. 21) of the person name or organization name based on the number of person names or organization names acquired as the co-occurrence word group 53 .

(Screen creation means 51, collection screen creation means 75)
The screen creating means 51 creates a screen for displaying the level of the similarity 54 and the importance 55 on the display unit 16a. The collection screen creation means 75 creates a screen for displaying the level of the number of collections 76 on the display unit 16a.

(4) Program (flowchart for acquiring rule information 13, technical information 56, and academic information 57)
Returning to FIG. 4, the illustrated flowchart is a flowchart illustrating one embodiment of the processing of the crawler program 36g used by the crawler server 9 of the system 44. FIG.

(S1a) The CPU 30 (see FIG. 3a) of the crawler server 9 collects technical information 56 and academic information 57 in addition to the rule information 13 from the WEB pages published on the Internet 12 based on the collection conditions 2a.
In this embodiment, text data and files are collected as rule information 13, technical information 56, and academic information 57. FIG. Furthermore, the text information, title, organization name, and release date are extracted as collected information 2b from the text data, files, and the like. Furthermore, as the collection information 2b, the URL of the collection destination is acquired from the collection condition 2a. The information to be obtained is substantially the same as that described for system 10 .

(S2a) Store the collected rule information 13, technical information 56, and academic information 57 in the first storage unit 7. FIG. The collected information 2b is stored in the first storage unit 7 in association with the rule information 13, technical information 56, and academic information 57 collected at this time.
The collection conditions 2 a define conditions for storing the collected rule information 13 , technical information 56 and academic information 57 in the first storage unit 7 . In the present embodiment, for example, it is checked whether there is a title, publication date, and organization name obtained from the acquired rule information 13, technical information 56, and academic information 57 that all match in the first storage unit 7, Store if not present. This prevents collection of identical sentences.

(S3a) Acquire the rule information 13, the technical information 56, and the academic information 57 from the first storage unit 7, and translate them into a predetermined language based on the translation conditions 3a. Post-translation processing is performed based on a predetermined language. In this embodiment, the predetermined language is English. Note that the collected information 2b may be translated into a predetermined language.

Next, as in the system 10, data 21 of various release dates are arranged in a predetermined format based on a date table 22 provided for each language and stored in the first storage unit 7 (see FIG. 5). The date table 22 is included in the collection condition 2a.

(S4a) Store the translated rule information 13, technical information 56, and academic information 57 in the first storage unit 7;

(Processing for Acquiring Co-occurrence Word Group 53)
FIG. 18 is a flow chart showing an embodiment of processing of the programs 36h and 36i used in the server 1 and analysis server 45 of the system 44. FIG. In the flow chart of the system 44 shown in FIG. 18, substantially the same parts as those of the system 10 described above are denoted by the same reference numerals, and the description thereof will be omitted.

(S5) The rule information 13 is acquired from the first storage unit 7, and the rule information 13 related to a predetermined category is selected based on the selection condition 4a. For example, predetermined categories correspond to technology themes such as drones, blockchain, AI, batteries, and space technology.
(S5a) Also, the technical information 56 and academic information 57 are sorted by the analysis server 44. FIG. The sorting process is performed in a manner similar to that described for system 10 (see FIG. 7).

(S6a) From the rule information 13, concise information 5a is created. In this embodiment, characteristic words 52 are extracted as concise information 5a. The acquired feature word 52 is linked to the rule information 13 and stored in the second storage unit 8 .
(S6b) Characteristic words 52 are extracted from the technical information 56 and academic information 57, respectively. The acquired characteristic word 52 is linked to the corresponding technical information 56 or academic information 57 and stored in the third storage unit 46 . As with the rule information 13, concise information 5a may be created.

The acquired feature words 52 , 52 , 52 are words that characterize the content of each of the rule information 13 , the technical information 56 , or the academic information 57 . A known technique can be used to extract the characteristic words. For example, techniques such as TF-IDF (Term Frequency-Inverse Document Frequency), SVM (Support Vector Machine), or KeyGraph can be used.
In this embodiment, the feature word 52 is extracted using the TF-IDF technique. The TF-IDF method is a method of extracting words based on the hypothesis that frequently occurring words are important words, for example.
In addition, the method using SVM is a method of extracting words based on the assumption that feature words tend to be the center of topics and appear in headlines.
KeyGraph's method is based on the assumption that characteristic words tend to be the center of topics and appear in headlines, and that words that appear frequently in a sentence often form the basis of the entire sentence. It is a method based on the idea that what is most important to convey is what is supported by this foundation, that is, it becomes a characteristic word. It should be noted that feature words may be extracted using techniques other than these techniques.

(S12) Acquire the rule information 13, technical information 56, academic information 57, and characteristic words 52, 52, 52 from the second and third storage units 8, 46, respectively. The analysis server 45 acquires co-occurrence word groups 53 , 53 , 53 of the rule information 13 , the technical information 56 , and the academic information 5 corresponding to the acquired feature words 52 , 52 , 52 .
Here, the co-occurring word is a word that is highly related to and frequently used together with the main axis word. It can be said that it is a word that often appears around the word that is the main axis, and there is one or more. In this embodiment, a feature word 52 is used as a main axis word, and a group of words (co-occurrence words) used together with the feature word 52 in each information 13, 55 or 56 is defined as a co-occurrence word group 53. there is A known method can be used to acquire the co-occurrence word group 53 .

