WO2023163201A1 - 情報分析装置及び記憶媒体並びに情報分析プログラム - Google Patents

情報分析装置及び記憶媒体並びに情報分析プログラム Download PDF

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Publication number
WO2023163201A1
WO2023163201A1 PCT/JP2023/007219 JP2023007219W WO2023163201A1 WO 2023163201 A1 WO2023163201 A1 WO 2023163201A1 JP 2023007219 W JP2023007219 W JP 2023007219W WO 2023163201 A1 WO2023163201 A1 WO 2023163201A1
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WO
WIPO (PCT)
Prior art keywords
information
real estate
company
keyword
analysis
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Ceased
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PCT/JP2023/007219
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English (en)
French (fr)
Japanese (ja)
Inventor
之裕 宮寺
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CCReB Advisors Inc
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CCReB Advisors Inc
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Priority to JP2023540481A priority Critical patent/JP7432980B2/ja
Priority to US18/724,036 priority patent/US20240420259A1/en
Publication of WO2023163201A1 publication Critical patent/WO2023163201A1/ja
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/16—Real estate
    • G06Q50/163—Real estate management
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/16—Real estate

Definitions

  • the present invention relates to an information analysis device or the like that analyzes real estate information from corporate management information.
  • Patent Document 1 discloses a technique for displaying a list of companies that are likely to have real estate transaction demand by analyzing company management information such as medium-term management plans and securities reports.
  • Patent Document 1 Although it is an epoch-making system that can display a list of business target company candidates in descending order of the probability of demand for real estate transactions, keywords are not displayed. Moreover, it takes time and effort to search for the hot topic of the real estate utilization that the company is interested in, and it is not easy. In consideration of such circumstances, the present invention visualizes keywords and specific limited information obtained by analyzing a company's management information and property information, thereby grasping the company's real estate utilization trend at a glance. The purpose is to provide an information analysis device that can
  • the information analysis apparatus of the present invention includes a storage unit that stores real estate keywords related to corporate real estate utilization, an information acquisition unit that acquires management information of a plurality of companies, a management information Analysis scope identification unit that identifies the scope of analysis of each company. and an output unit for outputting display data for displaying a keyword display field containing the real estate keyword of the company as individual information of the company.
  • the information processing apparatus of this aspect by acquiring management information of a plurality of companies and analyzing and extracting real estate keywords related to real estate utilization of the companies in the specified management information analysis range, For example, it is possible to make characteristic keywords stand out more than the keywords that the company uses frequently. As a result, it is possible to visualize the true trends of real estate utilization of companies that can be understood from the management information with keywords, so that real estate utilization trends of companies with high potential for real estate transaction demand can be grasped at a glance.
  • the storage unit stores hot keywords related to trends in the environment surrounding the company
  • the analysis unit selects real estate keywords among the keywords included in the management information acquired by the information acquisition unit.
  • a keyword and a hot keyword are separately analyzed and extracted
  • the keyword display column includes a first keyword display column including the real estate keyword extracted by the analysis unit and a second keyword display column including the hot keyword.
  • the hot keywords include hot keywords associated with each industry
  • the analysis range identification unit uses management information of a plurality of companies included in the business industry of the companies acquired by the information acquisition unit. Information is specified as an analysis range, and the analysis department analyzes and extracts hot keywords associated with the industry from the management information within the analysis range.
  • the scope of hot keyword analysis is not limited to the management information of individual companies, but management information of a plurality of companies included in the industry of the company. It is possible to efficiently acquire hot keywords for the entire industry, including up to 10 companies.
  • the analysis range specifying unit includes past management information in the analysis range, and the analysis unit searches for keywords included in the management information of the company acquired by the information acquisition unit.
  • a keyword not included in the management information is extracted as the latest keyword, and the output unit outputs display data for displaying the latest keyword with priority over other keywords.
  • the keywords not included in the past management information of the company are extracted as the latest keywords. This is because the management information of the same company is often issued periodically in a similar format, and the latest keywords of the company can be efficiently extracted by using the past management information of the same company.
  • the analysis unit separately extracts real estate keywords included in the management information acquired by the information acquisition unit and real estate keywords included in past management information
  • the output unit extracts the first
  • display data for displaying the real estate keywords included in the past management information in the keyword display column is output.
  • the information acquisition unit is configured to acquire real estate property information of a plurality of companies, and includes a limited information identification unit that identifies limited information of the real estate property from the real estate property information
  • the analysis unit comprises , the information acquisition unit analyzes and extracts limited information from the real estate property information of each company acquired by the information acquisition unit, and the output unit converts the limited information display column containing the company's limited information extracted by the analysis unit into the individual information of the company. Output the display data to be displayed as
  • the limited information specified from the real estate property information of the company is analyzed and displayed, it is possible to narrow down and display the specific limited information from many pieces of information of each individual property. According to this, specific limited information is visualized as individual information of the company, so it is easier to find the real estate property you really need at a glance compared to the conventional way of including more information. .
  • the information acquisition unit acquires real estate information including at least the location, use, use area, and size of the real estate from the management information of the company
  • the analysis unit acquires real estate information from the management information. Analyze and extract limited information from According to this aspect, since limited information including at least the location, use, use area, and size of the real estate property is analyzed and extracted, it is possible to visualize the minimum necessary and important information for the user searching for corporate real estate.
  • the information acquisition unit acquires demand information including limited information on real estate properties
  • the analysis unit combines the limited information on real estate properties in the demand information with the limited information on real estate properties extracted by the analysis unit. are compared and analyzed to calculate matching scores
  • the display data includes data for displaying limited information in descending order of matching scores.
  • the limited information of the real estate property is the minimum information necessary for searching for the real estate property of the company, and matching can be performed with such little information, so when matching with more information Compared to , it is easier to match real estate that meets your needs. This makes it easier to find properties that meet your needs.
  • the information acquisition unit acquires map information
  • the display data includes a limited information display field for displaying limited information of real estate properties whose matching score is equal to or greater than a predetermined value, and a map from the map information. and a map information display field for displaying the matching score superimposed on the position of the real estate property on the map.
  • the display data includes a property number display field in which the number of real estate properties for each area is superimposed on the map, and a limited information property number display field that displays the number of properties for each item of the limited information.
  • the property number display column is displayed by superimposing the number of real estate properties for each area on the map, the number of real estate properties for each area can be understood at a glance.
  • the limited information property number display column the number of properties can be known for each item of the limited information as a breakdown, so it is easy to find a corporate real estate property that matches the needs.
  • the storage unit is configured to store specific keywords related to corporate real estate transactions, and determines whether the specific keywords are included in the management information acquired by the information acquisition unit. and a company selection unit that selects companies that have been determined by the keyword determination unit to include a specific keyword in their management information as business target company candidates.
  • Output data According to this aspect, companies that may have a demand for real estate transactions are displayed as business target company candidates from the management information of the companies, and even keywords related to real estate transactions and real estate utilization are visualized as individual information of the companies. Therefore, it is possible to understand the real estate transaction trends and usage trends of the company at a glance, and to make it easier to formulate a sales strategy for the real estate of the company.
  • a storage medium of the present invention is a computer-readable storage medium storing a program for causing a computer to execute information analysis processing on management information including real estate keywords related to corporate real estate utilization.
  • the information analysis process includes steps of acquiring management information of a plurality of companies, specifying the analysis range of the management information, and identifying keywords included in the acquired management information of each company for real estate utilization. It includes a step of analyzing and extracting relevant real estate keywords in the analysis range, and a step of outputting display data for displaying a keyword display field containing the real estate keywords of the extracted company as individual information of the company.
  • the information analysis processing of the present invention can be executed by reading and executing the program stored in the storage medium of this aspect with a computer, and the computer can function as an information analysis device.
  • a program of the present invention is a program for causing a computer to execute information analysis processing on management information including real estate keywords related to corporate real estate utilization, wherein the information analysis processing includes a plurality of a step of acquiring management information of each company; a step of specifying the analysis range of the management information; It includes a step of analyzing and extracting, and a step of outputting display data for displaying a keyword display column containing the real estate keyword of the extracted company as individual information of the company.
  • the information analysis processing includes steps of acquiring real estate information of a plurality of companies, identifying limited information of the real estate from the real estate information, A step of analyzing and extracting limited information from property information, and a step of outputting display data for displaying a limited information display column of a company containing the extracted limited information as individual information of the company.
  • the information analysis processing comprises steps of acquiring management information of a plurality of companies, a step of selecting a company determined to include a specific keyword in its management information as a candidate company for business; and displaying a company candidate display column containing the selected candidate company for business together with individual information. and outputting the display data.
  • the present invention by visualizing keywords and specific limited information obtained by analyzing the management information and property information of a company, it is possible to grasp the real estate utilization trend of the company at a glance. You can make it easier to set up a sales strategy for
  • FIG. 1 is a block diagram showing a specific configuration example of an information analysis system according to a first embodiment
  • FIG. It is a figure which shows the structural example of the keyword database of 1st Embodiment.
