KR102047669B1 - Method of electronic commerce for a range of possible examination questions - Google Patents

Abstract

Provided is an electronic commerce method for possible questions for examination. According to an embodiment of the present invention, the electronic commerce method for possible questions for examination, which a method performed by a server in an electronic commerce system including a server, an administrator terminal, a seller terminal, and a buyer terminal, may comprise the steps of: receiving item information of a textbook from the administrator terminal; storing the item information received from the administrator terminal; receiving a request for the item information on a specific textbook from the seller terminal; sending the item information about the specific textbook to the seller terminal; receiving a selection of one or more items of a plurality of items included in the item for the specific textbook from the seller terminal; receiving a purchase request for selection information from the buyer terminal; and transmitting the selection information to the buyer terminal.

Description

E-Commerce Method of Question Expected Information {METHOD OF ELECTRONIC COMMERCE FOR A RANGE OF POSSIBLE EXAMINATION QUESTIONS}

The present invention relates to an electronic commerce method of question prediction information. More specifically, the present invention relates to an electronic commerce method in which a plagiarism prevention function is added to a selected item in providing a service for selecting candidate prediction information from a textbook and selling the selected item to the examinee.

A tweezers instructor is an instructor who focuses on a large portion of the learning material that is likely to appear on the test. You can easily find tweezer instructors by subjects at university entrance schools and find tweezer instructors in various English test preparation classes such as TOEIC and TOEFL. Tweezers lectures help the test preparer as the test approaches.

Today's tweezer test information, soon to be asked information is mostly made up of a large collection of questions asked by a large school instructor, tutor or publisher. As a result, much information is shared only through instructors, institutes, or via websites provided by the institute.

Due to the confidentiality of questions, the candidates who do not know the route to obtain the information are in a relatively disadvantageous position. In addition, due to the confidentiality of information, there are many tweezer instructors throughout the country, and many instructors and tutors give special lectures before the test, but it is difficult to determine how much of the lectures were hit on the actual test.

Due to the confidentiality of the information, it is tested whether high tutoring in an area that is famous for institutes was truly efficient, or whether the information provided by the candidates who passed the exam last time was more efficient than the tutoring. It is not known even after this question is asked.

Currently, there is no digitization of exams in each country and the digitization of the tweezers lectures and the expected problem collections for all the tests, and the excessive cost of information opacity and low tweezers lectures can be a problem.

Digitization of the expected information and whether or not it is hit makes the information transparent, as well as the fair cost of the expected information. However, when instructors reveal questions expected through digitization, the expected questions are only optional information, so plagiarism can occur very easily. Therefore, it is necessary to prepare a preventive measure against plagiarism of the expected information in order to digitize the expected information and whether or not it is hit.

Korea Patent Registration No. 10-1673448 (registered on November 1, 2016)

The technical problem to be solved by the present invention is to provide an e-commerce method that allows the purchaser (investigator) to search for a seller (instructor) provided a high hit rate prediction information in the past test to purchase the high-precision question prediction information. .

Another technical problem to be solved by the present invention is to provide an e-commerce method that allows sellers (instructors) to easily create questions predicted by referring to past test questions.

Another technical problem to be solved by the present invention is to provide an electronic commerce method of question prediction information to which the plagiarism prevention function is added to prevent plagiarism caused by the digitization of the question prediction information.

The technical problems of the present invention are not limited to the above-mentioned technical problems, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description.

According to an embodiment of the present invention for solving the technical problem, the electronic commerce method of predicted information includes a server, a manager terminal, a seller terminal, and a buyer terminal, the method being performed by the server, Receiving item information of the teaching material from the manager terminal, Storing item information received from the manager terminal, Receiving a request for item information on a specific teaching material from the seller terminal Steps to the seller of the specific teaching material Transmitting item information about a; receiving a selection of one or more items among a plurality of items included in the item for the specific teaching material from the seller terminal; receiving a purchase request for the selection information from the buyer terminal; And selecting the selection to the purchaser terminal. It may comprise the step of transmitting.

Receiving the item information on the specific teaching material from the manager terminal according to an embodiment, comprising the step of receiving item information having a data structure of the table form from the manager terminal, and storing the item information May include converting the tabular data structure into a tree data structure.

According to an embodiment, the tree-type data structure may be XML (eXtensible Markup Language).

According to an embodiment, the tree-type data structure may be JavaScript Object Notation (JSON).

The converting the tabular data structure into a tree data structure may include converting data of each row of the table into a tree structure, and converting data of each row of the table into a tree structure. Converting to a structure comprises: moving a node from an n (n = 2) th column of each row of the table to a first column of each row and creating a node; Connecting the node created in the n-th column of each row as a child to the node of the previous row if the node created in the n-1th column of each row has no data in the n-2th column. And connecting the nodes of the current line as children.

