KR102137230B1 - Server for providing artificial intelligence based real estate auction information service using analysis of real estate title and deeds - Google Patents

Abstract

Provided is a server for providing a real estate auction information service using artificial intelligence (AI) based automatic title deed analysis, comprising: an AI-based automatic title deed analysis unit collecting and preprocessing at least one set of auction and winning bid data to construct big data, performing training and learning using the constructed big data and generating data on a query on whether to perform an auction and a query on an acquisition price when a bid is won, which is data inputted as a query; an information processing unit collecting at least one set of auction information data, arranging and listing, according to a preset classifier, any one or at least one combination among a real transaction price, a land utilizing plan, a building ledger, apartment complex information, detached multi-household information, and registration reading information which are included in the collected auction information data, and outputting the arranged and listed data; and an inspection unit transmitting the data, analyzed by the AI-based automatic title deed analysis unit, to a manager terminal, reflecting an inspection result, from the manager terminal, to data resulted from whether to perform auction and data resulted from the acquisition price when a bid is won and updating the data. The present invention can integrate various types of information and analysis results on one map platform to maximize convenience.

Description

How to provide real estate auction information service using AI-based automatic rights analysis{SERVER FOR PROVIDING ARTIFICIAL INTELLIGENCE BASED REAL ESTATE AUCTION INFORMATION SERVICE USING ANALYSIS OF REAL ESTATE TITLE AND DEEDS}

The present invention relates to a method for providing a real estate auction information service using artificial intelligence-based automatic rights analysis, and provides information for real estate auction processing and provides a platform for intuitive recognition by providing rights analysis based on artificial intelligence. do.

In the real estate auction practice, the information related to the sale acquired by various interested parties, such as mortgage lenders, lien holders, and prospective buyers, is very important for the collection of bonds and the purchase price. The problem is that there is substantial and procedural damage, such as delay in the sale process such as misrepresentation of false/exaggerated lien notification, reduction in the sale rate, difficulty in delivery and reputation, and avoidance of purchase participation due to uncertain information on the lien. . The main reason is that the right to lien is not complete and uncertain in its nature as a security right. In particular, debate over the interpretation of the lien has not been repeated under the circumstances that the related laws such as civil law and civil execution law have not been amended.

At this time, a method of analyzing and providing information for real estate auction was researched and developed. In this regard, in the prior art, Korean Patent Publication No. 2007-0033093 (published on March 26, 2007), various data on auction real estate Is stored in the database unit, the analysis module unit that searches and extracts data related to the auction real estate from the database unit to perform the analysis, the weighting unit to assign weights to the analysis results by the analysis module unit, the weights of the weighting unit The investment feasibility analysis unit that analyzes investment feasibility by adding weights according to use and region to the grant result, and the investment feasibility analysis result of the investment feasibility analysis unit and the data related to the auction property stored in the database The construction of a report generation unit that generates a final analysis result, an auction real estate analysis report, is disclosed.

However, there is a difference in the information held by each trading entity in the market, and after applying for a bid due to an error or an abnormality in auction analysis due to the information asymmetry of the uneven information structure, the bid is incorrectly confiscated. The damage caused by the information gap between economic actors has long exceeded the allowable level in bias in the distribution of information held by people, as the bid deposit amount to reach 20 billion a year. In addition, even after receiving a successful bid, the amount to be reimbursed frequently exceeds the analyzed amount due to uncertainty such as the increase in the lien or the right to take over. Therefore, in the auction process, the stakeholder's perception of the right relations such as the sale and collection of bonds or the sale price is raised with respect to the acquisition of complete information and the value of the information obtained by removing the accurate and uncertainty related to various restricted and beneficial interests. There is a need for a way to increase efficiency.

In one embodiment of the present invention, in the auction process, for the right relationship of obtaining and collecting the complete information with the correct and uncertainty regarding various restricted property rights and beneficial property rights of interested parties, and the sale or collection of bonds or the sale price, It can raise awareness and increase the efficiency of the auction process, solve the asymmetry of information, make it possible to analyze auction rights without errors with accurate information without incurring excessive auction analysis costs, and solve risk factors based on the analysis of rights using artificial intelligence. Whether it is possible to find and bid first, and secondly, the bid price is calculated in advance by calculating the amount of bidding in case of a successful bid, thereby zeroing the damages caused by the auction, and building a map-based platform to create a single map platform. It is possible to provide a method for providing a real estate auction information service using artificial intelligence-based automatic rights analysis, which can maximize convenience by allowing various information and analyzed results to be collected within. However, the technical problem to be achieved by the present embodiment is not limited to the technical problem as described above, and other technical problems may exist.