  • FIG. 4 is a diagram showing a specific example of a display screen according to the first embodiment
  • FIG. 4 is a flowchart showing a specific example of information analysis processing according to the first embodiment
  • 6 is a flowchart showing a specific example of keyword analysis processing according to the first embodiment
  • FIG. 10 is a diagram showing a configuration example of a data table that stores hot keywords according to the second embodiment; It is a figure which shows the structural example of the data table which memorize
  • FIG. 11 is a block diagram showing a specific configuration example of an information analysis device according to a third embodiment; FIG. FIG. 11 is a diagram showing a configuration example of a data table that stores specific keywords according to the third embodiment; It is a figure which shows the structural example of the data table which memorize
  • FIG. 11 is a flowchart showing a specific example of information analysis processing according to the third embodiment; FIG. FIG.
  • FIG. 11 is a flowchart showing a specific example of specific keyword determination processing according to the third embodiment;
  • FIG. It is a figure which shows the specific example of the display screen of 3rd Embodiment.
  • It is a block diagram which shows the specific structural example of the information-analysis system of 4th Embodiment.
  • FIG. 14 is a flow chart showing a specific example of information analysis processing according to the fourth embodiment;
  • FIG. FIG. 14 is a flow chart showing a specific example of matching analysis processing according to the fourth embodiment;
  • FIG. 16 is a flow chart showing a specific example of information analysis processing according to the fifth embodiment;
  • FIG. FIG. 21 is a block diagram showing a specific configuration example of an information analysis device according to a sixth embodiment;
  • FIG. 12 is a diagram showing a specific example of a display screen according to the sixth embodiment;
  • FIG. 21 is a block diagram showing a specific configuration example of an information analysis device according to a seventh embodiment;
  • FIG. 21 is a diagram showing a specific example of a display screen according to the seventh embodiment;
  • FIG. 1 is a diagram showing the configuration of an information analysis system 100 according to the first embodiment.
  • an information analysis system 100 includes an information analysis device 10 and a terminal device 20.
  • the information analysis device 10 of the first embodiment analyzes real estate keywords related to real estate utilization obtained from management information such as a business plan, and outputs display data for displaying the analysis results to the terminal device 20 ( Hereinafter, this function is also referred to as "first function").
  • the information analysis device 10 here is exemplified by a server computer that uses the terminal device 20 as a client.
  • the information analysis device 10 may be configured to perform distributed processing by a plurality of devices, or may be configured by a plurality of virtual machines provided in one server device. Further, the information analysis device 10 may be configured by a personal computer or may be configured by a cloud server. The information analysis device 10 and the terminal device 20 are configured to communicate with each other via a network N such as the Internet.
  • the information analysis device 10 is configured to be able to communicate with an external management information providing server 30 via the network N.
  • the management information providing server 30 is a server that provides corporate management information such as management plans and securities reports.
  • the management information providing server 30 may be a server that provides management information on a company's home page or the like, or may be a server of an operator that operates a management information site that provides management information of a plurality of companies.
  • the network N may be composed of an intranet connecting the information analysis device 10 and the terminal device 20 and the Internet connecting the information analysis device 10 and the management information providing server 30 .
  • the terminal device 20 is an information processing device used by the user.
  • the terminal device 20 is, for example, a mobile terminal such as a smart phone, a tablet, or a PDA (Personal Digital Assistant), a desktop personal computer, a notebook personal computer, or the like.
  • a plurality of terminal devices 20 may be connected to the network N.
  • FIG. 1 A plurality of terminal devices 20 may be connected to the network N.
  • FIG. 2 is a block diagram showing a specific configuration example of the information analysis system 100 according to the first embodiment.
  • the information analysis device 10 shown in FIG. 2 includes a communication section 11, a control section 12, and a storage section .
  • the communication unit 11, the control unit 12, and the storage unit 14 are each connected to the bus line 10L, and can mutually exchange information (data).
  • the communication unit 11 is connected to the network N by wire or wirelessly, and transmits and receives information (data) to and from the terminal device 20 and the management information providing server 30 .
  • the communication unit 11 functions as a communication interface for the Internet or an intranet, and is capable of communication using, for example, TCP/IP, Wi-Fi (registered trademark), and Bluetooth (registered trademark).
  • the control unit 12 comprehensively controls the information analysis device 10 as a whole.
  • the control unit 12 is composed of an integrated circuit such as an MPU (Micro Processing Unit).
  • the control unit 12 includes a CPU (Central Processing Unit), a RAM (Random Access Memory), and a ROM (Read Only Memory).
  • the control unit 12 loads a necessary program into the ROM and executes the program using the RAM as a work area, thereby performing various processes.
  • the storage unit 14 is a storage medium (computer-readable tangible storage medium: a tangible storage medium) for storing an information analysis program (to be described later) executed by the control unit 12, other various programs, and data used by these programs. ) is an example.
  • the storage unit 14 is configured by a storage device such as a hard disk or an optical disk.
  • the configuration of the storage unit 14 is not limited to these, and the storage unit 14 may be configured by a semiconductor memory such as RAM or flash memory.
  • the storage unit 14 can be configured with an SSD (Solid State Drive).
  • the storage unit 14 includes a program storage unit 141, a company information database 142 (company information DB), a management information database 143 (management information DB), a keyword database 144 (keyword DB), a score database 145 (score DB), and the like.
  • the program storage unit 141 stores an information analysis program executed by the control unit 12, other various programs, and the like.
  • the control unit 12 reads necessary programs from the program storage unit 141 and executes various processes.
  • the company information database 142 stores company information such as company names of listed companies, security codes (stock codes), and listed markets (Tokyo Stock Exchange, Nagoya Stock Exchange, Fukuoka Stock Exchange, etc.).
  • company information database 142 can store information useful for sales of real estate transactions to each company.
  • the company information database 142 may store basic company information such as capital, industry, business type, number of employees, closing date, and location.
  • the management information database 143 stores management information to be analyzed by the information analysis device 10 for each company.
  • Management information includes IR (Investor Relations) information for investors, such as management plans (mid-term management plans, etc.), securities reports, quarterly reports, and financial results briefing reports.
  • IR Investor Relations
  • the management information is not limited to IR information, and includes, for example, management information published on corporate websites.
  • the keyword database 144 stores real estate keywords and the like used for analyzing management information.
  • FIG. 3 is a diagram showing a configuration example of a data table of the keyword database 144. As shown in FIG. As shown in FIG. 3, the keyword database 144 stores real estate keywords FK1, FK2, .
  • a real estate keyword is a keyword that is relevant to corporate real estate utilization. A plurality of real estate keywords are preset in the keyword database 144 . Note that the configuration of the keyword database 144 is not limited to that shown in FIG.
  • the medium-term management plan and the annual securities report are time-series continuous management information, as they are issued for each fiscal year or period. Therefore, when we focused on this point and conducted various analyzes, we found that terms that are likely to be used by companies and industries certainly appeared frequently in past management information.
  • the analysis range of management information so that, for example, not only the latest management information but also past management information can be specified.
  • the real estate keywords FK1, FK2, are preferable that the real estate keywords FK1, FK2, .
  • a real estate keyword trends in real estate utilization by companies (for example, what kind of real estate is there, what kind of use do you want to use it for, and whether there is a possibility of buying and selling or leasing, including demand and its potential demand)
  • a keyword is set that understands. If it is possible to display keywords that show trends in corporate real estate utilization, it will be possible to predict corporate needs from those keywords.
  • Such real estate keywords FK1, FK2, are examples of real estate keywords that show trends in corporate real estate utilization, it will be possible to predict corporate needs from those keywords.
  • FIG. 4 is a diagram showing a configuration example of a data table that stores the score database 145 (score DB).
  • score database 145 company ID, company name, analysis range, real estate keyword (real estate KW), management information (mid-term management plan, etc.) and the number of appearances of the keyword (KW appearance number), etc. are associated with each company. stored. Note that the configuration of the database that stores word scores of real estate keywords is not limited to that shown in FIG.
  • FIG. 4 illustrates a case where management information P(n) and management information P(n-1) are specified as the analysis range.
  • FK1, FK2, . . . are real estate keywords (real estate KW) in FIG. CFK1(n), CFK2(n), . . . are the number of appearances of real estate keywords FK1, FK2, . CFK1(n ⁇ 1), CFK2(n ⁇ 1), . WFK1, WFK2, . . . are word scores of real estate keywords FK1, FK2, .
  • the word score is calculated for each real estate keyword, and is used, for example, to determine the keyword display (character size, etc.) as a trend of corporate real estate utilization.
  • the keyword appearance count (KW appearance count) in FIG. 4 is the appearance count for each real estate keyword included in the management information, and the keyword total appearance count (CFKt(n), etc.) is the total appearance count of all real estate keywords. .
  • the word score is calculated for each company based on the number of times the real estate keyword appears in the management information within the specified scope of analysis. Therefore, the word score of the present embodiment depends on the specified scope of analysis. For example, if the specified analysis range is only the latest management information of the company, the word score is the number of occurrences of each real estate keyword included in the latest management information. At this time, for example, a value obtained by multiplying the number of occurrences by a weighting factor may be used as the word score. In that case, the weighting factor may be adjusted to lower the word score of real estate keywords that appear frequently in past management information. As a result, new and characteristic terms in the latest management information can be made visible more prominently than terms that are often used in past management information.