The generating of the node according to an embodiment may include specifying a value of the data as a value of a generated node for a column having data and not specifying a value of a generated node for a column having no data. Can be.

The converting the tabular data structure into a tree data structure according to an embodiment may generate a single tree structure by traversing data of the transformed tree structure of each row of the table. It may include the step.

According to an embodiment of the present disclosure, an electronic commerce method of predicting information about an item includes receiving a selection of one or more items among a plurality of items included in the item from the seller terminal, and then querying a unique key for the one or more selected items. Sorting the one or more unique keys that are queried, generating a string by concatenating the one or more sorted unique keys, generating a hash value by inputting the string into a hash function, and The method may further include querying a hash value.

The querying the hash value according to an embodiment may include transmitting a guide message to the seller terminal when the hash value is found as a result of the query.

According to an embodiment, the electronic commerce method of predicting questions may include storing the one or more selected items after querying the hash value, and if the hash value is not found as a result of the query.

According to an embodiment of the present disclosure, an electronic commerce method of predicting information about an item includes initially selecting randomly one or more indexes of all items of a specific textbook from the administrator terminal and storing unique keys corresponding to the corresponding indexes; Receiving a selection of at least one item from among a plurality of items included in the item from the terminal, and if the manager's unique keys exist in the seller's selection item, storing the unique key as a plagiarism search key; and Querying a unique key for one or more selected items.

According to an embodiment of the present invention, an electronic commerce method of predicted question information includes comparing a unique key for the one or more selected items and the one or more plagiarism search keys, and informing the seller terminal if there are more than a predetermined number of matching keys. It may include the step of transmitting.

According to an embodiment of the present invention, an electronic commerce method of predicting question information compares a unique key for the one or more selected items and the one or more plagiarism search keys, and if there are less than a predetermined number of matching keys, select the one or more selected items. And storing.

According to another embodiment of the present invention, a server includes an server, an administrator terminal, a seller terminal, and a purchaser terminal. The server may include one or more processors, a memory for loading a computer program executed by the processor, and Including a storage for storing a computer program, the computer program, instructions for receiving item information of the teaching material from the manager terminal, instructions for storing the item information received from the manager terminal, items for a specific teaching material from the seller terminal An instruction for receiving a request for information, an instruction for transmitting item information on the specific teaching material to the seller terminal, and a selection for one or more items among a plurality of items included in the item for the specific teaching material from the seller terminal doing The truck's design, may contain instructions to the buyer and the terminal receiving the purchase request for the selected information from the buyer terminal instructions to transmit the selected information.

According to an embodiment of the present invention, the purchaser (examiner) can easily find and confirm the latest questionnaire prediction information of the seller (instructor) by searching for a seller (instructor) that provided a high hit rate prediction information in the past test. .

According to another embodiment of the present invention, the seller (instructor) is the same or similar to the specific items in the textbooks or how many times the area of the question was asked in the past test, the test of other species, the same test in other countries You can easily search for information on a question of the area or type of question, so you can refer to it when creating the expected information.

According to another embodiment of the present invention, this time, the prediction information provided by the seller (instructor) recorded a high hit rate in the past can be prevented from being completely plagiarized by other sellers (instructor). Specifically, plagiarism can be prevented by setting an item group not to be opened before a specific date, or by denying registration of plagiarism-probable information by comparing data in a database with each other.

The effects of the present invention are not limited to the above-mentioned effects, and other effects not mentioned may be exerted in the technical field of the present invention.

1 is a block diagram of an electronic commerce system of anticipated information with a plagiarism prevention function according to an embodiment of the present invention.
2 is a block diagram of an electronic commerce system of the anticipated information with the plagiarism prevention function according to another embodiment of the present invention.
3 is a block diagram illustrating a configuration of a seller terminal in an electronic commerce system of question prediction information according to an embodiment of the present invention.
4 is a block diagram illustrating a configuration of a purchaser terminal in an electronic commerce system of question prediction information according to an embodiment of the present invention.
5 is a block diagram illustrating a configuration of an intermediary server in an electronic commerce system of question prediction information according to an embodiment of the present invention.
6 is a block diagram illustrating a configuration of a test information management server in an electronic commerce system of question prediction information according to an embodiment of the present invention.
FIG. 7 is a diagram illustrating a screen in which an administrator inputs a detailed category of each subject to an electronic commerce intermediary of an intermediary server using an administrator terminal in an electronic commerce system of question prediction information according to an embodiment of the present invention.
FIG. 8 is a diagram illustrating a screen in which an administrator inputs an item of a textbook to an electronic commerce mediation unit of an intermediary server in an electronic commerce system of question prediction information according to an embodiment of the present invention.
FIG. 9 is a diagram illustrating an example of a water code of an algorithm for converting a table type question prediction information input by an administrator into a tree form in an electronic commerce system of question prediction information according to an embodiment of the present invention.
FIG. 10 is a diagram illustrating data in which question prediction information is converted into a tree form in an electronic commerce system of question prediction information according to an embodiment of the present invention.
11 is a flowchart illustrating an electronic commerce method performed in an electronic commerce system of question prediction information according to an embodiment of the present invention.
12 is a flowchart illustrating a configuration of a server in an electronic commerce system including a server, a manager terminal, a seller terminal, and a buyer terminal 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. Advantages and features of the present invention and methods for achieving them will be apparent with reference to the embodiments described below in detail with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various forms, and only the embodiments are intended to complete the disclosure of the present invention, and the general knowledge in the art to which the present invention pertains. It is provided to fully inform the person having the scope of the invention, which is defined only by the scope of the claims. Like reference numerals refer to like elements throughout.