(Processing for Acquiring Co-occurrence Word Group 53)
FIG. 19 is a flowchart illustrating one embodiment of the processing of program 36j used in analysis server 45 of system 44. FIG. The flowchart shown in FIG. 19 is mainly similar to one specific information input by selection of the user 15 (see FIG. 17) from the rule information 13, the technical information 56 or the academic statement information 57, and the input It acquires specific information of a different kind from the information provided. For example, taking the rule information 13 as an example, the specific information is the rule information 13a specified by the user 15 from among the rule information 13, which is a bundle of a plurality of information related to rule formation (see the upper symbol 13a in FIG. 20). corresponds to Note that the suffix a indicates specific rule information.

(S13) For example, the user 15 (see FIG. 17) selects specific rule information from the rule information 13. FIG.
The user terminal 16 acquires information (input information 67 ) indicating the specific rule information 13 a by the input operation of the user 15 and transmits it to the analysis server 45 . The analysis server 45 acquires the specific rule information 13 a corresponding to the input information 67 from the second storage section 8 . The input information 67 is information for identifying the specified rule information 13a.
As with the rule information 13, the technical information 56 and academic information 57 are also given subscripts when indicating specific information. If there is a plurality of pieces of information to be specified, for example, specific rule information 13a, 13b, 13c, .

(Correlation diagram showing similarity 54)
From here, further details will be given with reference to FIG. 20 . FIG. 20 is a schematic diagram showing an embodiment of a screen displayed on the display section 16a (see FIG. 17) of the user terminal 16. As shown in FIG. The screen shows a correlation diagram 60 of similarities. The correlation diagram 60 shows a plurality of circular display elements 58 indicating specific information of the rule information 13 , the technical information 56 and the academic information 57 . A linear shape connecting the display elements 58 , 58 is a connecting display element 59 . Note that in the correlation diagram 60 , display elements 58 representing information having a medium or higher degree of similarity 54 are displayed, and these display elements 58 and 58 are connected by a connection display element 59 .

(S14) Based on the input information 67, the co-occurrence word group 53a corresponding to the rule information 13a is obtained from the third storage unit 46. FIG.
The co-occurring word group 53a of the rule information 13a is compared with the co-occurring word groups 53, 53 of the technical information 56 and academic information 57, respectively. Here, for example, the co-occurrence word group 53 of the technical information 56 is a bundle of co-occurrence word groups 53a, 53b, .
As a result of the above comparison, technical information 56 and academic information 57 having similar co-occurrence word groups 53a of rule information 13a are acquired. In this embodiment, technical information 56a, 56b, 56c, 56d and academic information 57a are listed as information to which the co-occurrence word group 53a is similar, as shown in FIG. Also, the similarity 54 of the information 56a, 56b, 56c, 56d, and 57a with the rule information 13a is obtained.

(Similarity 54)
In this embodiment, for example, two co-occurring word groups are compared, and if 80% or more of one co-occurring word group is the same or 80% or more of one co-occurring word group is included in the other co-occurring word group, similar It is said that the degree is high. Furthermore, if less than 80% to 60% or more of each co-occurring word group is the same or one is included in the other by less than 80% to 60% or more, the similarity is medium, and less than 60% to 20% or more are the same. Or if one is included in the other less than 60% to 20% or more, the similarity is low, and if less than 20% is the same or one is included in the other less than 20%, the similarity is zero. .

(61 connections)
Next, for example, the number of pieces of information (the number of connections) having a similar relationship with the specific rule information 13a is obtained. The acquired number of connections 61 is stored in the third storage unit 46 . For example, in FIG. 20, five connected display elements 59a and 59b extend from a display element 58 representing specific rule information 13a. That is, it can be seen that there are five pieces of specific rule information 13a and specific information having a degree of similarity 54 of medium or higher. Information with a greater number of connections is presumed to be quoted to other information, and thus is presumed to have a high degree of importance and value as information.

(S15, degree of importance 55) In this embodiment, if the number of connections is 5 or more, the degree of importance 55 is high, if the number of connections is 4 or 3, the degree of importance is medium, and the number of connections is 2 or less. If so, the importance is low. In the present embodiment, the number of connections 61 is divided into three levels of high, medium, and low. Furthermore, the importance level 55 may be divided into two stages or four stages or more.

The obtained similarity 54, number of connections 61, and importance 55 are stored in the third storage unit 46 together with corresponding technical information 56a, 56b, 56c, 56d and academic information 57a.
In the process of acquiring the degree of similarity 54 and the degree of importance 55 described above, the degree of similarity 54 and the degree of importance 55 stored in the past may be read from the third storage unit 46 . Whether or not it was stored in the past is determined, for example, based on the date and time when the similarity 54 and the importance 55 were stored. Regarding the similarity 54 and the importance 55 regarding the rule information 13, the technical information 56, and the academic information 57 collected after the date and time, the similarity 54 and the importance 55 are acquired based on the co-occurring word group 53 as described above. do.