  • the specified scope of analysis is the company's latest management information and past management information
  • for each real estate keyword based on the number of appearances in the latest management information and the number of appearances in past management information Calculate word score. For example, as shown in FIG. 4, if the analysis range is the latest management information P(n) and the previous past management information P(n ⁇ 1), the latest management information P(n) for each of the real estate keywords A word score is calculated from the number of appearances and the number of appearances in the previous management information P(n-1).
  • the rate of increase in the ratio of the number of appearances of all real estate keywords to the total number of appearances of keywords may be used as the word score.
  • the word score WFK1 of the real estate keyword FK1 in FIG. 4 will be taken as an example.
  • Let RFK1(n) ( CFK1(n)/CFK1t(n)) be the ratio of the number of appearances of the real estate keyword FK1 to the total number of appearances of the keyword in the latest management information P(n).
  • a word score WFK1 can be calculated.
  • WFK1 (RFK1(n)/RFK1(n ⁇ 1) ⁇ 1) ⁇ 100 ...
  • FIG. 5 shows a specific example of the display screen SCK1 displaying the analysis result of such management information.
  • FIG. 5 is a diagram showing a specific example of the display screen SCK1 displayed on the terminal device 20.
  • a keyword display field KS is displayed on the display screen SCK1.
  • the keyword display field KS displays real estate keywords indicating real estate usage trends of companies.
  • the real estate keywords in FIG. 5 are emphasized and displayed such that the higher the word score, the larger the character size, for example.
  • KF1 "Inbound” with a word score WFK2 of 400% is displayed in large characters
  • KF1 "Sales” with a word score WFK1 of 0% is not displayed. .
  • keywords that have been used frequently in the past such as "sales”
  • distinctive keywords that are rapidly increasing in importance such as "inbound” can be can also be represented in capital letters.
  • the highlighting of real estate keywords is not limited to changing the character size as shown in FIG.
  • the font or color of characters may be changed for highlighting.
  • the display of real estate keywords is not limited to a display like a word cloud.
  • a list of real estate keywords may be displayed such that the higher the word score, the higher the ranking.
  • the control unit 12 shown in FIG. 2 includes an information acquisition unit 121, an analysis range identification unit 122, an analysis unit 124, and an output unit .
  • Each component of the control unit 12 may be configured by a physical circuit, or may be configured by a program executable by the CPU.
  • the configuration of the control unit 12 is not limited to the configuration shown in FIG.
  • the information acquisition unit 121 acquires management information of multiple companies from the management information providing server 30 via the communication unit 11 .
  • the information acquisition unit 121 scrapes a management information providing site operated by the management information providing server 30 to acquire document data of management information of a plurality of companies.
  • the information acquisition unit 121 can periodically crawl specific management information providing sites and automatically acquire document data of management information of various companies.
  • the information acquisition unit 121 stores it in the management information database 143 as it is. PDF captured as an image) is converted into data that can be searched for character strings and stored in the management information database 143 .
  • XBRL eXtensible Business Reporting Language
  • XML eXtensible Markup Language
  • document data of management information obtained through another route can also be added to the management information database 143 by the information acquisition unit 121 .
  • the information acquisition unit 121 receives document data of management information in response to a user operation from the terminal device 20 and adds it to the management information database 143 .
  • the management information database 143 As a result, for example, even when management information of an unlisted company or document data of undisclosed management information is obtained, it can be added to the management information database 143 .
  • the analysis range specifying unit 122 specifies the analysis range of management information.
  • the analysis range specifying unit 122 specifies the analysis range of management information according to an instruction from the user through the terminal device 20 .
  • the user can specify, via the terminal device 20, which type of management information is to be analyzed from a medium-term management plan, a securities report, etc., and which year or period of management information is to be analyzed as the scope of analysis.
  • management information for a desired year or term can be specified as the analysis range. As described above, past management information can be identified together with the latest management information.
  • the analysis unit 124 analyzes the management information of each company acquired by the information acquisition unit 121 within the analysis range specified by the analysis range specification unit 122 . Specifically, the analysis unit 124 counts the number of appearances in each piece of management information for a real estate keyword such as that shown in FIG.
  • the output unit 130 outputs display data for displaying the keyword display column containing the company's real estate keyword extracted by the analysis unit 124 as the company's individual information. Specifically, the output unit 130 generates and outputs display data for a keyword display column for displaying keywords emphasized according to the word score calculated by the analysis unit 124 .
  • the display data is transmitted to the terminal device 20 via the communication section 11 .
  • the terminal device 20 displays the keyword display field based on the display data.
  • the display data may be Web screen data.
  • the information analysis device 10 displays the keyword on the web screen.
  • the terminal device 20 receives the web screen data and displays it on the browser.
  • the communication unit 21, the control unit 22, the storage unit 24, the input unit 25, and the display unit 26 are each connected to the bus line 20L, and can mutually exchange information (data).
  • the communication unit 21 is connected to the network N by wire or wirelessly, and transmits and receives information (data) to and from the information analysis device 10 .
  • the communication unit 21 functions as a communication interface for the Internet or an intranet, and is capable of communication using, for example, TCP/IP, Wi-Fi (registered trademark), and Bluetooth (registered trademark).
  • the control unit 22 controls the terminal device 20 as a whole.
  • the control unit 22 is composed of an integrated circuit such as an MPU (Micro Processing Unit).
  • the control unit 22 includes a CPU (Central Processing Unit), a RAM (Random Access Memory), and a ROM (Read Only Memory).
  • the control unit 22 loads necessary programs into the ROM and executes the programs using the RAM as a work area, thereby performing various processes.
  • the storage unit 24 is an example of a storage medium (computer-readable tangible storage medium: a tangible storage medium) that stores various programs executed by the control unit 22 and data used by these programs.
  • the storage unit 24 stores various programs executed by the control unit 22 and data used by these programs.
  • the storage unit 24 is configured by a storage device such as a hard disk or an optical disk.
  • the configuration of the storage unit 24 is not limited to these, and the storage unit 24 may be configured by a semiconductor memory such as RAM or flash memory.
  • the storage unit 24 can be configured with an SSD (Solid State Drive).
  • the input unit 25 includes a keyboard, a mouse, and the like, receives operation inputs from the user, and transmits control signals corresponding to the operation contents to the control unit 22 .
  • the input unit 25 may have a touch panel.
  • the display unit 26 is a liquid crystal display, an organic EL display, or the like, and displays various information according to instructions from the control unit 22 . Based on the display data received from the information analysis device 10 via the communication unit 21 , the control unit 22 displays a company list of potential sales destination companies on the display unit 26 .
  • the first function is a keyword display function that enables grasping trends in corporate real estate utilization by analyzing management information using real estate keywords related to real estate utilization.
  • FIG. 6 is a flowchart showing a specific example of information analysis processing. The information analysis process is executed by reading necessary programs from the program storage unit 141 by the control unit 12 (information acquisition unit 121, analysis range identification unit 122, analysis unit 124, output unit 130, etc.).
  • the control unit 12 acquires management information of each company.
  • the information acquisition unit 121 acquires document data of management information of each company from the management information providing server 30 via the communication unit 11 and stores it in the management information database 143 .
  • the information acquisition unit 121 stores the acquired management information in the management information database 143 as it is in the case of document data (PDF, XML, XBRL, etc. including text) that can be searched for character strings (text search), and the document data that cannot be searched for character strings.
  • PDF PDF, XML, XBRL, etc. including text
  • text search text search
  • the document data that cannot be searched for character strings In the case of (eg, PDF in which a document is captured as an image), it is converted into character string searchable data and stored in the management information database 143 .
  • the control unit 12 specifies the analysis range of management information.
  • the analysis range specifying unit 122 specifies the analysis range based on preset information. For example, the latest management information (most recent management information) and immediately preceding management information (past management information) as described above are set by default as the analysis range. Note that the specification of the analysis range is not limited to the default settings.
  • specific information of the analysis range set by the user on the terminal device 20 may be used.
  • the information acquisition unit 121 acquires the specific information of the analysis range set by the user from the terminal device 20, and the control unit 12 sets the analysis range from the acquired specific information.
  • the analysis range specifying unit 122 specifies the analysis range based on the set information.
  • step S130 the control unit 12 performs keyword analysis processing.
  • the analysis unit 124 performs keyword analysis processing of the management information acquired by the information acquisition unit 121 .
  • This keyword analysis process is performed on management information within the specified analysis range.
  • the management information acquired by the information acquisition unit 121 is analyzed as the latest management information. If not only the latest management information but also past management information is specified in the analysis range, the control unit 12 reads out the past management information of the company from the storage unit 14 and performs keyword analysis processing. Keyword analysis processing is performed, for example, as shown in FIG.
  • FIG. 7 is a flowchart showing a specific example of keyword analysis processing.
  • the analysis unit 124 counts the number of occurrences of the real estate keyword (real estate KW) from the document data of the management information within the specified analysis range.