Unless otherwise defined, all terms used in the present specification (including technical and scientific terms) may be used in a sense that can be commonly understood by those skilled in the art. In addition, the terms defined in the commonly used dictionaries are not ideally or excessively interpreted unless they are specifically defined clearly. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. In this specification, the singular forms also include the plural unless specifically stated otherwise in the phrases.

The expression 'comprises' or 'comprising' as used herein does not exclude the presence or addition of any other configuration / step / operation other than the configuration / step / operation mentioned.

A tweezers instructor is an instructor who focuses on a large portion of the learning material that is likely to appear on the test. You can easily find tweezer instructors by subjects at university entrance schools and find tweezer instructors in various English test preparation classes such as TOEIC and TOEFL. Tweezers lectures help the test preparer as the test approaches.

Today's tweezers test information is mostly made up of large-scale school instructors, tutors, or publishers expected questions.

The textbook may be a textbook associated with a particular test. For example, EBS-linked textbooks for university mathematics tests are linked to the university mathematics examinations by a percentage of the Ministry of Education policy.

The textbook linked to the University Scholastic Ability Test is issued by EBS under the guidelines of curbing private education and normalizing public education. 70% of the textbook is linked to the actual test. The link between the College Scholastic Ability Test and EBS was introduced in the 2005 SAT. The government announced in February 2004 "Reduction Measures for Private Education Expenses" and announced that it would link EBS Internet lectures starting in April of that year with the SAT. At the time, the Ministry of Education estimated that private education costs could be reduced by around KRW 500 billion annually. Since the 2011 CSAT, the linkage rate has been fixed at 70%, and the linkage rate has been maintained at 70-80%.

All of the EBS textbooks linked to the College Scholastic Ability Test are supervised by the Korea Institute of Curriculum and Evaluation. It is preferable as a textbook for carrying out the e-commerce method of the question prediction information. Therefore, hereinafter, the EBS method for linking the college mathematics test with reference to the e-commerce method for predicting the expected information according to an embodiment of the present invention will be described.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

1 is a block diagram of an electronic commerce system of anticipated information with a plagiarism prevention function according to an embodiment of the present invention.

As shown in FIG. 1, the electronic commerce system according to an exemplary embodiment of the present invention includes a seller terminal 110, a buyer terminal 120, an intermediary server 210, a test information management server 220, and a manager terminal 300. It may include.

The seller terminal 110 is a terminal used by a seller, for example, an instructor or a tutor, to input question prediction information. The seller terminal 110 selects an item to be predicted from the item information of the textbook input to the mediation server 210. You can enter the expected information. Seller terminal 110 preferably has a wired and wireless communication function for connecting to the mediation server 210 online to input questions expected information, a variety of devices, such as PC, smartphone, tablet, etc. Seller terminal 110 It can be utilized as.

The purchaser terminal 120 is a terminal used by the buyer to access the mediation server 210 to purchase the expected prediction information selected by the seller, and a payment program for electronic commerce may be installed. The purchaser terminal 120 preferably has a wired / wireless communication function for accessing the intermediary server 210 to purchase online and purchase expected information, and a variety of devices such as a PC, a smart phone, a tablet, etc. 120).

The mediation server 210 stores item information, etc. of the teaching material that is the basis of the expected item information, and receives the expected item information from the seller terminal 110, and sells the expected item information to the buyer terminal 120 to sell. Has the ability to

The test information management server 220 stores information on past actual questions, and the mediation server 210 compares the actual test information stored in the test information management server 220 with the expected questions of sellers. In this case, the hit ratio of the questions for each seller can be calculated.

The manager terminal 300 is a terminal used by the administrator to input the item information of the teaching material, which is the basis of the expected question information, to the mediation server 210, and various devices such as a PC, a smart phone, and a tablet are the manager terminal 300. It can be utilized as. The type of the manager terminal 300 is not limited to a PC, a smartphone, a tablet, or the like, and is a computing device having a function of inputting data such as item information of a textbook, which is a basis of expected information by connecting to the mediation server 210. If all may be the manager terminal (300).