As a technical means for achieving the above-described technical problem, an embodiment of the present invention collects at least one auction successful bidding data, pre-processes it, constructs big data, and trains and learns the constructed big data to query AI auto-rights analysis unit that generates data for querying whether to enter an auction, which is the data input as (Query), and querying the amount of auction upon successful bid, collects at least one auction information data, and the real transaction price included in the collected auction information data An information processing unit that sorts and lists up one or at least one combination of land use plan, building register, apartment complex information, independent multi-family information, and registered reading information by a pre-set classifier, and AI automatic rights analysis It includes an inspection unit that transmits the analyzed data from the department to the manager terminal, and updates the results inspected from the manager terminal by reflecting the result data on whether to auction or not and the result data of the bid amount upon successful bidding.

According to any one of the above-mentioned problem solving means of the present invention, in the auction procedure, the complete and accurate acquisition of information and the value of the information obtained by removing the accurate and uncertainty regarding various restricted rights and beneficial property rights of interested parties is sold and collected or sold. Raise awareness of the right relationship of decision and increase the efficiency of the auction process, solve the asymmetry of information, enable accurate error-free auction rights analysis with accurate information without spending excessive auction analysis costs, and analyze the rights using artificial intelligence Based on the basis, it finds risk factors and whether or not it is possible to bid in the first place. Secondly, it calculates the bid amount upon successful bidding so that the bid price can be estimated in advance, thereby zeroing the damages caused by the auction. You can maximize convenience by building and collecting various information and analyzed results in one map platform.

1 is a view for explaining a real estate auction information service providing system using artificial intelligence-based automatic rights analysis according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating a real estate auction information service providing server included in the system of FIG. 1.
3 is a view for explaining an embodiment in which a real estate auction information service using artificial intelligence-based automatic rights analysis according to an embodiment of the present invention is implemented.
FIG. 4 is a diagram illustrating a process in which data is transmitted and received between each component included in the real estate auction information service providing system using the artificial intelligence-based automatic rights analysis of FIG. 1 according to an embodiment of the present invention.
5 is an operation flowchart for explaining a method for providing a real estate auction information service using AI-based automatic rights analysis according to an embodiment of the present invention.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art to which the present invention pertains may easily practice. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. In addition, in order to clearly describe the present invention in the drawings, parts irrelevant to the description are omitted, and like reference numerals are assigned to similar parts throughout the specification.

Throughout the specification, when a part is "connected" to another part, this includes not only "directly connected" but also "electrically connected" with other elements in between. . Also, when a part is said to “include” a certain component, it means that the component may further include other components, not exclude other components, unless specifically stated otherwise. However, it should be understood that the existence or addition possibilities of numbers, steps, actions, components, parts or combinations thereof are not excluded in advance.

The terms "about", "substantially", and the like used throughout the specification are used in or near the numerical values when manufacturing and material tolerances unique to the stated meanings are presented, and the understanding of the present invention. To help, accurate or absolute figures are used to prevent unconscionable abusers from unduly using the disclosed disclosure. The term "~(step)" or "step of" as used in the entire specification of the present invention does not mean "step for".

In the present specification, the term “unit” includes a unit realized by hardware, a unit realized by software, and a unit realized by using both. Further, one unit may be realized using two or more hardware, and two or more units may be realized by one hardware.

In the present specification, some of the operations or functions described as performed by the terminal, the device, or the device may be performed instead on the server connected to the corresponding terminal, device, or device. Similarly, some of the operations or functions described as being performed by the server may be performed in a terminal, apparatus, or device connected to the corresponding server.

In this specification, some of the operations or functions described as mapping or matching with the terminal means that the unique number of the terminal or identification information of the individual, which is identification data of the terminal, is mapped or matched. Can be interpreted as

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

1 is a view for explaining a real estate auction information service providing system using artificial intelligence-based automatic rights analysis according to an embodiment of the present invention. Referring to FIG. 1, a real estate auction information service providing system 1 using artificial intelligence-based automatic rights analysis includes at least one customer terminal 100, a real estate auction information service providing server 300, and at least one manager terminal ( 400), and at least one information providing server 500. However, since the real estate auction information service providing system 1 using the artificial intelligence-based automatic right analysis of FIG. 1 is only an embodiment of the present invention, the present invention is not limitedly interpreted through FIG. 1.

At this time, each component of FIG. 1 is generally connected through a network (network, 200). For example, as illustrated in FIG. 1, at least one customer terminal 100 may be connected to the real estate auction information service providing server 300 through the network 200. In addition, the real estate auction information service providing server 300 may be connected to at least one customer terminal 100, at least one manager terminal 400, and at least one information providing server 500 through the network 200. . Also, the at least one manager terminal 400 may be connected to the real estate auction information service providing server 300 through the network 200. Further, the at least one information providing server 500 may be connected to at least one customer terminal 100, the real estate auction information service providing server 300, and at least one manager terminal 400 through the network 200. .