(Processing to acquire next similarity, number of connections, and importance)
Next, the acquired specific technical information 56a, 56b, 56c, 56d and the specific academic information 57a co-occurring word group 53a . A new similarity 54, new specific technical information 56e, 56f, and new specific academic information 57b, 57c are obtained by comparing with the origin group 53. A new number of connections 61 and a new degree of importance 55 are respectively acquired for the newly acquired specific technical information 56e, 56f and specific academic information 57b, 57c. The newly acquired similarity 54, the number of connections 61, and the importance 55 are linked to the corresponding new information, and are stored in the third storage unit 46 together with the technical information 56e, 56f and the specific academic information 57b, 57c. Remember.

(Process of repeatedly acquiring and storing similarity, number of connections, importance, and specific information)
Regarding the newly acquired specific technical information 56e, 56f and specific academic information 57b, 57c, the specific technical information, academic information, similarity 54, number of connections 61 and importance 55 are acquired again, and the third storage unit 46. By repeating this process to deepen the depth of the search, the possibility of reaching the technical information 56 and/or the academic information 57 that are the basis of the specific rule information 13a increases. In this embodiment, the similarity 54, the specific technical information, the academic information, the number of connections 61, and the importance 55 are acquired five times. The above treatment may be performed 1 to 4 times, or may be performed 6 times or more.

(S16) A correlation diagram 60 is created based on the obtained similarity 54, specific technical information, academic information, number of connections 61, and importance 55. FIG. FIG. 21 displays display elements 58 and connected display elements 59 based on importance 55 and similarity 54 values. For example, in the present embodiment, the higher the importance 55, the larger the shape of the display element 58 is. For example, display elements 58a and 58b correspond to high and medium importance levels 55, respectively.
Further, in this embodiment, the degree of similarity 54 is represented by the length of the connected display element 59 . The shorter, the higher the similarity. For example, the connected display elements 59a and 59b correspond to high or medium similarities 54, respectively. In addition, in the present embodiment, in order to further clarify whether the similarity 54 is medium or high, the connected display elements with the medium similarity 54 are displayed with a dashed line (see reference numeral 59b). . For example, in FIG. 20, technical information 56a, 56b, 56c, 56d and scientific information 57a are displayed as information similar to the rule information 13a. Among them, technical information 56b and 56c connected by a solid line (see reference numeral 59a) have a high degree of similarity 54 with the rule information 13a. In this embodiment, as the predetermined degree of similarity 54, a link display element 59 is displayed between pieces of information having a high and medium degree of similarity 54 relationship.

(Direction of arrow of connecting display element 59)
In this embodiment, the connecting display element 59 is an arrow line. The direction of the arrow points to the display element 58 having a large number of co-occurring word groups 53 . For example, the display element 58 to which the arrow is pointing may be assumed to be primary and the opposite display element 58 to be secondary. Note that the arrow does not have to be indicated.

(Correlation diagram 60)
For example, from the correlation diagram 60, it can be understood that the display element 58 representing the academic information 57l is one of the starting points for the rule information 13a. It can be understood that the starting point of the academic information 57l leads to the rule information 13a along the left and right routes in the figure. The route on the right is a route from academic information 57l, which is the starting point at the bottom of the figure, upwards through academic information 57i, 57f, 57c, and 57a to rule information 13a. On the other hand, the route on the left is a route from academic information 57l, which is the starting point at the bottom of the figure, upwards via academic information 57g, 57d, and 57e, then technical information 56f, 56a to rule information 13a. is.

For example, in the correlation diagram 60, when the user 15 selects a display element 58 whose details are to be displayed, brief information 5a associated with the display element 58 may be displayed on the display unit 16a. The concise information 5a is displayed via the SNS server 4. FIG. Screens for displaying the concise information 5a include, for example, the screens 23, 40, 41, and 42 (see FIGS. 9, 10, and 13).
Note that text information indicating the concise information 5a may be obtained from the second storage unit 8 or the third storage unit 46 and displayed.

(Another Embodiment 62 of Correlation Diagram)
FIG. 22 shows another embodiment of correlation diagram 60 . Since the person correlation diagram 62 shown in FIG. 22 is substantially the same as the correlation diagram 60 described above, the same parts are denoted by the same reference numerals and the description thereof is omitted. The person correlation diagram 62 is different from the information of the correlation diagram 60 described above in that information regarding a person/organization is further displayed.

Returning to FIG. 19, a flowchart illustrating one embodiment of the processing of program 36k for displaying person correlation diagram 62 will be described. The processing of the program 36k (see the dotted line) is almost the same as the processing of the program 36j described above, so only the different parts will be explained and the explanation of the same parts will be omitted. The processing of the program 36k includes a step (S17) of acquiring the importance of the person/organization between the step of acquiring the degree of similarity/number of connections (S14) and the step of acquiring the degree of importance (S15). This is different from the processing of the program 36j in that respect.

(S17, person/organization information 63)
Information (person/organization information) 63 of a person name or an organization name and the number of appearances of the person/organization information 63 are obtained from the co-occurrence word group 53 . The degree of importance 66 of the person/organization is acquired based on the number of appearances. The degree of importance 66 of the person/organization is stored in the third storage unit 46 . Here, the suffix a indicates specific person/organization information. When there is a plurality of information to be specified, for example, specific person/organization information 63a, 63b, 63c, .