The manager may input data in a manner of directly accessing the mediation server 210 or the test information management server 220 using the manager terminal 300. For example, the manager may directly access the intermediary server 210 using the manager terminal 300, and then input the item information of the teaching material, which is the basis of the expected question information, to the intermediary server 210 to be stored. In addition, the manager may directly access the test information management server 220 by using the manager terminal 300, and input information stored in the actual test to the test information management server 220 to be stored.

Although FIG. 1 illustrates that the mediation server 210 and the test information management server 220 run on different server computers, the mediation server 210 and the test information management server 220 run on a single server computer. It is also possible. That is, instead of dividing the server into an intermediate server 210 and a test information management server 220, a single server having both a mediation function of expected question information and a management function for a question that is actually asked is operated in such a manner as to operate a single server. In addition, it is also possible to provide an e-commerce service of the expected item information according to an embodiment of the present invention.

2 is a block diagram of an electronic commerce system of the anticipated information with the plagiarism prevention function according to another embodiment of the present invention.

2 illustrates that the manager terminal 300 accesses the mediation server 210 and the test information management server 220 through the Internet network.

The mediation server 210 and the test information management server 220 may be built using a cloud platform (a virtual server hosting platform) such as Amazon Web Services (AWS) or Microsoft Azure. That is, the mediation server 210 and the test information management server 220 may be built in the form of a physical server or in the form of a virtual server on a cloud platform.

When the intermediary server 210 and the test information management server 220 are built in the form of a virtual server, the administrator accesses the virtual server hosting platform using the manager terminal 300.

You can then install the server on a virtual server hosting platform, modify the installed server, stop the installed server, restart the installed server, and so on.

You can connect to the virtual server hosting platform directly using telnet, SSH, or through the Internet using the AWS console. That is, the administrator may access the intermediary server 210 and the test information management server 220 installed in the virtual server hosting platform through the network using the manager terminal 300 to control and modify the server.

Although FIG. 2 illustrates that the mediation server 210 and the test information management server 220 run on different virtual server hosting platform instances, the mediation server 210 and the test information management server 220 may be executed in a single instance. It is also possible to drive with different ports.

In addition, the server is not divided into a mediation server 210 and a test information management server 220, and a single server having a mediation function of expected information and a management function for a question that is actually asked is formed by a single server. It is also possible to provide an e-commerce service of the expected information of the question according to an embodiment of the present invention in a manner to be executed in an instance.

3 is a block diagram illustrating a configuration of a seller terminal 110 in an electronic commerce system of questions expected information according to an embodiment of the present invention.

As shown in FIG. 3, the seller terminal 110 of the e-commerce system of the question prediction information according to an embodiment of the present invention includes a test question prediction information editing unit 111, a past question trend search unit 112, and a past question trend The display unit 113 may be included.

The test question prediction information editing unit 111 may perform a function of inputting question prediction information by checking a seller item information of a textbook input to the mediation server 210 and then selecting a question item expected from the item information. have. In addition, the test questionnaire prediction information editing unit 111 may add additional text, images, audio, video, and the like related to the questionnaire prediction information when selecting and generating the questionnaire prediction information.

The seller may set the publication date on the expected question information using the seller terminal 110. The reason for setting the release date is that if the expected information is released in advance before the test date, it is highly likely that a third party will copy the expected information. That is, in order to prevent plagiarism, the seller may access the mediation server 210 by using the seller terminal 110 and input the question prediction information, and then set the publication date for each question prediction information. If the publication date is determined, corresponding prediction information is not displayed on the other seller terminal 110 or the purchaser terminal 120 before the publication date.

Question prediction information may be grouped and managed. For example, the first question expected information, the second question predicted information, the third question predicted information, the fourth question predicted information, the fifth question predicted information, the sixth question predicted information, the seventh question predicted information, and the eighth question predicted information The first question prediction information, the second question prediction information and the third question prediction information are grouped in the first group, the fourth question prediction information and the fifth question prediction information are grouped in the second group, and the sixth The question prediction information, the seventh question prediction information, and the eighth question prediction information may be grouped into a third group. In this case, the seller can set the release date for each group.

By grouping the expected questions in a group, buyers (investees) can understand the questions because the expected questions are categorized, and can set a date for each group to help prevent plagiarism.

The past question trend search unit 112 may perform a function of displaying a past question trend through the past question trend display unit 113 after the seller receives a past question trend from the mediation server 210. The seller may check past questions by using the past question trend search unit 112 to select items that were frequently asked in the past as question prediction information, or exclude items that were asked in the last round from the question prediction information. You can get help with the selection of information.