Here, the network means a connection structure capable of exchanging information between each node such as a plurality of terminals and servers, and examples of such a network include RF, 3GPP (3rd Generation Partnership Project) network, and LTE (Long Term) Evolution (Evolution) network, 5GPP (5th Generation Partnership Project) network, WIMAX (World Interoperability for Microwave Access) network, Internet (Internet), Local Area Network (LAN), Wireless Local Area Network (LAN), Wide Area Network (WAN) , PAN (Personal Area Network), Bluetooth (Bluetooth) network, NFC network, satellite broadcasting network, analog broadcasting network, DMB (Digital Multimedia Broadcasting) network, and the like.

In the following, the term at least one is defined as a term including singular and plural, and even if the term at least one does not exist, each component may exist in singular or plural, and may mean singular or plural. It will be self-evident. In addition, it may be said that each component is provided in a singular or plural form, depending on the embodiment.

At least one customer terminal 100, the user using the artificial intelligence-based automatic rights analysis real estate auction information service related web pages, app pages, programs or applications to request real estate rights analysis information or request real estate auction information It may be a terminal. Further, the at least one customer terminal 100 may be a terminal that transmits address information for requesting information, etc. to the real estate auction information service providing server 300, receives response data, and displays the response data. In order to use the above-described service, the at least one customer terminal 100 may be a terminal that performs a payment process, but does not exclude that it is possible to proceed for free. Further, the at least one customer terminal 100 may be a terminal that receives feedback of auction analysis information from the manager terminal 400 via the real estate auction information service providing server 300.

Here, the at least one customer terminal 100 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, navigation, a laptop equipped with a web browser, a desktop, a laptop, and the like. At this time, the at least one customer terminal 100 may be implemented as a terminal capable of accessing a remote server or terminal through a network. The at least one customer terminal 100 is, for example, a wireless communication device in which portability and mobility are guaranteed, navigation, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), Personal Handyphone System (PHS), Personal Digital Assistant (PDA), International Mobile Telecommunication (IMT)-2000, Code Division Multiple Access (CDMA)-2000, W-Code Division Multiple Access (W-CDMA), Wireless Broadband Internet ) It may include all kinds of handheld-based wireless communication devices such as a terminal, a smartphone, a smartpad, and a tablet PC.

The real estate auction information service providing server 300 may be a server that provides a real estate auction information service web page, app page, program, or application using artificial intelligence-based automatic rights analysis. And, the real estate auction information service providing server 300, when receiving auction information request data such as address information from the customer terminal 100, parsing and mining it to include the address of the object, the set real estate and reimbursement amount, etc. It may be a server that extracts the identifier. In addition, the real estate auction information service providing server 300 may be a server that generates a query in order to extract similar analysis data stored and mapped to a corresponding object using the extracted identifier. Then, the real estate auction information service providing server 300 may be a server that transmits a question to the big data using the generated query and extracts similar analysis data as an answer to the query. In addition, based on the extracted similar medical advisory data, the real estate auction information service providing server 300 generates analysis data so as to correspond to the object requested by the customer terminal 100 for analysis, or generates analysis results using a preset analysis algorithm. It may be a server that is authenticated by the administrator terminal 400 and then transmitted to the customer terminal 100. To this end, the real estate auction information service providing server 300 builds big data using at least one information providing server 500 and pre-stored history log data, and classifies big data through collection, preprocessing, and analysis. And a server for learning after clustering. In addition, the real estate auction information service providing server 300 performs data learning using a deep learning artificial neural network algorithm for tagging identifiers from image data and image data in order to extract identifiers from image data or image data that is unstructured data. It can be an ongoing server. In addition, the real estate auction information service providing server 300 may be a server that tags or extracts an identifier from an image, image, etc. that is subsequently input according to the learning result.

Here, the real estate auction information service providing server 300 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, navigation, a laptop equipped with a web browser, a desktop, a laptop, and the like.

The at least one manager terminal 400 may be a terminal such as a web page, app page, analyst or consultant using a program or application related to a real estate auction information service using artificial intelligence-based automatic rights analysis. Then, the at least one manager terminal 400 receives the analysis request data received from the customer terminal 100 via the real estate auction information service providing server 300, and verifies the result of the received analysis request data The terminal may be transmitted to the real estate auction information service providing server 300. At this time, a time stamp or a Server Based Computing (SBC) may be driven in at least one administrator terminal 400 to protect personal information. That is, the user desktop environment is stored on the server for user PC work, and the documents stored on the notebook and the PC are stored on the SBC, so that the real estate auction information service providing server 300 stores internal data and files on the user PC. To prevent this, it is possible to prevent the leakage of analysis information. In addition, the information input from the at least one administrator terminal 400 may be processed to prevent forgery and alteration after a timestamp or the like.