  • the analysis unit 124 calculates a word score based on the counted number of appearances, and stores the word score in the score database 145 . This word score is the analysis result of keyword analysis.
  • the output unit 130 generates display data and transmits the display data to the terminal device 20, so that the keywords highlighted according to the word scores are displayed.
  • the output unit 130 generates display data such that the characters are larger as the word score is higher.
  • the process of step S ⁇ b>140 may be executed by the output unit 130 upon receiving a display request from the terminal device 20 .
  • the processing of steps S110 to S140 is executed upon request from the terminal device 20.
  • FIG. Further, the process of step S110 may be automatically executed by periodic crawling of a specific management information providing site.
  • the information analysis apparatus 10 by acquiring management information of a company, specifying the analysis range, and analyzing the management information with keywords, for example, keywords frequently used by the company Keywords with distinctive features can be made to stand out.
  • keywords for example, keywords frequently used by the company Keywords with distinctive features
  • keywords can be displayed so that the company's real estate utilization trend can be seen at a glance, so the time and effort required for strategy planning can be greatly reduced, and sales activities can be made more efficient.
  • the analysis range identification unit 122 includes not only the current management information but also the past management information in the analysis range, so that the analysis unit 124 obtains , keywords that are not included in the past management information of the company are extracted as the latest keywords.
  • the management information of the same company is often issued periodically in a similar format, and the latest keywords of the company can be efficiently extracted by using the past management information of the same company.
  • the entire management information such as a management plan or securities report may be compared, or specific items may be compared. Being able to do this is one of the features of the present invention when using management information that is often issued periodically in the same format for the same company.
  • the analysis range identification unit 122 may search for items including real estate keywords and compare the searched items.
  • the latest keyword here may be a real estate keyword or a hot keyword to be described later.
  • the latest hot keyword can also be extracted from the management information by the same comparative analysis as in the case of the real estate keyword described above.
  • the above real estate keywords can be read as hot keywords.
  • the output unit 130 can also output display data for displaying the latest keyword with priority over other keywords. According to this, it is possible to preferentially display (for example, raise the display order, highlight, etc.) the latest keyword that is a hot topic in the management information.
  • the output unit 130 changes the character size according to the number of appearances of the keyword, and outputs display data in which the latest keyword is displayed in larger characters than the keywords included in the past management information. good too. As a result, the newest keywords stand out, so that it can be seen at a glance that the management information is being talked about.
  • the analysis unit 124 separately extracts the real estate keywords included in the management information acquired by the information acquisition unit 121 and the real estate keywords included in the past management information
  • the output unit 150 extracts the first keyword display field.
  • display data for displaying real estate keywords included in past management information may also be output to KS1. According to this, past real estate keywords and the latest real estate keywords can be compared, so that changes in trends in the real estate usage trends of the company can be understood at a glance.
  • the analysis unit 124 of the second embodiment separately analyzes and extracts real estate keywords and hot keywords from the keywords included in the management information acquired by the information acquisition unit 121 .
  • the keyword display fields of the second embodiment include a first keyword display field KS1 containing real estate keywords extracted by the analysis unit 124 and a second keyword display field KS2 containing hot keywords.
  • FIG. 8 is a diagram showing a specific example of the display screen SCK2 displayed on the terminal device 20 in the second embodiment.
  • a first keyword display field KS1 containing real estate keywords indicating real estate utilization trends of companies in FIG. 5 and a second keyword display field KS2 containing hot keywords indicating industry trends of the companies are displayed in parallel.
  • hot keywords are also displayed in different font sizes according to word scores. According to this, not only real estate utilization trends of companies, but also industry trends (environmental trends) of the companies can be understood at a glance, so it is easy to understand why the companies are using the real estate trends. This will allow us to gain a deeper understanding of the company's real estate usage trends, making it easier to formulate a sales strategy that will have a deep impact on that company.
  • the keyword database 144 of the second embodiment stores not only real estate keywords (real estate KW) as shown in FIG. 3, but also hot keywords (hot KW) as shown in FIG.
  • FIG. 9 is a diagram showing a configuration example of a hot keyword data table.
  • the keyword database 144 stores hot keywords FH1, FH2, .
  • Hot keywords are keywords that are related to environmental trends surrounding companies.
  • a keyword database 144 stores a plurality of hot keywords. Hot keywords may be classified by industry and stored in the keyword database 144 .
  • the configuration of the hot keyword data table is not limited to that shown in FIG.
  • the hot keywords FH1, FH2, ... here preferably include keywords related to environmental trends surrounding companies.
  • a hot keyword a keyword that shows the trend of the industry is set, such as a keyword that is currently a hot topic in the industry or the world. If you can display hot keywords that show trends in the industry and the world, you can understand the environment surrounding the company you are selling from the hot keywords.
  • keywords in the latest management information can be analyzed in comparison with the past, so for example, even a term that appears frequently in the latest management information will have a low word score if it appears frequently in past management information.
  • the hot keyword word scores obtained by analyzing management information within the specified analysis range are stored in the score database 145 in association with each industry.
  • the score database 145 of the second embodiment stores a data table for each industry as shown in FIG. 10 in addition to the data table for each company as shown in FIG.
  • FIG. 10 is a diagram showing a configuration example of a data table that stores word scores of hot keywords.
  • FIG. 10 differs from FIG. 4 in that real estate keywords and their word scores are stored for each company in FIG. 4, whereas hot keywords and their word scores are stored for each industry in FIG. .
  • the industry ID, industry name, analysis range, hot keyword (hot KW), management information (mid-term management plan, etc.) and the number of appearances of the keyword (number of appearances of KW), etc. are associated with each industry. stored. Note that the configuration of the data table that stores the word scores of hot keywords is not limited to that shown in the figure.
  • FIG. 10 illustrates a case where management information P(n) and management information P(n-1) are specified as the analysis range.
  • FH1, FH2, . . . are hot keywords (hot KW) in FIG. CHK1(n), CHK2(n), . . . are the numbers of occurrences of hot keywords FH1, FH2, . CHK1(n ⁇ 1), CHK2(n ⁇ 1), . . . are the number of appearances of hot keywords FH1, FH2, . WHK1, WHK2, . . . are word scores of hot keywords FH1, FH2, .
  • a word score is calculated for each hot keyword, and is used, for example, to determine keyword display (character size, etc.) as an industry trend.
  • the keyword appearance count (KW appearance count) in FIG. 10 is the appearance count for each hot keyword included in management information
  • the keyword total appearance count (CFKt(n), etc.) is the total appearance count of all hot keywords. .
  • the word score is calculated for each industry based on the number of occurrences of hot keywords in management information within the specified scope of analysis. While the analysis range of the first embodiment is management information for each company, the analysis range of the second embodiment is management information for each industry, that is, management information of a plurality of companies included in the industry. differ.
  • the analysis unit 124 of the second embodiment analyzes and extracts hot keywords associated with the industry from the management information within the analysis range. In this way, the scope of hot keyword analysis is not the management information of individual companies, but the management information of multiple companies within the industry of that company. It is possible to efficiently acquire hot keywords for the entire industry, including up to.
  • the word score in the second embodiment also changes depending on the specified analysis range.
  • the specified analysis range is limited to the latest management information of the industry
  • the word score is the number of occurrences of each hot keyword included in the latest management information.
  • a value obtained by multiplying the number of occurrences by a weighting factor may be used as the word score.
  • the word score of hot keywords that appear frequently in past management information may be lowered.
  • new and characteristic terms in the latest management information can be made visible more prominently than terms that are often used in past management information.
  • each hot keyword is based on the number of appearances in the latest management information and the number of appearances in past management information. Calculate word score. For example, as shown in FIG. 4, if the analysis range is the latest management information P(n) and the past management information P(n ⁇ 1) immediately before that, the latest management information P(n) for each hot keyword A word score is calculated from the number of appearances and the number of appearances in the previous management information P(n-1).
  • the word score may be the rate of increase in the ratio of the number of appearances of all hot keywords to the total number of appearances of the keyword.
  • the word score is the "increase in importance,” which indicates how much the importance of a hot keyword has increased from the immediately preceding management information, by recognizing that the higher the ratio of all hot keywords to the number of times they appear, the more important the term is. can be calculated as
  • the word score WHK1 of the hot keyword FHK1 in FIG. 10 will be taken as an example.
  • a word score WHK1 can be calculated.
  • WHK1 (RHK1(n)/RHK1(n-1)-1) x 100 ... (2)
  • FIG. 8 shows a specific example of the display screen SCK2 on which the word scores WHK1, WHK2, . . . are calculated and the analysis results are displayed.
  • FIG. 8 is a diagram showing a specific example of the display screen SCK2 of the second embodiment.
  • a keyword display field KS is displayed on the display screen SCK2 of FIG.
  • the keyword display field KS includes a first keyword display field KS1 and a second keyword display field KS2.
  • the first keyword display field KS1 displays real estate keywords indicating real estate utilization trends of companies
  • the second keyword display field KS2 displays hot keywords indicating industry trends. As with the real estate keywords, the hot keywords in FIG. 8 are emphasized and displayed such that the higher the word score, the larger the character size, for example.