Using the past question trend search unit 112, when the seller selects the item of the textbook, it is easy to know how often the item was asked in the past test, or the question in the same subject of another test.

For example, the item currently selected by the seller using the seller terminal 110 is' Physical 1 → 02 Kang. Law of motion and mechanical energy (1) → 1 →? [2] →? If it is a 3 'item, the seller would like to search how many times and how many times the item has been asked in the past test.

In this case, the seller may search for the corresponding item through the past question trend search unit 112. When a search for the corresponding item is requested through the past question trend search unit 112, a unique key of the database of the test information management server 220 is searched to receive a past question trend about the item.

The past questions tendency display unit 113 shows the information received from the test information management server 220 graphed on the screen, or summarizes on the screen so as to check how many times the question is found. That is, the past question trend display unit 113, when the past question trend search unit 112 searches and receives the result, the graph of the time series of the test questions that have been questioned in the past, the test name, the name of the subject, the problem number, the history The cumulative number of questions on the exam and the number of questions on the exam are displayed to the seller.

Each component of the seller terminal 110 illustrated in FIG. 3 may refer to software or hardware such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC). However, the components are not limited to software or hardware, and may be configured to be in an addressable storage medium, or may be configured to execute one or more processors. The functions provided in the above components may be implemented by more detailed components, or may be implemented as one component that performs a specific function by combining a plurality of components. In addition, each component of the seller terminal 110 illustrated in FIG. 3 may mean each functional module constituting one software.

4 is a block diagram illustrating a configuration of a purchaser terminal 120 in an electronic commerce system of question prediction information according to an embodiment of the present invention.

As shown in FIG. 4, the purchaser terminal 120 of the electronic commerce system of the question prediction information according to an embodiment of the present invention includes a test question prediction information search unit 121 and a test question prediction information display unit 122. can do.

The test questions prediction information search unit 121 may perform a function of displaying the question prediction information through the test question prediction information display unit 122 after the purchaser searches for and receives the question prediction information from the mediation server 210. . The purchaser may search for a lot of questions expected by the seller using the test questions prediction information search unit 121, and then select one or more of them to purchase.

Each component of the purchaser terminal 120 illustrated in FIG. 4 may refer to software or hardware such as an FPGA or an ASIC. In addition, each component of the purchaser terminal 120 illustrated in FIG. 4 may mean each functional module constituting one software.

5 is a block diagram illustrating a configuration of an intermediary server 210 in an electronic commerce system of question prediction information according to an embodiment of the present invention.

As shown in FIG. 5, the mediation server 210 of the electronic commerce system of the predicted question information according to an embodiment of the present invention includes an e-commerce mediation unit 211, a hit result report unit 212, and a seller hit report unit. 213 may include.

The e-commerce broker 211 may store a question prediction information received from the seller terminal 110 and transmit the stored question prediction information to the purchaser terminal 120.

In addition, the electronic commerce broker 211 may prevent plagiarism of the question prediction information by preventing a third party other than the seller who directly inputs the question prediction information having the publication date set.

In addition, the e-commerce broker 211 sets a prohibition period for a certain period of time before the test is started, so that during the prohibition period, sellers can no longer modify the question prediction information, thereby preventing plagiarism of the question prediction information. have.

The hit result report unit 212 may perform a function of transmitting to the seller terminal 110 what problem was hit in the question prediction information input by a specific seller. The seller may check the hit result through the seller terminal 110. The hit result may be determined by comparing actual test item data obtained from the test information management server 220 with expected item information of the seller.

The seller hit reporter 213 shows the hits of the sellers' prediction information to the buyers, so that the buyers can refer to the purchase of the predictions of the future questions. The buyer may check the hit information received from the seller hit reporter 213 through the purchaser terminal 120. For example, the A's hit accuracy is 50% for the 'English' subject of the 'University Ability Test' of seller 'A'. If 30%, the buyer can buy with confidence the seller's prediction information of the high hit A.

The seller hit reporter 213 may report the hit of the seller against the test, the hit against the subject, the hits of each test series, the hit rank, the maximum hits, the number of hits, and the like from the previous test.

FIG. 6 is a block diagram illustrating a configuration of a test information management server 220 in an electronic commerce system of question prediction information according to an embodiment of the present invention.

As shown in FIG. 6, the test information management database 221 may be included, and the test information management database 221 may store information about a question actually presented in a test. The past questioning trend search unit 112 of the seller terminal 110 may show the past questioning trend to the seller using data obtained from the test information management database 221.

The test information management database 221 stores information such as a test name, a trial date, a subject name, and a question number of past past tests. At this time, each question on the test can be classified into each category, and the categories are managed by unique keys. For example, in the case of physics, categories such as the problem related to 'free fall motion', the problem related to 'movement of a vertically thrown object', and the problem related to 'movement of a vertically thrown object' are set. A unique key may be stored for each problem.