Here, the at least one administrator terminal 400 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, navigation, a laptop equipped with a web browser, a desktop, a laptop, and the like. At this time, the at least one manager terminal 400 may be implemented as a terminal that can access a remote server or terminal through a network. The at least one manager terminal 400 is, for example, a wireless communication device in which portability and mobility are guaranteed, navigation, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), Personal Handyphone System (PHS), Personal Digital Assistant (PDA), International Mobile Telecommunication (IMT)-2000, Code Division Multiple Access (CDMA)-2000, W-Code Division Multiple Access (W-CDMA), Wireless Broadband Internet ) It may include all kinds of handheld-based wireless communication devices such as a terminal, a smartphone, a smartpad, and a tablet PC.

The at least one information providing server 500 receives information requested by the real estate auction information service providing server 300 using a web page, app page, program, or application related to real estate auction information service using AI-based automatic rights analysis. The server may be transmitted to the real estate auction information service providing server 300.

Here, the at least one information providing server 500 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, navigation, a laptop equipped with a web browser, a desktop, a laptop, and the like. At this time, the at least one information providing server 500 may be implemented as a terminal capable of accessing a remote server or terminal through a network. The at least one information providing server 500 is, for example, a wireless communication device in which portability and mobility are guaranteed, navigation, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular). , Personal Handyphone System (PHS), Personal Digital Assistant (PDA), International Mobile Telecommunication (IMT)-2000, Code Division Multiple Access (CDMA)-2000, W-Code Division Multiple Access (W-CDMA), Wireless Broadband Internet) terminal, a smart phone (smartphone), a smart pad (smartpad), a tablet PC (Tablet PC), and the like may include all kinds of handheld (Handheld)-based wireless communication device.

2 is a block diagram illustrating a real estate auction information service providing server included in the system of FIG. 1, and FIG. 3 is a real estate auction information service using artificial intelligence-based automatic rights analysis according to an embodiment of the present invention. It is a diagram for explaining one embodiment.

Referring to FIG. 2, the real estate auction information service providing server 300 includes an AI automatic rights analysis unit 310, an information processing unit 320, an inspection unit 330, a map search unit 340, and an information collection unit 350. ), and the virtualization unit 360.

Real estate auction information service providing server 300 or another server (not shown) operating in conjunction with at least one customer terminal 100, at least one manager terminal 400, and at least one according to an embodiment of the present invention When transmitting a real estate auction information service application, program, app page, web page, etc. using artificial intelligence-based automatic rights analysis to the information providing server 500 of at least one customer terminal 100, at least one manager terminal ( 400), and at least one information providing server 500, may install or open a real estate auction information service application, program, app page, web page, etc. using artificial intelligence-based automatic rights analysis. In addition, the service program may be driven in at least one customer terminal 100, at least one manager terminal 400, and at least one information providing server 500 using a script executed in a web browser. Here, a web browser is a program that enables the use of the world wide web (WWW) service, and refers to a program that receives and displays hypertext written in hypertext mark-up language (HTML), for example, Netscape. , Explorer, Chrome, and the like. Also, the application means an application on the terminal, and includes, for example, an app that is executed on a mobile terminal (smartphone).

Referring to FIG. 2, the AI automatic right analysis unit 310 collects and preprocesses at least one auction successful bidding data, constructs big data, and trains and learns the constructed big data to query. It is possible to generate data on the input data, such as a query on whether to auction or not, and on the bid amount acquisition. At this time, when the AI automatic rights analysis unit 310 derives a query, it automatically searches for reference data having a predetermined similarity based on the pre-classified identifier of the input data, and uses the derived query. Thus, reference data having a predetermined similarity may be searched, and reference data having a predetermined similarity may be extracted as a result of the search. Accordingly, it is also possible to perform analysis on an object to be auctioned by a customer by using similar analysis data.

However, depending on the nature of the rights analysis that should be changed according to the market price or policy, it is possible to perform analysis in addition to finding and applying similar data using the already constructed big data. Therefore, the AI automatic right analysis unit 310 lists time data in a time series from the initial decision start date (Approval Auction Start Day) to the successful bidding day (Bidding Day) using the correlation dimension when constructing big data. In addition, training data and experimental data sets may be trained using a Hurst index and a Chaos analysis. At this time, an auction successful bid calculation program, an automatic rights analysis program, a real estate mortgage loan program, a commercial analysis program, and a real estate geographic information (GIS) program may be further used.