  • the first keyword display field KS1 and the second keyword display field KS2 are arranged side by side with respect to the display screen SCK2.
  • the arrangement positions of the first keyword display field KS1 and the second keyword display field KS2 are not limited to those shown in the figure, and may be arranged vertically, for example.
  • real estate keywords that indicate a company's real estate usage trend and hot keywords that indicate the company's industry trends side by side the company's real estate usage trends and environmental trends surrounding the industry can be grasped at a glance. This makes it easy to understand why the company is using that real estate trend.
  • the highlighting of hot keywords is not limited to changing the character size as shown in FIG. For example, the font or color of characters may be changed for highlighting. Also, the display of hot keywords is not limited to this. For example, a list of hot keywords may be displayed so that the higher the word score, the higher the ranking.
  • the information analysis processing by the second function performed by the second embodiment is the same as in FIGS. 6 and 7.
  • the analysis range of the second embodiment is the management information for each industry, that is, the management information of a plurality of companies in the industry, as described above.
  • the third embodiment exemplifies the third function of displaying on the terminal device 20 a candidate list of business partner companies that are selected companies with a high possibility of real estate transactions by analyzing the management information of a plurality of companies.
  • the third function is a function of displaying a list of business target company candidates by analyzing management information using specific keywords related to real estate transactions. According to this, individual information (real estate keywords that indicate the company's real estate utilization trends and industry trends) of companies specified by hovering or clicking the cursor among the companies listed in the candidate company list hot keywords, etc.) can be displayed on the same display screen of the terminal device 20.
  • FIG. 11 is a block diagram showing a specific configuration example of the information analysis apparatus of the third embodiment. 11 differs from FIG. 2 in that the control unit 12 is provided with a keyword determination unit 126 and a company selection unit 128 . Specific keywords and weighting factors are stored in the keyword database 144 (keyword DB) of the third embodiment.
  • FIG. 12 is a diagram showing a configuration example of a data table that stores specific keywords.
  • the specific keyword here is a keyword related to real estate transactions, and is used to select business target company candidates that are likely to have demand for real estate transactions.
  • specific keywords are keywords that may be included in the management information of companies with demand for real estate transactions (including demand for real estate sales and leasing, and potential demand for such). Companies can be selected.
  • Such specific keywords include "trend prediction keywords” for predicting trends in corporate real estate transactions, and "key man keywords” for finding companies with executives who can easily understand the necessity of real estate securitization. ', and 'facility status keywords' for finding companies that own real estate and real estate facilities that are likely to have demand for real estate transactions.
  • a plurality of specific keywords are divided into a plurality of keyword groups GA1, GA2, . . . , and each keyword group GA1, GA2, . be.
  • the "efficiency-related keywords” include, for example, specific keywords such as the above-described "asset efficiency improvement.”
  • the "financial keywords” include, for example, the aforementioned "interest-bearing debt reduction”.
  • the weighting factor for keyword group GA1 is WA1
  • the weighting factor for keyword group GA2 is WA2.
  • the probability of business success is higher than when a specific keyword of the keyword group GA1 appears. is set to be large. As a result, it becomes possible to analyze management information that reflects a high degree of interest in real estate transactions based on knowledge of corporate management related to real estate transactions, so that influential companies are more likely to be selected as business destinations.
  • the score database 145 stores the number of appearances of specific keywords associated with each piece of management information and the sales destination score (index value) for each company.
  • the customer score is calculated for each piece of management information, and is used, for example, as approach information for selecting customer company candidates and determining the display order.
  • the sales destination score is calculated based on the number of appearances of a specific keyword in each keyword group and a weighting factor. Specifically, the sales destination score is calculated from the word hit information obtained from the number of occurrences of the specific keyword for each keyword group and the weighting coefficient.
  • the word hit information is information that serves as an index of how many specific keywords included in the keyword group were included in the management information (hit) for each keyword group. According to the word hit information, it is possible to know how many specific keywords of which keyword group appeared in the management information.
  • the word hit information is, for example, the total number of appearances of all specific keywords included in the keyword group. However, it is not limited to this, and for example, if even one of the specific keywords included in the keyword group is included in the management information, the word hit information may be set to 1 (hit). Further, a numerical value obtained by normalizing or standardizing the number of appearances of each specific keyword included in the keyword group may be used as the word hit information.
  • the business partner score can be interpreted as the word coverage rate of a specific keyword.
  • FIG. 13 a configuration example of a data table that stores such sales destination scores will be described with reference to FIG.
  • the data table of FIG. 13 is stored in the score database 145.
  • the configuration of the data table that stores the sales destination scores is not limited to that shown in FIG.
  • the data table in FIG. 13 stores information such as company IDs, types of management information, basic information of management plans such as company names, keyword groups used for analysis of management information, weight coefficients, and specific keywords.
  • the number of appearances HA11 in FIG. 13 is the number of appearances of the specific keyword KA11 of the keyword group (KW group) GA1, and the number of appearances HA21 is the number of appearances of the specific keyword KA21 of the keyword group GA2.
  • the word hit information of each keyword group in FIG. 13 is, for example, the sum of the number of occurrences of each specific keyword included in the keyword group.
  • HGA1 is obtained by summing up all appearance frequencies HA11, HA12, . . . of specific keywords in the keyword group GA1.
  • the business partner score Sa can be expressed by the following formula (3) from the word hit information HGA1 to HGAn and the weighting coefficients WA1 to WAn.
  • the formula for calculating the sales destination score Sa is not limited to the following formula (3).
  • the weighting factor for each keyword group can be freely set.
  • a skilled salesperson can preset a weighting factor based on his/her own experience, so that the management information of an influential customer company with a high possibility of demand for real estate transactions has a higher customer score.
  • specific keywords are grouped according to common features and weighting factors are set in advance, so that the features and importance of the concept of corporate management are reflected in the sales destination score of management information. be able to. As a result, it is possible to acquire sales destination scores according to the possibility of demand for real estate transactions.
  • the keyword determination unit 126 of the third embodiment performs specific keyword determination to determine whether or not the management information acquired by the information acquisition unit 121 contains the specific keyword of the keyword database 144. Acquire the customer score as a result of analysis of management information.
  • the keyword determination unit 126 reads document data of management information from the management information database 143 and performs specific keyword determination.
  • the keyword determination unit 126 performs specific keyword determination for each management information acquired by the information acquisition unit 121, counts the number of appearances of the specific keyword in each keyword group, and stores the counted number of appearances in the score database 145.
  • the keyword determination unit 126 acquires a business partner score as a result of analysis of management information based on specific keyword determination. Specifically, the keyword determination unit 126 calculates and acquires the sales destination score from the management information based on the number of appearances of the specific keyword in each keyword group and the weighting factor. The keyword determination unit 126 associates the obtained sales destination score with the management information and stores it in the score database 145 .
  • the company selection unit 128 selects companies that have been determined by the keyword determination unit 126 to include a specific keyword in their management information as business target company candidates.
  • the sales destination score of the management information described above is used to select the business destination company candidate.
  • the company selection unit 128 selects companies whose business destination scores in the management information stored in the score database 145 are equal to or greater than a predetermined threshold as business destination company candidates. According to this, by adjusting the predetermined threshold value, the number of business target company candidates can be adjusted, so that, for example, it is possible to prevent the number of business target company candidates with low business target scores from becoming too large.
  • management information that does not contain any specific keywords the number of occurrences of specific keywords is zero, so the business partner score is also zero.
  • Management information containing at least one specific keyword has a business partner score of 1 or more. Therefore, when there are few business target company candidates, for example, companies having a business target score of management information equal to or greater than a threshold value of 1 may be selected as business target company candidates. As a result, companies that include at least one specific keyword can be selected as business target company candidates, so that the number of business target company candidates can be increased.
  • the output unit 130 generates and outputs display data for displaying a company list of business target company candidates selected by the company selection unit 128 .
  • the output unit 130 generates and outputs display data for displaying a list of companies in descending order of business destination scores in the management information.
  • the display data is transmitted to the terminal device 20 via the communication section 11 .
  • the terminal device 20 displays a company list of business target company candidates based on the display data.
  • the display data may be Web screen data.
  • the information analysis device 10 displays a list of business target company candidates on the Web screen.
  • the terminal device 20 receives the web screen data and displays it on the browser.
  • FIG. 14 is a flowchart showing a specific example of information analysis processing.
  • the information analysis process is executed by reading a necessary program such as an information analysis program from the program storage unit 141 by the control unit 12 (information acquisition unit 121, keyword determination unit 126, company selection unit 128, output unit 130, etc.). be.
  • step S210 shown in FIG. 14 the control unit 12 acquires management information of each company. Since this step S210 is the same as the processing of step S110 in FIG. 6, detailed description thereof will be omitted.
  • step S ⁇ b>220 the control unit 12 performs specific keyword determination for each piece of document data of management information acquired by the information acquisition unit 121 .
  • the specific keyword determination it is determined whether or not the specific keyword of each keyword group is included in the document data of the management information, and the frequency of appearance of the specific keyword and the sales destination score of the management information are acquired. Specific keyword determination is performed as shown in FIG. 15, for example.