When the seller inputs the corresponding category when searching the past questioning trend using the seller terminal 110, the test name, test date, and subject name of the search result according to the unique key according to the category from the test information management database 221. You can retrieve the problem number and retrieve it. The search result according to the unique key according to the corresponding category can be shown in a graph by time zone based on the test date.

7 is a screen for inputting a detailed category of each subject to an e-commerce intermediary of an intermediary server 210 by using an administrator terminal 300 in an e-commerce system of question prediction information according to an embodiment of the present invention. The illustrated figure.

As shown in FIG. 7, the manager may designate and input a detailed category of each subject on the mediation server 210 using the manager terminal 300. Each category may be uniquely assigned, in which case a unique key may be specified for each category. Unique keys for each category are referred to herein as "unique B keys".

7 illustrates setting categories for each item in a physics subject. As illustrated in FIG. 7, 'free fall motion', 'movement of the object thrown vertically', 'movement of the object thrown vertically', 'movement of the object thrown horizontally' and 'movement of the object thrown obliquely' When each category of 'is specified, a unique B key for each category may be specified.

The category may be set and input for each subject. To enter a category, first, a list of all the knowledge items that can be taken in the test, such as mathematics, mathematics, and physics, is created. When you make this list, you make a list by categorizing each area of the subject so that it can no longer be broken down. Since you need to search for the item later, assign a unique B-key to each category.

FIG. 8 illustrates a screen in which an administrator inputs an item of a textbook to an e-commerce intermediation unit of an intermediary server 210 by using an administrator terminal 300 in an e-commerce system of question prediction information according to an embodiment of the present invention. Drawing.

As shown in FIG. 8, the manager may designate and input an item of a specific textbook to the mediation server 210 using the manager terminal 300. A unique key may be specified for each item, and a unique key for each item in the textbook is referred to herein as a “unique A key”.

Administrators list the candidates' favorite textbooks and list them with numbers or titles that refer to all parts of the book, such as the table of contents, problem number, and item number. Also enter the page position and line position information.

For example, when inputting an item of a textbook, the information to be input may include at least one or more of the title, chapter number, chapter name, item number, item name, problem number, problem name, problem number, page number, and line number of the textbook. have. When sellers create questions, they can choose one or more of these items.

8 is a diagram exemplifying contents that can be input in an item input unit of a textbook. The column labeled Key is a unique A key that refers to a specific item of the textbook. That is, the unique A key is the only key that refers only to that item.

As such, the data created by using the table of contents list table for each item of the textbook is converted into a JSON / XML data tree structure in the mediation server 210.

The reason for converting data input in table form into JSON / XML form is to facilitate data processing. The reason why it is difficult to input in JSON / XML format from the administrator's input stage is that if you want to input each item list in JSON / XML format from the beginning, the tree becomes very large. This is because there is a lot of trouble, such as writing, and because of this trouble, a small chapter or an item may be missed and entered.

Therefore, the best editor for inputting the item data of the textbook is in the form of a table (like Excel), and the mediation server 210 needs to convert the data input in the form of a table into a tree structure (JSON / XML). .

An algorithm for converting data input in a table form into a tree structure (JSON / XML) will be described with reference to FIG. 9.

The tree structure may be generated in order from the leaf node existing at the end to the root node.

Data for each node included in the tree structure generated in the above order may include information about child nodes of each node. Therefore, in order for a specific node to be created, a child node of each specific node must be created.

Using the algorithm to convert the table type into a tree type data structure, the first item at the left end is moved to the left by one cell starting from the cell in the last column located at the far right of each row of the table where the expected information is stored. Up to cells can be converted into tree structures.

A detailed description of the pseudo code of the algorithm shown in FIG. 9 is as follows.

First, if data exists in a cell to be processed currently and a node corresponding to the current cell has never been created, a new node is created and the data is stored in the generated node.

If data exists in a cell to be processed and a node corresponding to the current cell has been created, the data of the current cell is stored in a previously generated node.

In addition, if there is a node corresponding to the cell located in the right column generated previously, the node is connected as a child node of the current node.

If no data exists in all the cells in the left column, find the parent node one level higher than the node level of the current cell among the nodes created in the previous rows, and move the node of the current cell one level higher than the node level of the current cell. Connect to the child of the parent node.

If none of the cells exist in the previous rows, a new parent node is created to connect the node of the current cell to the child node of the generated parent node.

Repeating the above steps for all the cells in each row completes the conversion of the table's specific row into the tree structure.

However, according to some embodiments of the present disclosure, the method for converting the table-type information received from the user into a tree form is not limited thereto, and various types of algorithms that can be easily modified by those skilled in the art may be used. .