In the time series data, information about the system that generated the data is hidden. Information about the system refers to the rules by which the system operates, which can be modeled as mathematical nonlinear differential equations called motion equations. Correlation Dimension, which is one of the time series analysis methods, expresses the degree of trajectory of the phase space as a dimension after realizing the phase space from the time series, and these dimensions are integer dimensions, that is, 1,2,3 It is expressed as a fraction such as 1.23, 2.34, .., etc. rather than ..dimension, so it can also be called a fractional dimension. The degree of space occupied by the phase trajectory is quantified, and the phase space is also referred to as a “state space” because the state of the system at a specific point in time is expressed as a single point in the phase space. Therefore, the change of the state of the system over time is expressed in the form of a trajectory, which is a connection of dots in the phase space, and the phase trajectory reflects all changes in the state of the system. Correlation dimension is a variable that quantifies the degree of space occupied by the locus among the geometric characteristics of the phase trajectory, and after creating an n-dimensional sphere with radius r, the number of points in the sphere is represented by C(r). , C(r) value is calculated while gradually increasing the radius r. The number of points C(r) naturally increases as the radius r increases. The important thing is the degree of increase, which is quantified by estimating the D value, assuming that C(r) is proportional to the D-squared of r. In the case of a face, when the length r increases, C(r) increases in proportion to the square of r. In this case, D=2 and 2D. In the case of volume, C(r) increases in proportion to the cube of r. In addition, the concept of chaos analysis and Hearst index is the same as that of public technology, and detailed description is omitted.

In court real estate auctions, it is important to propose an expected bid price for an object. Currently, most court real estate auction websites are composed of information that can be viewed by the court or provided by the court DB, and excludes the possibility of an object being inspected. Since the lowest bid price is proposed as the expected bid price, there is a significant difference in the dividends according to the rights of the product. To this end, in order to calculate an automatic right analysis or a successful bid price, a method through time series data analysis can be used. Time series data refers to a series of data obtained by observing a phenomenon that changes with the passage of time. You can predict how much the data will affect future results. In one embodiment of the present invention, the successful bid price of a real estate item handled by a court real estate auction can be predicted by expressing it as target time series data. Moving average (MA) and exponential smoothing (ES) methods, which are representative methods of time series analysis, can be used, and modified exponential smoothing applied with the advantages of each method can be used.

In general, court auctions are not conducted periodically, so the average bid rate of monthly successful bids for real estate items conducted by the court is expressed as time-series data, and local changes are made using a weighted moving average (MA) model. By removing it, you can easily identify long-term trends. Therefore, if there is a change in the system in which the time series is generated, it can be easily coped with, and the calculation method is easy and there is no need to store a lot of data. In addition, it is possible to calculate a predicted value after an arbitrary time difference from the current time point to time-series data defined by using a weighted moving average that gives the highest weight to recent data. The Exponential Smoothing (ES) model is a method of giving more weight to recent data and reducing the weight exponentially toward the past. Therefore, since the future is mainly predicted by using the latest data, the predicted value after a certain time point based on the current time point of the defined time series data can be calculated by a simple index smoothing formula. When the weight value is small, the smoothing effect is large, so the predicted value is insensitive to the local change in time series, whereas when the weight value is large, the effect of smoothing is small and the predicted value is sensitive to the local change in time series.

In order to automatically analyze rights, the estimated bid price is estimated through an analysis system such as the commercial district and nearby auction cases, and based on this, various legal rights related to the real estate are analyzed to automatically present the expected dividend and whether or not the successful bidder will be acquired. Can. At this time, the explanation will be based on analyzing the expected bid price of a commercial building, but excluding the analysis of real estate such as residential buildings (apartments, detached houses, multi-family, multi-family, tenement, villas, neighboring houses) and real estate, forests, and warehouses It is not. The AI automatic right analysis unit 310 can automatically input the registered items of the real estate and input the tenant details. Using the existing rights analysis program to provide rights analysis to the user and the user may be satisfied with the program, the program may be terminated, but if the user adds using the AI automatic rights analysis unit 310 according to an embodiment of the present invention If you want to carry out an analysis of commercial districts, you can additionally perform a trust-based commercial building right analysis. To this end, the input data is divided into a part that is automatically input from the existing data and a part that is modified and input by the user, and the rights analysis engine may be composed of a commercially available rights analysis engine and a commercial area analysis engine. It can be configured to pass the data value generated in the commercial area analysis engine to the rights analysis engine and perform the rights analysis based on this value. The output engine can provide various statistical values, distribution diagrams, detailed rights analysis, and other information required for auctions.