  • FIG. 15 is a diagram showing a specific example of specific keyword determination processing.
  • the control unit 12 acquires the number of appearances of each specific keyword (specific KW) for each keyword group.
  • the keyword determination unit 126 reads the management information document data from the management information database 143, and determines whether or not the document data includes the specific keyword associated with each keyword group in the keyword database 144. , to count the number of occurrences of a particular keyword.
  • the keyword determination unit 126 stores the counted number of appearances in the score database 145 in association with the management information.
  • step S222 the control unit 12 calculates the sales destination score of the management information based on the number of appearances of the specific keyword associated with the management information and the weighting factor.
  • the keyword determination unit 126 calculates a sales target score from word hit information obtained from the number of appearances of a specific keyword for each keyword group and a weighting factor, and stores the score in the score database 145 in association with the management information.
  • Calculation of business partner scores in step S222 is performed for all document data of management information acquired by the information acquisition unit 121 .
  • This sales destination score is the analysis result of the management information based on the determination of the specific keyword.
  • step S230 shown in FIG. 14 the control unit 12 selects business target company candidates from the analysis results of management information based on specific keyword determination. Specifically, the company selection unit 128 selects companies whose sales destination scores in the management information stored in the score database 145 are equal to or greater than a predetermined threshold value as sales destination company candidates. It should be noted that the processing of step S230 is performed for the sales destination scores of the latest management information for all companies stored in the score database 145. FIG. This makes it possible to always select business target company candidates based on the latest management information.
  • step S240 the control unit 12 causes the terminal device 20 to display the companies selected in step S230.
  • the output unit 130 generates display data and transmits the display data to the terminal device 20, thereby causing the terminal device 20 to display the company list selected by the company selection unit 128 as approach information.
  • the output unit 130 generates and outputs display data for displaying the candidate company display field LS such that the selected company is displayed in the order of highest sales destination score.
  • the process of step S ⁇ b>240 may be executed by the output unit 130 upon receiving a display request for approach information from the terminal device 20 .
  • the processing of steps S210 to S230 may be automatically executed by periodic crawling of a specific management information providing site, or may be executed upon request from the terminal device 20. .
  • FIG. 16 is a diagram showing a specific example of the display screen SCK3 of the third embodiment.
  • a candidate company display field LS and a keyword display field KS are displayed on the display screen SCK3, and a first keyword display field KS1 and a second keyword display field KS2 are displayed on the keyword display field KS.
  • the first keyword display field KS1 displays real estate keywords indicating real estate utilization trends of companies, and the second keyword display field KS2 displays hot keywords indicating industry trends.
  • the company candidate display field LS when viewing the display screen SCK3 from the front, the company candidate display field LS is arranged on the left side, and the keyword display field KS is arranged on the right side.
  • the first keyword display field KS1 and the second keyword display field KS2 are arranged vertically and displayed.
  • the arrangement positions of the company candidate display field LS, the first keyword display field KS1, and the second keyword display field KS2 are not limited to those shown in the figure, and may be arranged in any manner.
  • a candidate company list is displayed as approach information in the company candidate display field LS.
  • companies with higher scores are displayed at higher ranks.
  • companies with a higher probability of sales success can be displayed higher.
  • the company candidate display field LS displays the number of company candidates (for example, 80 found), a page switching button, and the like.
  • “date”, "company name”, "sales destination score” and the like are displayed. Display items are not limited to those shown in the figure. ”, “sales information”, and “remarks” may be added.
  • an item of search period may be provided so that the period can be entered in the item, and the companies selected by analyzing the management information within the entered period can be narrowed down and displayed.
  • the output unit 130 of the third embodiment highlights the specified business target company candidate in the company candidate display field LS, and also displays the individual information of the specified business target company candidate (the company's real estate keywords indicating real estate utilization trends, etc.) are generated and output to be displayed side by side in the company candidate display field LS.
  • the company is specified, and the individual information of the specified company is displayed in the company candidate display column. It is displayed side by side with LS.
  • each company display field LS1 (individual company display frame) in FIG.
  • the company is highlighted (color change, shading, font change, etc.).
  • a real estate keyword indicating the company's real estate usage trend is displayed in the first keyword display field KS1
  • a hot keyword indicating the industry trend of the company is displayed in the second keyword display field KS2.
  • FIG. 16 is a display example when Company A at the top of each company display field LS1 is clicked
  • the first keyword display field KS1 displays a real estate keyword indicating the real estate utilization trend of Company A.
  • the second keyword display field KS2 displays hot keywords indicating industry trends of company A.
  • the positions and colors of the characters may be random, or may be arranged such that the greater the co-occurrence, the closer they are.
  • the keyword analysis information of each company is displayed side by side.
  • companies with potential demand for real estate transactions are displayed as business target company candidates based on company management information, and even keywords related to real estate transactions and real estate utilization are visualized as individual information for each company. Therefore, it is possible to understand the real estate transaction trends and utilization trends of the company at a glance, making it easier to formulate a sales strategy for the company's real estate.
  • the individual information of that company is displayed. Specifically, if you click on candidate companies one after another, you can see keywords related to the real estate transaction trends and usage trends of that company one after another, making it easy to find the desired business target company. Become.
  • the customer score may be acquired by a trained model learned by machine learning or artificial intelligence (AI: Artificial Intelligence).
  • AI Artificial Intelligence
  • a fourth embodiment of the present invention will be described.
  • a case was exemplified in which a keyword indicating a real estate activity trend of a company is displayed as individual information of the company by the first function.
  • the fourth function is used to display a business target company candidate list together with limited information and map information of real estate properties of those companies as individual information of the company.
  • the fourth function is to analyze the real estate property information in the company's management information by focusing on specific limited information and display the limited information and map information.
  • "Limited information” here is the minimum necessary information for searching for a company's real estate property.
  • FIG. 17 is a block diagram showing a specific configuration example of the information analysis system 100 of the fourth embodiment.
  • the information analysis apparatus 10 of FIG. 17 differs from that of FIG. 2 in that the control unit 12 is provided with a limited information identification unit 123 instead of the analysis range identification unit 122, and the storage unit 14 is provided with a demand information database 146 (demand information DB ) and a map information database 147 (map information DB).
  • the control unit 12 is provided with a limited information identification unit 123 instead of the analysis range identification unit 122
  • the storage unit 14 is provided with a demand information database 146 (demand information DB ) and a map information database 147 (map information DB).
  • the property information of the real estate in the management information of the company is acquired by narrowing it down to specific limited information and displayed on the terminal device 20 .
  • “Limited information” here is the minimum necessary information for searching for a company's real estate property.
  • Such “limited information” includes at least the "location", “usage”, “use area”, “scale of land”, and “scale of building” of the real estate property. It is preferable that the "location” has at least information on prefectures and municipalities.
  • “Use” is the use (asset) of real estate such as “factory” and “warehouse”.
  • Size preferably includes information on "land size” and "building size”. These are the minimum necessary and important information for a user looking for corporate real estate.
  • “Usage zone” here refers to an area where building usage, building coverage ratio, floor area ratio, etc. are regulated.
  • An "industrial zone” is defined primarily to enhance the convenience of industry, while a “semi-industrial zone” is defined primarily to promote the convenience of industry that does not cause environmental deterioration.
  • “Industrial zone” is a zone for promoting the convenience of industry. In this way, the "use district” is important information for confirming what kind of regulations apply to the real estate.
  • the limited information keywords used for analyzing management information are stored in the keyword database 144.
  • a limited information keyword is a keyword used to acquire specific limited information from management information.
  • FIG. 18 is a diagram showing a configuration example of a data table for storing limited information keywords.
  • Specific limited information keywords Limited information keywords LK1, LK2, . . . are preset in the data table of FIG. Note that the configuration of the keyword database 144 is not limited to that shown in FIG.
  • the limited information keyword is preferably a keyword that allows the above-mentioned specific limited information to be obtained from the management information.
  • limited information keywords include "location”, “usage”, “use area”, and “scale”.
  • “Location” is a keyword for acquiring at least prefectures and municipalities
  • "usage” is a keyword for acquiring real estate usage such as "factory” and "warehouse”. It is preferable to divide "scale” into “scale of land” and “scale of building”. As a result, it is possible to acquire scale information separately for land scale and building scale.
  • “Use district” is a keyword for acquiring the type of “use district” of real estate as described above.
  • a description field containing a limited information keyword of a real estate property is found from the management information, and the content of the limited information is obtained from the description field.
  • the limited information keyword does not necessarily have to be used to acquire the limited information.
  • the description column of the limited information of the real estate property is known in advance like the securities report, the content of the limited information can be acquired from the description column.
  • items of limited information may be changed or added by setting the information analysis device 10 or by operating the terminal device 20 .
  • the limited information keyword can also be changed or added according to the changed or added item.
  • Limited information on real estate properties acquired from management information is stored for each company in the company information database 142 (company information DB).