(person/organization importance 66)
In the information (13, 56, 57) having a relationship of a predetermined degree of similarity 54 shown in the correlation diagram 60, from the co-occurrence word groups 53, 53, 53 of the respective information (13, 56, 57), Get the number of occurrences of the organization name. The personal name/organization importance level 66 of the personal name/organization information 63 is obtained based on the number of appearances. In the present embodiment, for example, 10 times or more is defined as high, 5 times or more and less than 10 times is defined as medium, and less than 5 times is defined as low.
For example, in this embodiment, the specific personal name/organization information 63a (see FIG. 22) appears in the rule information 13a and the technical information 56e. The sum of the number of occurrences of these is obtained as the personal name/organization importance level 66 .

Based on the acquired personal name/organization information 63 and personal name/organization importance degree 66, a person correlation diagram 62 is created. From here, further description will be given with reference to FIG. 21 . FIG. 21 shows a person/organization display element 64 created based on the value of the person's name/organization importance 66 . In this embodiment, the higher the person name/organization importance 66 is, the larger the shape of the person/organization display element 64 is. For example, personal name/organization display elements 64a, 64b, and 64c correspond to high, medium, and low personal name/organization importance levels 66, respectively.
The person connection display element 65 connects the person/organization display element 64 and the corresponding display element 58 . For example, in the person correlation diagram 62 shown in FIG. 22, the person/organization information 63f is linked to the rule information 13a, the technical information 56f, and the academic information 57a, 57b, 57e, 57f, and 57h.
In the present embodiment, the person/organization display element 64 of the person/organization information 63 having a relationship of low or higher importance 66 is displayed as the predetermined person/organization importance 66 . Note that the personal name/organization importance 66 may be set to high or higher or medium or higher.

(Person correlation diagram 62)
For example, from the person correlation diagram 62, the person/organization information 63f is linked to seven pieces of surrounding information, so it can be inferred that the person or organization is important to the rule information 13a.

(others)
In FIG. 19, the process of acquiring the importance (S15) may be performed at the same time as or after the process of acquiring the importance of the person/organization (S17).
After the correlation diagram 60 (see FIG. 20) is displayed, the person/organization display element 64 and the person connection display element 65 may be added to the correlation diagram 60 by the user 15 operating the user terminal 16. . For example, by acquiring input information (see reference numeral 67a) from the user terminal 16, the importance of the person/organization is acquired (S17), a diagram is created (step 16), and displayed on the user terminal 16 (program 36l See double-dotted line processing for one embodiment of processing).

(Understanding trends in collected information)
Next, with reference to FIG. 23, a method for grasping trends in the collected rule information 13, technical information 56, or academic information 57 will be described. FIG. 23 is a flow chart showing an embodiment of processing of the programs 36m and 36n used in the analysis server 45. FIG.

(Preparation Step) The CPU 30 (see FIG. 3B) of the user terminal 16 requests the analysis server 45 to download the input screen. Conditions for grasping trends are entered via the input screen.

(Input screen 69)
The input screen (trend screen) 69 will now be described with reference to FIG. FIG. 24 shows a schematic diagram of an input screen displayed on the display section 16a of the user terminal 16. As shown in FIG. The input screen 69 displays the collected number of the rule information 13, the technical information 56, or the scientific information 57 for each technical theme in chronological order based on the creation date of each information. The input screen 69 is composed of a vertical axis screen portion 70, a horizontal axis screen portion 71, a collection number screen portion 72 indicating the number of collections 76, and an operation screen portion 73 operated to change collection conditions.

(Vertical axis screen portion 70, horizontal axis screen portion 71, collection number screen 72, operation screen portion 73)
The vertical axis screen portion 70 lists technology-related words (technical themes) among the keywords 4c selected based on the selection conditions 4a (see FIG. 7).
The horizontal axis screen portion 71 has an axis indicating the date and time of creation. The date of creation corresponds to the date of creation (date and time of creation), the date of publication (date and time of publication), the date of update (date and time of update), and the like of the information acquired by the collecting means 2 (see FIG. 17). In this embodiment, the creation date is used. If the date of creation cannot be obtained, the date of publication may be used, and if the date of creation/publication cannot be obtained, the date of update may be used. In the present embodiment, the horizontal axis screen portion 71 displays an axis with a time length of about two years and a memory attached at intervals of half a year.
The collection count screen portion 72 is a screen portion of an internal area surrounded by the vertical axis screen portion 70 and the horizontal axis screen portion 71 . On the collection count screen portion 72, the number of collected information (collection count) is indicated by a collection count display element 74 every six months for each date and time of creation. In this embodiment, for example, the collected number of the collected number display element 74 is displayed in shades of color (see FIG. 21). The darker the color, the more collected. The collection number display element 74 is divided into three stages according to the number of collections. For example, it consists of a collection number display element 74a that indicates a large number of collections of 101 or more, a collection number display element 74b that indicates a medium number of 100 to 11 cases, and a collection number display element 74c that indicates a decimal number of 10 to 1 cases. .
The operation screen portion 73 includes a country/technology selection screen portion 73a for selecting a country name/technical theme, and an information selection screen portion 73b for selecting the rule information 13, the technical information 56, or the academic information 57. FIG. In this embodiment, for example, the selection screen portions 73a and 73b employ a method called a drop-down menu or pull-down menu, and when the user 15 touches the selection screen portions 73a and 73b with a finger, selectable options Listed in a selectable state on the screen. In the operation screen portion 73, the length of time indicated by the horizontal axis screen portion 71 and the time interval may be changed. In this embodiment, the country name displayed on the country/technology selection screen portion 73 a and the information displayed on the information selection screen portion 73 b correspond to the operation input information 68 .