For the above-mentioned rights analysis, first, general rights analysis data is required. The location including the auction real estate number, the area of the real estate, the court's auction proceedings, lease relations, various rights relations listed on the register, and existing auction proceeding data may be required. In order to provide value-added information to the user, the land use plan of the real estate, nearby school-related information, a variety of terminology information related to auctions, and legal information to be used in legal services may also be collected. In addition, the successful bid rate applied to the analysis of rights can use the average successful bid rate within a predetermined period of each city/county/district to which the corresponding shopping mall belongs, and the unit price of the shopping mall may vary depending on the area and type per square meter when calculating the market price. If the mall is auctioned, all tenants may be considered to have made a dividend request. The right analysis engine can be started by tenant analysis. Based on the size of the tenant's deposit amount, it can be determined whether the amount of the deposit can be protected by the Commercial Rental Protection Act. Whether or not to secure a lease deposit is determined by the date on which the underlying mortgage is established. Since it is the highest priority payment to be paid before lease deposits and mortgage payments, it is possible to determine whether or not there is a deposit corresponding to such a priority payment among tenant deposits. The lease deposit of the highest priority may also be determined according to the date on which the underlying mortgage is established. Next, the sequential order of the rights relations in the tenant's deposit, such as seizures and mortgages, etc. can be listed in chronological order. Finally, it is possible to find out whether the advance registration or lien is classified as the right to be acquired by the successful bidder. The most important thing in the rights analysis engine is to judge the expected bid price. The estimated bid price used by the rights analysis engine can be used by multiplying the court appraisal value of the property and the average successful bid rate within a predetermined period. The reason for using the average successful bid rate within a predetermined period is when the amount of data is not large. This is to impart relative stability. The expected bid price can be corrected and provided in consideration of the sales of the relevant commercial district and the relevant number provided by the commercial district analysis engine. Of course, in addition to the above-mentioned rights analysis, it is possible to further analyze the bookkeeping-registered rights relationship, or to grasp the unregistered bond lease rights and use them further in the above-mentioned rights analysis.

The commercial area analysis engine can find the total amount of sales generated in the corresponding shopping mall by combining the sales of the corresponding industry and the sales generated in the corresponding number in the certain commercial area entered by the user. The profit margin can be set to calculate the average profit by applying the average profit margin of the industry, and to increase the value of the building as the sales increase and the average profit margin increases. This is because, according to the cash flow method, the higher the cash flow of profit, the higher the present value of the future cash flow. The input data of the commercial area analysis engine can be configured so that the user can conveniently view it by automatically inputting the input data using the existing input data. In addition, if the user wants to analyze the sensitivity of the output data, the user can adjust the data. The rights analysis engine can analyze the rights relationship and show the rankings of the rights relationship of the mortgage on the user screen, starting with court expenses and seizures that are the highest priority. In addition, by presenting the number of bidders, bids, competition rate, average bid rate, standard deviation and quartile, etc. that participated in the auction of nearby auctions as well as rights analysis, it can be used as a reference when actually participating in an auction.

The information processing unit 320 collects at least one auction information data, and includes any one of real transaction price, land use plan, building ledger, apartment complex information, independent multi-family information, and registered reading information included in the collected auction information data. Alternatively, at least one combination may be sorted and listed by a pre-set classifier and output. When looking at the types of rights that are usually acquired by buyers, there are chartered rights and powerful tenants as liens that are acquired by buyers regardless of whether or not they have been canceled. When the real estate is sold, the rights that were registered before the clearing right are still intact even if the ownership is transferred to the buyer, so the buyer cannot claim that he has full rights to the property unless he or she takes over these rights. It has a significant impact. Accordingly, among the factors affecting the selling price in the real estate auction process, through panel data analysis on the selling price of liens, the selling price of senior cheonsei, and the selling rate of powerful tenants, through which panel data was analyzed, which rights had the greatest influence on the total selling rate? When analyzing the magazine, it is possible to estimate the estimated price of the sale or the right to collect the above-described data, and process various information according to the request desired by the customer to provide a response corresponding to the request. .

The inspection unit 330 transmits the data analyzed by the AI automatic rights analysis unit 310 to the manager terminal 400, and transmits the results inspected from the manager terminal 400 to the auction status result data and the acquired price result data at the time of a successful bid. It can be updated to reflect on. At this time, even though the AI automatic right analysis unit 310 automatically performs a mechanical analysis, it may be required to perform an inspection before being sent to the customer because a difference may occur from the actual correction by a consultant or expert. have. Therefore, the inspection unit 330 may receive a feedback by performing an inspection from at least one administrator terminal 400, but may use a method of retraining big data again using the received feedback. At this time, among the methods of supervised learning, semi-supervised learning, unsupervised learning, and reinforcement learning, the rest of the methods except for unsupervised learning are continuously fed through big data through feedback. Because the correction is made while training and learning, the more feedback, the more accurate the result. Of course, various methods may be used in addition to the learning methods described above, and the present invention is not limited to the above-described ones.