  • the company information database 142 may store not only limited information about real estate properties acquired from management information, but also limited information about real estate properties input from the terminal device 20 . According to this, the user who wants to provide real estate can also input from the terminal device 20 . In this case, when the information analysis device 10 receives the limited information input from the terminal device 20 , it stores it in the company information database 142 . It should be noted that the limited information on real estate properties is not limited to being stored in the company information database 142 .
  • a property information database (property information DB) (not shown) may be separately provided in the storage unit 14 to store limited information of real estate properties.
  • the demand information database 146 stores demand information of users looking for corporate real estate.
  • the demand information includes limited information (needs) of the real estate property that the user is looking for.
  • the demand information database 146 may store registration information such as the user's name, company, email address, and password.
  • a user who is looking for a real estate property inputs registration information from the terminal device 20 and registers it, so that the real estate property of a company can be searched.
  • desired limited information about the real estate property to be searched for is input from the terminal device 20 .
  • the information acquisition unit 121 receives from the terminal device 20 the limited information from the user who is looking for real estate, the information acquisition unit 121 stores the demand information including the limited information of the real estate in the demand information database 146 .
  • the score database 145 stores matching scores (index values) obtained in matching analysis processing.
  • FIG. 19 is a diagram showing a configuration example of a data table that stores the score database 145.
  • the score database 145 of FIG. 19 includes company IDs, company names, types of management information, properties (real estate properties), location information (location information of real estate), limited information keywords (limited information KW), and the number of occurrences of the keywords ( number of appearances of KW), etc. are stored in association with each company. Note that the configuration of the database that stores matching scores is not limited to that shown in FIG.
  • Properties L1, L2, . . . in FIG. 19 are property IDs for identifying each property.
  • the position information GL1, GL2, . . . is GPS information. GPS information is acquired via the network N from the "location" information of the property among the acquired limited information.
  • the limited information keywords LK1, LK2, . . . in FIG. 4 are the limited information keywords in FIG.
  • FIG. 20 shows a case where there are only five items of limited information on a real estate property, where LK1 is "location”, LK2 is “use”, LK3 is “use area”, LK4 is “land size”, and LK5 is "building property”. scale.
  • XL11 is "Tokyo XX Ward”
  • XL12 is “Factory”
  • XL13 is “Factory”
  • XL14 is "2000 tsubo”
  • XL15 is "4000 It is tsubo.
  • XL13 "factory” is a type of land use area, and is a “factory area”.
  • the "semi-industrial” of the second property L2 is a "semi-industrial area”.
  • the evaluation MSL in FIG. 4 is the evaluation of individual limited information and is used in the matching analysis process.
  • the limited information from the user who is looking for the real estate property and the limited information of the company's real estate property are compared and analyzed.
  • the evaluation is set to "0".
  • MSL1 in FIG. 4 is the matching score of property L1
  • MSL2 is the matching score of property L2.
  • the matching score MSL1 of the property L1 is calculated by the following formula (4), where MA is the number of pieces of matching limited information, and MB is the number of pieces of matching limited information.
  • MSL1 (MB/MA) x 100 ...(4)
  • the map information database 147 in FIG. 17 stores map information.
  • the map information in the map information database 147 may be obtained from an external map server (not shown) via the network N based on the location of the property, or may be stored in the map information database 147 in advance. good. For example, when displaying the location of a property on a map as shown in FIG. 20, the number of the matching score of the property may be superimposed on the position on the map based on the GPS information of the property.
  • FIG. 20 shows a specific example of the display screen SDK1 that displays limited information about real estate properties acquired from such management information.
  • FIG. 20 is a diagram showing a specific example of the display screen SDK1 displayed on the terminal device 20.
  • a limited information display field BL and a map information display field BM are displayed on the display screen SDK1.
  • the limited information display field BL a list of real estate properties of companies whose matching score is equal to or higher than a predetermined value is displayed together with limited information. The higher the matching score, the higher the real estate property displayed.
  • FIG. 20 shows a case where there are only five pieces of limited information about real estate, and the five items are "location", "use", “use area”, “scale of land", and "scale of building".
  • the map information display field BM displays a map from the map information and a matching score superimposed on the position of the real estate property on the map.
  • the limited information display column BL and the map information display column BM are arranged side by side with respect to the display screen SDK2.
  • the arrangement positions of the limited information display column BL and the map information display column BM are not limited to those shown in the figure, and may be arranged vertically, for example.
  • the information acquisition unit 121 of the fourth embodiment acquires demand information including limited information on real estate properties from the terminal device 20 and stores it in the demand information database 146 .
  • the information acquisition unit 121 also acquires registration information such as the user's name, company, email address, and password, and stores it in the demand information database 146 . Further, the information acquisition unit 121 acquires map information including the location of the property based on the location of the property obtained from the limited information.
  • the information acquisition unit 121 acquires map information via the network N from an external map server (not shown).
  • the limited information identification unit 123 identifies the limited information from the real estate property information of the management information. Specifically, the limited information identification unit 123 identifies the description column of the limited information from the real estate property information of the management information based on the limited information keyword. It should be noted that items of limited information on real estate properties may be changed by instructions from the user through the terminal device 20 .
  • the analysis unit 124 analyzes and extracts limited information from the real estate property information of each company's management information. Specifically, the content of the limited information is analyzed and extracted from the description column of the limited information specified by the limited information specifying unit 123 . In the case of management information, such as securities reports, in which the entry columns for real estate information are known in advance, the analysis unit 124 may acquire the content of limited information from the entry columns for the real estate information.
  • the analysis unit 124 performs matching analysis processing for calculating matching scores.
  • the matching analysis process compares and analyzes the limited information from the user searching for the real estate property and the limited information of the company's real estate property, and calculates the matching score based on the result.
  • Analysis unit 124 stores the calculated matching score in score database 145 .
  • the output unit 130 generates and outputs display data that displays the limited information display column containing the property list and the matching score together with the limited information extracted by the analysis unit 124 as individual information of the company.
  • the display data also includes a map information display field in which the matching score of the property calculated by the analysis unit 124 is superimposed on the position on the map based on the GPS information of the property.
  • the display data is transmitted to the terminal device 20 via the communication section 11 .
  • the terminal device 20 displays the keyword based on the display data.
  • the display data may be Web screen data.
  • the information analysis device 10 displays the keyword on the web screen.
  • the terminal device 20 receives the web screen data and displays it on the browser.
  • FIG. 21 is a flowchart showing a specific example of information analysis processing.
  • the information analysis process is executed by reading a necessary program such as an information analysis program from program storage unit 141 by control unit 12 (information acquisition unit 121, limited information identification unit 123, analysis unit 124, output unit 130, etc.). be.
  • the control unit 12 acquires management information of each company.
  • the information acquisition unit 121 acquires document data of management information of each company from the management information providing server 30 via the communication unit 11 and stores it in the management information database 143 .
  • the information acquisition unit 121 stores the acquired management information in the management information database 143 as it is in the case of document data (PDF, XML, XBRL, etc. including text) that can be searched for character strings (text search), and the document data that cannot be searched for character strings.
  • PDF PDF, XML, XBRL, etc. including text
  • text search text search
  • the document data that cannot be searched for character strings In the case of (eg, PDF in which a document is captured as an image), it is converted into character string searchable data and stored in the management information database 143 .
  • step S120 the control unit 12 identifies limited information on the real estate property from the management information acquired by the information acquisition unit 121.
  • the limited information identification unit 123 identifies the limited information from the real estate property information of the management information.
  • the limited information identification unit 123 identifies the description column of the limited information from the real estate property information of the management information based on the limited information keyword.
  • step S130 the control unit 12 analyzes and extracts limited information on real estate properties from the management information acquired by the information acquisition unit 121. Specifically, the analysis unit 124 analyzes and extracts the content of the limited information from the description column of the limited information specified by the limited information specifying unit 123 and stores it in the company information database 142 .
  • step S140 the control unit 12 performs matching analysis processing.
  • the analysis unit 124 compares and analyzes limited information on real estate properties included in user demand information and limited information on real estate properties of companies stored in the company information database 142, and performs matching based on the results. Calculate the score.
  • the matching analysis process is performed as shown in FIG. 22, for example.
  • FIG. 22 is a flowchart showing a specific example of matching analysis processing.
  • the information acquisition unit 121 acquires demand information including limited information on real estate properties from the terminal device 20 and stores the demand information in the demand information database 146 .
  • a matching score is calculated based on the limited information (needs) of the real estate property included in the demand information.
  • the analysis unit 124 compares and analyzes the limited information on the real estate property included in the demand information and the limited information on the real estate property of the company stored in the company information database 142, calculates the matching score, and calculates the score database 145. memorize to This matching score becomes the analysis result of the matching analysis.
  • step S150 shown in FIG. 21 the control unit 12 causes the terminal device 20 to display the analysis result of the matching analysis.
  • the output unit 130 generates display data and transmits it to the terminal device 20, so that matching scores are displayed in the limited information display field BL and the map information display field BM as shown in FIG.
  • the output unit 130 displays the limited information display field BL for displaying the property list together with the limited information extracted by the analysis unit 124, and the location of the property calculated by the analysis unit 124 on the map based on the GPS information. It generates and outputs display data including a map information display field BM in which the numbers of matching scores of properties are superimposed and displayed.