For example, if the current cell is category 5, if there is text / image in the current cell (category 5) and no node has been created, then a node of that level is created. If there is an empty node (no text / image) already created in the right cell (category 6) of the current cell (category 5), the text / image is stored in the node without creating a new node.

If there is text or an image in the right cell (category 6) of the current cell (category 5), you would have already created a node for category 6 when you processed the data in category 6, so that node (category 6) Add as child node.

Next, if category 4 level has never created a node in the previous row, create a category 4 empty node. Then on the left, note that we created a new, empty node in category 4. And if category 4's node is an empty node, add a category 5 node as the child of category 4 you created in the previous rows.

In this way, we handle categories 6 through 2 on the far right.

Each row is processed using the above method.

Finally, you can generate JSON or XML data by traversing the nodes of the generated tree structure for every row.

FIG. 10 is an example of data obtained by converting the data of FIG. 8 into a JSON format.

JSON is a type of data storage format that consists of data objects consisting of 'property: value' or 'key: value'. Therefore, the value of the '_caption' attribute of the node that stores the information about the mathematics hypothetical subject may be 'mathematics'.

For example, a node that stores information that includes information about the fourth line on page 5 as a reference, a node that stores information about 'mathematical pseudo-type' subjects, a node that stores information about 'calculus', and an 'exponential function and log' 'The meaning of the function and the graph' information can be created to have a node that stores the parent node. However, this is only an example of representing a tree-type data structure as JSON-type data, and a method of expressing a tree form of input data according to some embodiments of the present invention is not limited thereto.

Meanwhile, as a method for preventing plagiarism by searching for highly predicted question prediction information, the mediation server 210 largely compares (1) the hash value of the sorted list, and (2) the specific index of the textbook items list. There is a method to compare with the unique A key value.

A method of comparing a hash value of a sorted list, comprising sorting unique A keys for selecting items of a book from item prediction information of each seller, connecting all data to generate a string, and then hashing the string. Get the value.

If there is more than one seller who has the same hash value by comparing the hash value of the question prediction information of each seller, judge the question prediction information of the sellers other than the seller who registered the question prediction information first among sellers as plagiarism. .

Next, as a method of comparing the unique A value of a specific index, the administrator inputs a textbook item, and then randomly selects n special indexes for the book items of the test before allowing the seller to enter the expected information. do.

When the administrator allows the entry of questions for the specific test, the index is randomly generated, and then unique A keys corresponding to the index are stored in the database of the mediation server 210. When the seller enters the question prediction information, if there are unique A values selected by the administrator from the list of items included in the question prediction information entered by the seller, the corresponding unique A keys are plagiarism search key 1, plagiarism search key 2, and plagiarism search key. 3 ... Save to plagiarism search key n.

In the case of comparing the hash values of the sorted list, even if one of the items is different, the result is not plagiarism. For example, 99 out of 100 choices are plagiarism, and one is not plagiarism.

However, in the case of comparing a predetermined random number n unique A keys, plagiarism may be detected by a maximum of n plagiarism checks.

This improves security against plagiarism detection by using random fractional sample groups unknown to the seller, and speeds up plagiarism detection operations by using optional computing resources for fractional sample groups.

11 is a flowchart illustrating an electronic commerce method performed in an electronic commerce system of question prediction information according to an embodiment of the present invention.

As shown in FIG. 11, in the electronic commerce method performed in an electronic commerce system of question prediction information according to an embodiment of the present invention, step S910 of receiving an item information of a teaching material from the manager terminal 300 and a manager terminal ( Storing item information received from 300 (S920), receiving a request for item information on a specific textbook from the seller terminal 110 (S930), item information on a specific textbook to the seller terminal 110 Transmitting (S940), receiving a selection for one or more items from among a plurality of items included in the item for a specific teaching material from the seller terminal (110) (S950), for the selection information from the buyer terminal (120) Receiving a purchase request (S960) and transmitting the selection information to the purchaser terminal 120 (S970).

Receiving item information on a specific teaching material from the manager terminal 300 may include receiving item information having a data structure in a table form from the manager terminal 300, and storing the item information. The method may include converting a tabular data structure into a tree data structure.

In this case, the tree-type data structure as a result of the transformation may be an XML (eXtensible Markup Language) structure.

Alternatively, the tree-type data structure as a result of the conversion may be a JavaScript Object Notation (JSON) structure.

Specifically, converting the tabular data structure into a tree data structure includes converting data of each row of the table into a tree structure, and converting data of each row of the table into a tree structure. Creates a node by moving from the n (n = 2) th column of each row of the table to the first column of each row and the n-1 th of each row If the node created in the column concatenates the node created in the nth column of each row as a child, and there is no node to create in column n-2, the node created in the rows above it concatenates the node of the current row as the child. It may include.