( S<b>18 ) Returning to FIG. 23 , the CPU of the user terminal 16 acquires the input screen 69 from the analysis server 45 . When the operation input information 68 is not input, the collection number display element 74 is not displayed on the collection number screen portion 72 of the input screen 69 .
If the operation input information 68 is preset as an initial value, the collection number display element 74 may be displayed with the operation input information 68 set in the collection number screen section 72 .

(S19) The user terminal 16 acquires the operation input information 68 by the user's 15 operation. The acquired operation input information 68 is transmitted to the analysis server 45 . In this embodiment, as information to be collected, Japan is selected from country names in the country/technology selection screen portion 73a, and rule information is selected in the information selection screen portion 73b. A frame indicating the selection is displayed on the screen portion around the selected option (see reference numeral 73c). In this embodiment, the rule and the text "Japan" are surrounded by rectangular frame-shaped display elements (see FIG. 24).

(S20) The analysis server 45 acquires the operation input information 68. FIG.
(S21) Based on the operation input information 68, the number of collections is acquired.
(S22) Based on the acquired number of collections, the collection number display element 74 (see FIG. 21) is acquired and displayed on the collection number screen section 72 to create the trend screen 69. FIG. A trend screen 69 is transmitted to the user terminal 16 .
(S23) The trend screen 69 is displayed on the display section 16a of the user terminal 16. FIG.

(Other examples)
FIG. 25 shows another embodiment of the trend screen 77. In FIG. Since the trend screen 77 is substantially the same as the trend screen 69 described above, description of the same portions will be omitted. In the trend screen 77 shown in FIG. 25, a technology theme is selected in the country/technology selection screen portion 73a. In addition, country names are listed on the vertical axis screen portion 70 . Rule information is selected in the information selection screen portion 73b. The technical theme displayed on the country/technology selection screen portion 73 a and the information displayed on the information selection screen portion 73 b correspond to the operation input information 68 . In this embodiment, 76 pieces of rule information collected are displayed in chronological order for each country with a technical theme of drones.

[6. others]
In the above-described embodiment, the first storage unit 7, the second storage unit 8, and the third storage unit 45 are used as external data servers. It may be provided in any of the servers 45 .
Also, although the translation means 3 is provided in the crawler server 9 , it may be provided in the server 1 and the analysis server 45 .
Further, the crawler server 9, the SNS server 14 and the analysis server 45 are provided separately from the server 1, but all or one or more functions of the crawler server 9, the SNS server 14 and the analysis server 45 are integrally provided in the server 1. may Furthermore, the crawler server 9 and the SNS server 14 may be one server. Furthermore, the crawler server 9 and the analysis server 45 may be one server. Furthermore, the SNS server 14 and the analysis server 45 may be integrated into one server.
Also, the request means 20 may be provided in the server 1 .
Further, in the present embodiment, the attention level measuring means 28 is provided in the SNS server 14, and the progress determining means 29 is provided in the server 1, but they may be provided in other servers. Further, it may reside on another server external to the system 10,44.
Alternatively, in step T3 of FIG. 11, the information on the new collection destination may be directly transmitted to the administrator terminal 10a.
Further, in step T1 of FIG. 11, a user other than the user registered in the SNS may be allowed to request the addition of the collection destination.
Furthermore, in step U1 of FIG. 12, a user other than the user registered in the SNS may be allowed to request the form.

In this embodiment, the degree of similarity 54 is divided into four stages of high, medium, low, and none, but may be divided into two or three stages or five or more stages. Note that the range of each step can be set arbitrarily.
With respect to the predetermined similarity 54, in the present embodiment, information having a relationship of medium or higher similarity 54 is displayed in the correlation diagram 60. For example, information having a relationship of high or higher or low or higher similarity 54 is displayed. may be displayed.
In the analysis server 46 , all or part of the cleansing means 17 and the processing of the tagging means 18 based on the classification conditions 18 a may be performed on the technical information 56 and academic information 57 .
In this embodiment, the result of the similarity 54 is stored in the third storage unit 46, but only the necessary similarity 54 may be recorded. For example, high or higher, medium or higher, or low or higher similarities 54 may be recorded.
In this embodiment, the number of connections 61 is stored, but it may be stored as high, medium, or low. If there is no connection number 61, it may be stored as 0 or none.
The shape of the display element 58 may be polygonal, elliptical, star-shaped, or any other shape. Depending on the degree of importance 54, the shape of the display element 58 may be changed to a different shape instead of being enlarged or reduced. For example, it may be circular, rectangular, or star-shaped. Furthermore, the color of the display element 58 may change. For example, blue, yellow, and red may be changed so that red or blue becomes darker. Furthermore, the degree of importance 54 may be represented by a single color shade.
If the degree of similarity 54 can be visually recognized by the length of the connected display element 59, the line type may be the same.
The degree of similarity 54 may be represented by the thickness of the connected display element 59 . For example, the thicker the line, the higher the similarity 54 is. Furthermore, when the degree of similarity 54 is represented by the type of line of the connecting display element 59, for example, the closer to the solid line, the higher the similarity 54, such as a solid line, a one-dot chain line, a two-dot chain line, and a dotted line. good.
The arrow of the connected display element 59 may point toward the display element 58 having a small number of co-occurring word groups 53 . If the number of co-occurrence word groups 53 is the same, the arrows may point to both display elements 58, 58, or may not be attached.
In the above-described embodiment, the acquisition of the similarity 54 of the technical information 56 and the academic information 57 is repeated starting from the specific rule information 13a. Acquisition of the similarity 54 between the rule information 13 and the academic information 57 or the rule information 13 and the technical information 56 may be repeated.
The matters described as other items in the above-described embodiments can be used in combination as appropriate.