  • the processing of steps S110 to S150 is executed upon request from the terminal device 20.
  • FIG. Further, the processing of steps S110 to S130 may be automatically executed by periodical crawling of a specific management information providing site.
  • the limited information specified from the real estate property information of the company is analyzed and displayed. It can be narrowed down and displayed. According to this, specific limited information is visualized as individual information of the company, so it is easier to find the real estate property you really need at a glance compared to the conventional way of including more information. .
  • limited information on real estate properties is the minimum information necessary to search for real estate properties of companies, and matching can be performed with such less information, so compared to matching with more information, Real estate that meets your needs is easy to match. This makes it easier to find properties that meet your needs.
  • a fifth embodiment of the present invention will be described.
  • the fourth function of displaying limited information on corporate real estate properties as shown in FIG. 20 was exemplified.
  • a case where even limited information on a real estate property is displayed as individual information of the company will be exemplified.
  • FIG. 23 is a diagram showing a specific example of the display screen SDK2 displayed on the terminal device 20 in the fifth embodiment.
  • the limited information display column BL and the map information display column BM of FIG. 20 are displayed side by side on the right side when viewed from the front.
  • a number-of-property display column BC1 in which the number of real estate properties for each area is superimposed on the map is displayed.
  • the limited information property number display column BC2 is displayed.
  • the limited information property number display column BC1 the number of real estate properties for each area can be understood at a glance.
  • the limited information item number display column BC2 the number of items for each item of the limited information can be known as a breakdown, so it is easy to find the item that matches the needs.
  • Fig. 23 300 cases (thick circle part) in the area of XX in Kanagawa Prefecture are clicked.
  • the limited information property number display column BC2 in FIG. 23 not only 300 properties in the area of XX in Kanagawa prefecture, but also the number of properties for each item of limited information (land: 200, building: 30, factory: 20) is displayed. warehouse, 50 warehouses) are displayed. Among these, a property list whose matching score is equal to or higher than a predetermined value is displayed in the limited information display field BL, and map information of the property is displayed in the map information display field BM.
  • the keyword database 144 of the fifth embodiment stores not only the limited information keywords as shown in FIG. 18, but also the limited information keywords associated with each region and the number of properties as shown in FIG. .
  • FIG. 24 is a diagram showing a configuration example of a data table of limitation information according to the fifth embodiment.
  • FIG. 24 also stores the number of local properties, which is the total number of properties in the area.
  • the number of properties for the limited information keyword LK1 is LA1
  • the number of properties for the limited information keyword LK2 is LA2.
  • the number of local properties LGA1 is the total number of properties of individual limited information in the area of XX, Tokyo.
  • FIG. 25 is a flowchart showing a specific example of information analysis processing according to the fifth embodiment.
  • the processes of steps S161 to S163 are the same as the processes of steps S110 to S130, respectively, so detailed description thereof will be omitted.
  • the process of steps S161 to S163 is performed by specifying an area, thereby acquiring limited information on real estate from the management information of companies located in that area.
  • the limited information input from the terminal device 20 by the user who wants to provide the real estate property may be received and acquired.
  • step S164 the control unit 12 determines whether or not the analysis processing for the specific region has ended.
  • step S166 the control unit 12 superimposes the number of real estate properties for each region on the map, and causes the terminal device 20 to display the analysis result in step S167.
  • the output unit 130 generates display data and transmits it to the terminal device 20, so that the property number display field BC1 in which the number of real estate properties for each region is superimposed on the map as shown in FIG. Is displayed.
  • the property number display column is displayed by superimposing the number of real estate properties for each region on the map as shown in FIG. Moreover, according to the limited information property number display column BC2, the number of properties can be known for each item of the limited information as a breakdown, so it is easy to find a corporate real estate property that matches the needs.
  • FIG. 26 is a block diagram showing a specific configuration example of the information analysis device of the sixth embodiment.
  • FIG. 26 differs from FIG. 17 in that the control unit 12 is provided with a keyword determination unit 126 and a company selection unit 128 .
  • Specific keywords and weighting factors are stored in the keyword database 144 (keyword DB) of the sixth embodiment.
  • keyword database 144 keyword database
  • FIG. 11 since these configurations are the same as those in FIG. 11, detailed description thereof will be omitted.
  • the information analysis processing by the third function performed by the sixth embodiment is the same as in FIGS. 14 and 15, and the information analysis processing by the fourth function is the same as in FIGS.
  • FIG. 27 is a diagram showing a specific example of the display screen SDK3 of the sixth embodiment.
  • a company candidate display field LS, a limited information display field BL, and a map information display field BM are displayed on the display screen SDK3.
  • limited information display field BL limited information and a matching score are displayed as real estate property information of a company.
  • the map information display field BM displays the map information of the property displayed in the limited information display field BL.
  • the company candidate display field LS when viewing the display screen SDK3 from the front, the company candidate display field LS is arranged on the left side, and the limited information display field BL and the map information display field BM are arranged on the right side.
  • the limited information display field BL and the map information display field BM are displayed side by side vertically.
  • the arrangement positions of the company candidate display field LS, the limited information display field BL, and the map information display field BM are not limited to those shown in the figure, and may be arranged in any manner.
  • a candidate company list is displayed as approach information in the company candidate display field LS.
  • companies with higher scores are displayed at higher ranks.
  • companies with a higher probability of sales success can be displayed higher.
  • the company candidate display field LS displays the number of company candidates (for example, 80 found), a page switching button, and the like.
  • “date”, "company name”, "sales destination score” and the like are displayed. Display items are not limited to those shown in the figure. ”, “sales information”, and “remarks” may be added.
  • an item of search period may be provided so that the period can be entered in the item, and the companies selected by analyzing the management information within the entered period can be narrowed down and displayed.
  • the output unit 130 of the sixth embodiment highlights the specified business target company candidate in the company candidate display field LS, and also displays the individual information of the specified business target company candidate (the company's limited information of real estate property information, map information, etc.) are generated and output to be displayed side by side in the company candidate display field LS.
  • the individual information of the specified business target company candidate the company's limited information of real estate property information, map information, etc.
  • the output unit 130 of the sixth embodiment highlights the specified business target company candidate in the company candidate display field LS, and also displays the individual information of the specified business target company candidate (the company's limited information of real estate property information, map information, etc.) are generated and output to be displayed side by side in the company candidate display field LS.
  • the individual information of the specified company candidate is displayed in the company candidate display column. It is displayed side by side with LS.
  • each individual company display column LS1 (individual company display frame) in FIG.
  • the limited information of the property and the matching score are displayed in the limited information display column BL, and the map information of the property is displayed in the map information display column BM.
  • FIG. 27 is a display example when Company A at the top of each company display field LS1 is clicked, so limited information and matching scores are displayed as real estate property information of Company A in the limited information display field BL.
  • the map information of the property is displayed in the map information display column BM.
  • a seventh embodiment of the present invention will be described.
  • the first function and the fourth function are combined with the third function of displaying a list of business target company candidates by analyzing management information using specific keywords related to real estate transactions.
  • individual information real estate keywords that indicate the company's real estate utilization trends and industry trends
  • the third function of displaying a list of business target company candidates by analyzing management information using specific keywords related to real estate transactions.
  • FIG. 20 is a block diagram showing a specific configuration example of the information analysis device of the seventh embodiment.
  • the information analysis apparatus 10 of FIG. 20 differs from that of FIG. 15 in that the control unit 12 is provided with not only the limited information specifying unit 123 but also the analysis range specifying unit 122 .
  • FIG. 21 is a diagram showing a specific example of the display screen SDK4 of the seventh embodiment.
  • a company candidate display field LS, a limited information display field BL, a map information display field BM, and a first keyword display field KS1 are displayed on the display screen SDK4.
  • a candidate company list is displayed in the candidate company display field LS, and limited information and map information of real estate properties of the company are displayed in the limited information display field BL and the map information display field BM.
  • Keywords for grasping real estate utilization trends are displayed in the first keyword display field KS1.
  • external functions may be linked in addition to the first to fourth functions.
  • a banner (land pollution report) of a link to an external function is pasted on the map information display column BM. Clicking on this banner may open the site of an external service that provides land pollution reports.
  • a banner linking to external services such as information related to city planning, changes in aerial photographs, and hazard maps may be pasted. This will allow us to further expand our services.
  • first to fourth functions for displaying information obtained by analyzing management information of a plurality of companies were exemplified.
  • One or a plurality of arbitrarily selected functions can be appropriately combined and displayed on the same display screen.
  • the first function of displaying real estate keywords and the second function of displaying hot keywords can be changed to the fourth function of displaying limited information on real estate properties owned by the company. They can be combined and displayed on the same display screen.
  • real estate keywords of the company and hot keywords of the industry are displayed on the same display screen as individual information of the company as limited information of real estate properties owned by the company, and transaction trends and utilization of the real estate properties are displayed. Trends can be predicted at a glance, making it easier to set up a sales strategy for that company.

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