The map search unit 340 overlays the data listed in the information processing unit by mapping it to addresses or coordinates on the map, and outputs the listed data on a map corresponding to a preset icon, but increases or decreases accumulation. In response, an icon or list-up data may be output. At this time, the information to be output may be optional information selected by the customer, or information preset by default may be represented by an icon, text, or image. Accordingly, even the general public who is difficult to analyze the auction can collect necessary information as much as an expert by gathering the information into one, and it is possible to intuitively recognize the icon symbolizing this without having to interpret the numerical value.

The information collecting unit 350 collects at least one auction item data, successful bid data, real transaction price data, development information data, real product data, and public auction data through web crawling, and includes raw data including raw data (Raw Data) is stored in parallel and distributed, unstructured data, structured data and semi-structured data contained in the stored raw data are refined, and pre-processing including classification as meta data is performed. , Pre-processed data can be analyzed including data mining. When collecting information, text data is also included, but there are some that require classification because they are not classified as pictures or metadata or are not tagged. Accordingly, data created without any format, even text, is classified as unstructured or semi-structured data, and data is processed. In the case of data described in a preset format, text is not classified as a classifier by a preset format. It can mechanically understand what is meant by, so it can be classified and recognized as a way to either not process or reuse the processed metadata.

When the virtualization unit 360 outputs data provided by the real estate auction information service providing server from at least one customer terminal connected to the real estate auction information service providing server, server-based computing or desktop virtualization Desktop Infrastructure).

Hereinafter, an operation process according to the configuration of the real estate auction information service providing server of FIG. 2 will be described in detail with reference to FIG. 3 as an example. However, the embodiment is only one of various embodiments of the present invention, it will be apparent that it is not limited thereto.

Referring to FIG. 3, (a) the real estate auction information service providing server 300 provides information such as auction information, building ledger, real transaction price, apartment complex information, land use plan, sale result, property auction, auction, and scheduled goods. Big data is constructed by collecting from at least one information providing server (500). And, (b) when the real estate auction information service providing server 300 searches for an object in the customer terminal 100, transmits the listed results based on a search word to the customer terminal 100 so as to be displayed on a map do. In addition, (c) the real estate auction information service providing server 300 collects it again after all the auctions are finished, compares it with the expected price and the result of the analysis of rights, and checks whether there is a match, and if an error or error exists, big data Is updated by comparing with the actual auction price. At this time, the real estate auction information service providing server 300 may update the predicted price or rights analysis data mechanically calculated through the inspection system.

2 and 3, a method for providing a real estate auction information service using AI-based automatic rights analysis is described in detail above with reference to a method for providing a real estate auction information service using AI-based automatic rights analysis. The following description is omitted because it can be easily inferred from the same or described contents.

FIG. 4 is a diagram illustrating a process in which data is transmitted and received between each component included in the real estate auction information service providing system using the artificial intelligence-based automatic rights analysis of FIG. 1 according to an embodiment of the present invention. Hereinafter, an example of a process in which data is transmitted and received between each of the components will be described with reference to FIG. 4, but the present application is not limited to such an embodiment, and illustrated in FIG. 4 according to various embodiments described above. It is apparent to those skilled in the art that the process of transmitting and receiving data can be changed.

Referring to FIG. 4, the real estate auction information service providing server 300 collects information from the information providing server 500 (S4100), accumulated data, and analysis algorithms collected from the information providing server 500, and the like. The process of constructing big data using data is performed (S4200).

On the other hand, the real estate auction information service providing server 300, when an analysis request arrives from the customer terminal 100 (S4600), parses the real estate data to extract the identifier (S4400), generates a query with the identifier (S4500) ), similar auction analysis data as an answer to the query is extracted (S4600), and analysis data is generated to correspond to the record of the requester (S4700).

Then, the real estate auction information service providing server 300 requests an inspection by the administrator terminal 400 (S4800), and receives feedback corresponding to the request (S4810), and if there is no error, returns to the customer terminal 100 Transmit (S4830), and when an error occurs, accumulate as data to identify the pattern in which the error occurred, and then extract the pattern using artificial neural network deep learning, so that no error occurs when a new request is received. .

Meanwhile, the real estate auction information service providing server 300 may collect data from the information providing server 500 and transmit it to the customer terminal 100 when a simple data inquiry request is received from the customer terminal 100 (S4830). (S4910), and may be overlaid to display data on the map (S4920).

The order between the above-described steps (S4100 to S4920) is only an example, and is not limited thereto. That is, the order between the above-described steps (S4100 ~ S4920) may be mutually variable, some of which may be executed or deleted simultaneously.