[7. summary]
Based on collection conditions 2a including pre-registered collection destinations 11, the system 10 collects rule information 13 including information on rule formation such as environmental issues, human rights issues, laws and regulations, and standardization, which are open to the public via the Internet 12. and a translation means 3 for translating into a predetermined language to be translated based on the translation condition 3a when the collected rule information 13 is different from the language to be translated; A selection means 4 for selecting rule information related to a predetermined category from the rule information 13 obtained based on a selection condition 4a, and concise information 5a is formed based on predetermined information acquired from the selected rule information 13. A server 1 comprising a simplification means 5, a progress measuring means 29 for measuring the progress of rule formation based on organizational information including an organization 11 from which rule information 13 is collected, and a simple information 5a first posted. and manages the SNS site 14a for posting as, and the posting means 6 for making the first post, the number of comments and reactions of the user 15 corresponding to the posted brief information 5a, the number of reactions, and the corresponding rules an attention degree measuring means 28 for measuring the attention degree of the corresponding rule information 13 based on at least one of the number of clicks on the link for accessing the information and the number of times the collapsed display is released. Consists of System 10 implements a rule watch method.

SNS has functions such as transmission, sharing, and diffusion of information. By simplifying the information 13 on rule formation and making it widely known on SNS, it is possible to collect comments and reactions from many SNS users across fields.
Therefore, the users 15 belonging to the SNS in various positions can encourage discussions on dealing with social issues across fields. On top of that, by observing the reactions of these SNS users 15, it is possible to notice important signs of rule formation, such as whether the rule formation should be welcomed or rule formation that requires caution. It can monitor global rule-making.

The system 10, the rule watch method, the server 1, and the server programs 36, 36h, and 36i have the steps of sorting the collected rule information into predetermined categories based on sorting conditions, and Since the rule information 13 is classified by category, the rule information 13 is organized as concise information 5a. Therefore, the user 15 can easily touch the content of the rule information 13 . In addition, it becomes easier to collect reactions from users 15 on the SNS site 14a.

In addition, the system 10 and the rule watch method include the step of translating into a predetermined language based on the translation condition 4a when the collected rule information includes a language different from the predetermined language in order to align the languages after the selecting step. Since it is prepared before the sorting step, the domestic and foreign rule information 13 can be summarized as the concise information 5a.

In addition, the system 10, the rule watch method, the SNS server 14, and the SNS server program 36e can monitor the number of comments, the number of reactions, and the number of clicks on the link for accessing the corresponding rule information by the user 15 corresponding to the posted concise information. , and a button for canceling the folding display, the degree of attention of the user 15 to the rule information 13 can be known. . The rule information 13 that attracts a lot of attention can be one of the important signs of rule formation, including whether the user's 15 interests and vigilance are good or bad.

The system 10, the rule watch method, the server 1, and the server program 36f are equipped with progress measuring means 29 for measuring the progress of rule formation based on the organization 25d, which is the collection destination 11 of the rule information 13. Since it is possible to know the extent to which rules are formed, it is possible to help judge whether the information should be dealt with immediately or whether the information should be noted.

Further, the SNS server 14 is provided with a request means 20 for requesting addition of a desired collection destination of the rule information 13 in order to make the SNS user 15 make a request. Therefore, the rule information 13 of interest to the user 15 is likely to be posted to the SNS site.

Further, the SNS server 14 is provided with a forum forming means 19 for forming a forum in which specific SNS users 15 can comment on the predetermined rule information 13 so that the SNS users 15 can create a forum. It can encourage conversation. Therefore, it becomes easier to collect user reactions.

The rule watch method shown in the system 44 includes technical information 56 related to the practical application of technology, such as press releases or technology investments related to science and technology, and academic information 57 related to the progress of technology, such as papers or patent documents related to science and technology. A step of collecting technical information and academic technical information from the Internet based on pre-registered collection conditions 2a including the collection destination of , and co-occurring word groups 53 from the rule information, the collected technical information and academic technical information, respectively and obtaining a degree of similarity 54 between pieces of information in the rule information, the technical information, and the academic information based on the degree of similarity of the respective co-occurring word groups.
Therefore, it is possible to easily grasp the connection among rule information, technical information, and academic information.

Such a rule watch method uses the thickness or length of a line connecting similar display elements among the display elements 58 respectively indicating the rule information 13, the technical information 56, and the academic information 57 to determine the degree of similarity on the user terminal. display on the display section, it is easy to grasp the mutual connection between rule information, technical information, and academic information.

Further, a step of sorting the collected rule information 13, technical information 56 and academic information 57 into a predetermined category based on the sorting condition 4a; and a step of displaying in a graph consisting of an axis showing and a time axis, it is easy to grasp the trend of rule information, technical information or academic information for each country or category.