The method for providing a real estate auction information service using the AI-based automatic right analysis of FIG. 4 is not described above. The following description is omitted because it can be easily inferred from the same or described contents.

5 is an operation flowchart for explaining a method for providing a real estate auction information service using artificial intelligence-based automatic rights analysis according to an embodiment of the present invention. Referring to FIG. 5, the real estate auction information service providing server collects and preprocesses at least one auction successful bidding data, builds big data, trains and learns the constructed big data, and enters it as a query. Data for querying whether to auction, which is the data, and querying the acquisition amount at the time of a successful bid are generated (S5100).

The real estate auction information service providing server collects at least one auction information data, and includes any of the real transaction price, land use plan, building ledger, apartment complex information, independent multi-family information, and registered reading information included in the collected auction information data. Sort or list up one or at least one combination by a pre-set classifier and output (S5200).

The real estate auction information service providing server transmits the analyzed data of the rights to the manager terminal, and updates the result inspected from the manager terminal by reflecting the result data on whether to auction or not and the result data of the acquisition price upon successful bidding (S5300).

The method for providing a real estate auction information service using the AI-based automatic right analysis of FIG. 5 is not described above. The following description is omitted because it can be easily inferred from the same or described contents.

A method for providing a real estate auction information service using artificial intelligence-based automatic rights analysis according to an embodiment described with reference to FIG. 5 includes a recording medium including instructions executable by a computer, such as an application or program module executed by a computer. It can also be implemented in form. Computer readable media can be any available media that can be accessed by a computer, and includes both volatile and nonvolatile media, removable and non-removable media. In addition, the computer-readable medium may include any computer storage medium. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data.

The method for providing a real estate auction information service using artificial intelligence-based automatic rights analysis according to an embodiment of the present invention described above includes an application basically installed in a terminal (which includes a program included in a platform or an operating system basically installed in the terminal). It may be executed by an application (i.e., program) directly installed on the master terminal through an application providing server such as an application store server, an application, or a web server related to a corresponding service. In this sense, the method for providing real estate auction information service using artificial intelligence-based automatic rights analysis according to an embodiment of the present invention described above is implemented as an application (that is, a program) basically installed in a terminal or directly installed by a user, It may be recorded on a computer-readable recording medium such as E.

The above description of the present invention is for illustration only, and those skilled in the art to which the present invention pertains can understand that the present invention can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims rather than the above detailed description, and it should be interpreted that all changes or modified forms derived from the meaning and scope of the claims and equivalent concepts thereof are included in the scope of the present invention. do.

Claims (6)

After collecting and pre-processing at least one auction successful bidding data, build big data, and train and learn the constructed big data to query the auction status, which is the data entered as a query, and the acquisition amount query at the time of a successful bid. AI automatic rights analysis unit for generating data;
Collect at least one auction information data, and include any one or a combination of real transaction price, land use plan, building ledger, apartment complex information, independent multi-family information, and registered reading information included in the collected auction information data. An information processing unit which sorts and lists up by the set classifier and outputs it;
An inspection unit that transmits data analyzed by the AI automatic rights analysis unit to a manager terminal, and reflects and updates the results inspected from the manager terminal to the auction status result data and the bid amount result data upon successful bidding;
The information processing unit overlays the list-up data by mapping it to an address or coordinate on a map, and outputs the list-up data on the map in correspondence with a preset icon, but an icon or A map search unit outputting list-up data; And,
Data of at least one auction item, successful bid data, real transaction price data, development information data, real sale data, and short sale data are collected through web crawling, and raw data including the collected data are parallel and distributed. Store, refine unstructured data, structured data and semi-structured data included in the stored raw data, perform pre-processing including classification as meta data, and perform the pre-processed data. Includes; information collection unit for performing analysis including data mining (Data Mining),
When the AI automatic rights analysis unit derives a query, the input data is automatically searched for reference data having a predetermined similarity based on the pre-classified identifier, and the similarity is preset using the derived query. Search for reference data having a, and the search result extracts the reference data having the predetermined similarity,
The real estate auction information service providing server, when outputting data provided by the real estate auction information service providing server from at least one customer terminal connected to the real estate auction information service providing server, Server Based Computing or Desktop Virtualization unit that executes the virtualization (Virtual Desktop Infrastructure); further includes,
When building the big data, the AI automatic rights analysis unit lists time data in a time series from an initial decision start date to a successful bidding day using a correlation dimension. Hurst) A real estate auction information service providing server using artificial intelligence-based automatic rights analysis, characterized by learning training data and experimental data sets using index and chaos analysis. delete delete delete delete delete

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