The user terminal 16 includes rule information 13 regarding rule formation such as environmental issues, human rights issues, laws and regulations or standardization, technical information 56 regarding practical application of technology such as press releases or technology investment related to science and technology, and information related to science and technology. A user terminal communicatively connected to a server 1 that collects scientific information 57 related to technological progress, such as papers or patent documents, from the Internet based on pre-registered collection conditions 2a and sorts them according to predetermined sorting conditions 4a. There is an operation input information acquisition means 16c for acquiring operation input information 68 including a country name or a technical theme name by user operation, and rule information, technical information or academic information created by the server and corresponding to the operation input information. and a display unit 16a for displaying a screen showing the number of pieces of information in chronological order.
Therefore, it is easy to grasp the trend of rule information, technical information or academic information for each country or category by simple operation.

1 Server 2 Collecting Means 2a Collecting Conditions 2b Collecting Information 3 Translating Means 4 Sorting Means 4a Sorting Conditions 5 Simplifying Means 5a Brief Information 6 Posting Means 7 First Storage Unit 8 Second Storage Unit 9 Crawler Server 10 Rule Watch System (System)
10a Administrator terminal 11 Collection destination 12 Internet 13 Rule information 14 SNS server 14a SNS site 15 User 16 User terminal 16a Display unit 16b Input information acquisition means 16c Operation input information acquisition means 17 Cleansing means 18 Tag means 18a Classification condition 18b Classification keyword 18c Tag 19 Forum formation means 20 Request means 21 Publication date data 22 Date table 23 Posting screen 23a Posting screen 24 Common screen section 24a Contributor screen section 24b Posting date and time screen section 25 Extracted keyword screen section 25a Title screen section 25b Shows the date of publication Screen portion 25c Screen portion 25d showing where the article is directed (for which country) Screen portion 25e showing organization name Screen portion 25f showing keywords Screen portion 25g showing extracted person names Screen portion showing extracted place names 25h Screen portion 25i showing the name of the extracted organization Screen portion 25j showing keywords that serve as basis Screen portion 25k to be folded Screen portion 25k Unfolding screen portion 26 Summary screen portion 26a Icon screen portion 26b Title screen portion 26c URL screen portion 26d Simple screen portion 26e tag screen portion 26f input screen portion 27a comment screen portion 27b worry screen portion 27c share screen portion 27d reaction screen portion 28 attention degree measuring means 29 progress degree determining means 30 CPU
31 memory 32 recording device 33 connection port 34 communication circuit 35 bus lines 36a-m server program 36n user terminal program 37 browser program 38 OS
39 Additional screen section 40 Home screen 41 Right screen 42 Left screen 42a Common screen section 42b Forum screen section 43a Rule trend screen section 43b Social issue screen section 43c Project screen section 43d Expert screen section 44 Rule watch system 45 Analysis server 46 Third Storage unit 47 Co-occurring word group acquisition means 48 Similarity acquisition means 49 Importance acquisition means 50 Person/organization importance acquisition means 51 Screen creation means 52 Characteristic word 53 Co-occurrence word group 54 Similarity 55 Importance 56 Technical information 57 Academic Information 58 Display element 59 Connection display element 60 Correlation diagram 61 Number of connections 62 Person correlation diagram 63 Person/organization information 64 Person/organization display element 65 Person connection display element 66 Importance of person/organization 67 Input information 68 Operation input information 69 Input Screen (trend screen)
70 vertical axis screen section 71 horizontal axis screen section 72 collection number screen section 73 operation screen section 74 collection number display element 75 collection screen creation means 76 collection number 77 input screen (trend screen)

Claims (21)

A rule watch method executed by one or more computers, comprising:
a step of collecting rule information including information on rule formation such as environmental issues, human rights issues, laws and regulations or standardization published via the Internet based on collection conditions including a pre-registered collection destination;
forming succinct information based on predetermined information obtained from the rule information;
and making the initial posting to a SNS site for posting the concise information as the initial posting. a step of sorting the collected rule information into a predetermined category based on sorting conditions;
forming said concise information from said filtered rule information. In order to align the languages after the selecting step, if the collected rule information includes a language different from the predetermined language, a step of translating into the predetermined language based on translation conditions is provided before the selecting step. 3. The rule watch method of claim 2, wherein: based on at least one of: the number of user comments, the number of reactions, the number of clicks on links to access corresponding rule information, and the number of uncollapsed views corresponding to the posted concise information. 4. A rule watching method according to any one of claims 1, 2 or 3, comprising the step of measuring the degree of attention of said corresponding rule information. 5. The rule watching method according to claim 1, further comprising the step of judging the degree of progress of said rule formation based on organization information including an organization from which said rule information is collected. . Collection means for collecting rule information including information on rule formation such as environmental issues, human rights issues, laws and regulations or standardization published via the Internet based on collection conditions including pre-registered collection destinations, and said collection a crawler server having translation means for translating into a predetermined language to be translated based on a translation condition when the rule information obtained is different from the language to be translated;
A selection means for selecting rule information related to a predetermined category from the translated rule information based on a selection condition, a simplification means for forming concise information based on predetermined information acquired from the selected rule information, and a server comprising progress measuring means for measuring the progress of rule formation based on organizational information including an organization from which the rule information is collected;
Managing an SNS site for posting the concise information as the first post, and furthermore, posting means for making the first post, and the number of comments and reactions of the user corresponding to the posted concise information. attention degree measuring means for measuring the attention degree of the corresponding rule information based on at least one of the number of , the number of link clicks for accessing the corresponding rule information, and the number of times the collapsed display is canceled A rule watch system consisting of a provided SNS server. A server provided with an SNS site for posting as the first post and forming the information to be posted,
Rule information collected based on collection conditions including pre-registered collection destinations and published via the Internet, including information on rule formation such as environmental issues, human rights issues, laws and regulations or standardization, as a selection condition a sorting means for sorting into rule information related to a predetermined category based on
simplification means for forming succinct information based on predetermined information obtained from said selected rule information. 8. The server according to claim 7, further comprising progress determination means for determining the progress of said rule formation based on organization information including an organization from which said rule information is collected. An SNS server that manages an SNS site for posting as the first post,
From rule information collected based on collection conditions including pre-registered collection destinations and published via the Internet, including information on rule formation such as environmental issues, human rights issues, laws and regulations or standardization, to sorting conditions posting means for selecting rule information related to a predetermined category based on the above, and posting concise information formed by acquiring predetermined information from the selected rule information to the SNS site as the first post. SNS server provided. 10. The SNS server according to claim 9, further comprising request means for requesting addition of said collection destination so as to make a request from said SNS user. 11. The SNS server according to claim 10, further comprising forum forming means for forming a forum in which specific users of the SNS can comment on the predetermined rule information so that users of the SNS can create the forum. based on at least one of the number of comments corresponding to the posted concise information, the number of reactions, the number of clicks on links to access corresponding rule information, and the number of unfolded views of the concise information. 12. The SNS server according to any one of claims 9, 10 and 11, further comprising an attention level measuring means for measuring an attention level of such information. A server program having an SNS site for posting as the first post and forming the information to be posted,
to the computer,
Rule information collected based on collection conditions including pre-registered collection destinations and published via the Internet, including information on rule formation such as environmental issues, human rights issues, laws and regulations or standardization, as a selection condition select rule information related to a predetermined category based on
A server program for forming concise information from the filtered rule information. 14. The server program according to claim 13, which determines the degree of progress of said rule formation based on organization information including an organization from which said rule information is collected. An SNS server program used as an SNS server for managing an SNS site for posting as a first post and for posting the information to be posted to the SNS site,
to the computer,
From rule information collected based on collection conditions including pre-registered collection destinations and published via the Internet, including information on rule formation such as environmental issues, human rights issues, laws and regulations or standardization, to sorting conditions a SNS server, which selects rule information related to a predetermined category based on the above, and causes concise information formed by acquiring predetermined information from the selected rule information to be posted on the SNS site as the first post. program. based on at least one of the number of comments corresponding to the concise information posted, the number of reactions, the number of clicks on a link to access the corresponding rule information, and the number of unfolded views; 16. The SNS server program according to claim 15, which measures the degree of attention of the rule information to be used. A rule watch method executed by one or more computers, comprising:
Based on pre-registered collection conditions, including collection destinations for technical information related to the practical application of technology such as press releases related to science and technology or technology investment, and academic information related to technological progress such as papers related to science and technology or patent documents respectively collecting the technical information and the academic technical information from the Internet;
obtaining co-occurring word groups from the rule information, collected technical information and academic technical information;
2. The rule watching method according to claim 1, further comprising the step of acquiring a degree of similarity between information in said rule information, said technical information and said academic information based on the degree of similarity of each co-occurring word group. a step of displaying the degree of similarity on the display unit of the user terminal by the thickness or length of a line connecting similar display elements among the display elements respectively indicating the rule information, the technical information, and the academic information; 18. The rule watching method of claim 17, comprising: a step of sorting the collected rule information, technical information and academic information into predetermined categories based on sorting conditions;
18. The rule watch according to claim 17, further comprising the step of displaying the display elements indicating the rule information, the technical information, or the academic information in a graph having an axis indicating the corresponding country or category and a time axis. Method. A rule watch method executed by one or more computers, comprising:
Information on rules related to environmental issues, human rights issues, laws and regulations, standardization, etc., technical information related to the practical application of technology, such as press releases or technology investment related to science and technology, and technologies such as papers or patent documents related to science and technology a step of collecting the rule information, the science and technology information, and the academic information from the Internet based on pre-registered collection conditions including a collection destination of academic information related to the progress of
obtaining co-occurring word groups from the rule information, collected technical information and academic technical information;
and obtaining a degree of similarity between information in the rule information, the technical information, and the academic information based on the degree of similarity of each co-occurring word group. Information on rules related to environmental issues, human rights issues, laws and regulations, standardization, etc., technical information related to the practical application of technology, such as press releases or technology investment related to science and technology, and technologies such as papers or patent documents related to science and technology A user terminal communicatively connected to a server that collects academic information related to the progress of
operation input information acquisition means for acquiring operation input information including a country name or a technical theme name by a user's operation;
A user terminal, comprising: a display section for displaying a screen created by the server and showing the number of the rule information, the technical information, or the scientific information corresponding to the operation input information in chronological order.

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