Generating the node may include specifying a value of data as a value of a generated node for a column having data and not specifying a value of a generated node for a column having no data.

In addition, converting the tabular data structure to a tree data structure may include traversing the data of the transformed tree structure of each row of the table, thereby generating a single tree structure. Can be.

In order to prevent plagiarism, receiving a selection of one or more items from among a plurality of items included in the item from the seller terminal 110, and then querying a unique key for the one or more selected items, and querying one or more unique items. The method may further include sorting a key, generating a string by connecting one or more sorted unique keys, generating a hash value by inputting the string into a hash function, and querying the hash value.

After querying the hash value, if the hash value is found as a result of the query, transmitting a guide message indicating that registration is rejected for plagiarism to the seller terminal 110 may be included. On the other hand, after querying the hash value, if the hash value is not found, the selected item may be stored.

Receiving a selection of one or more items among a plurality of items included in the item from the seller terminal 110, and then querying the unique A keys selected by the administrator for a plurality of items of a specific textbook to find them in the seller's selection. Storing the unique keys as plagiarism retrieval keys, if any, and querying the unique keys for one or more selected items.

If comparing the unique key and at least one plagiarism search key for one or more selected items, if there are more than a predetermined number of matching keys, transmitting a guide message to the seller terminal 110 that registration is rejected for plagiarism May be included. On the other hand, by comparing the unique key and the at least one plagiarism search key for one or more selected items, if there are less than a predetermined number of matching keys, one or more selected items may be stored.

12 is a flowchart illustrating a configuration of a server in an e-commerce system including a server, a manager terminal 300, a seller terminal 110, and a purchaser terminal 120 according to an embodiment of the present invention.

According to an embodiment of the present invention, a server includes one or more processors 1010, a memory 1020 for loading a computer program executed by the processor 1010, a storage 1030 in which one or more computer programs are stored temporarily, and It may include a network interface 1040.

The processor 1010 controls the overall operation of each component of the server that can implement the method according to embodiments of the present invention. The processor 1010 may include a central processing unit (CPU), a micro processor unit (MPU), a micro controller unit (MCU), a graphics processing unit (GPU), or any type of processor 1010 well known in the art. It can be configured to include. In addition, the processor 1010 may perform operations on at least one application or program for executing a method according to embodiments of the present invention. A server for executing a method according to embodiments of the present invention may include one or more processors 1010.

The memory 1020 stores various data, commands, and / or information. Memory 1020 may load one or more computer programs from storage 1030 to execute a method in accordance with embodiments of the present invention.

Storage 1030 may store one or more computer programs non-transitory. The storage 1030 may be a non-volatile memory such as a read only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, a hard disk, a removable disk, or the like. It may comprise any known type of computer readable recording medium. The storage 1030 stores a computer program for performing a method according to embodiments of the present invention.

The network interface 1040 supports a wired or wireless communication function. The network interface 1040 may support various communication schemes. To this end, the network interface 1040 may be configured to include a communication module well known in the art.

Computer program for performing the method according to embodiments of the present invention, instructions for receiving the item information of the teaching material from the manager terminal 300, instructions for storing the item information received from the manager terminal 300, seller terminal ( An instruction for receiving a request for item information on a specific textbook from 110; an instruction for transmitting item information for a specific textbook to seller terminal 110; a plurality of items included in an item for a specific textbook from seller terminal 110; Instructions for receiving a selection for one or more of the items, instructions for receiving a purchase request for the selection information from the buyer terminal 120 and instructions for transmitting the selection information to the buyer terminal 120.

On the other hand, each flowchart of the present specification is described as sequentially executing each step, which is merely illustrative of the technical idea of the present invention, the execution of each step of each flowchart of the present specification in a time-series order It is not limited.

Persons of ordinary skill in the art to which the present invention pertains may change the order of one or more steps, omit one or more steps, or one or more steps in each step of the flowchart herein without departing from the essential characteristics of the present invention. Various steps may be variously modified and modified, such as executing steps in parallel.

The methods according to the embodiments of the present invention described so far may be performed by execution of a computer program implemented in computer readable code. The computer program may be transmitted from the first computing device to the second computing device via a network such as the Internet and installed in the second computing device, thereby being used in the second computing device. The first computing device and the second computing device both include a server device, a physical server belonging to a server pool for cloud services, and a stationary computing device such as a desktop PC.

The computer program may include a magnetic storage medium (for example, a ROM, a floppy disk, a hard disk, etc.), an optical reading medium (for example, a CD-ROM, a DVD, etc.), a flash memory (for example, a USB, an SSD), and the like. It may be stored in the same non-transitory medium.

Although the embodiments of the present invention have been described above with reference to the accompanying drawings, those skilled in the art to which the present invention pertains may be embodied in other specific forms without changing the technical spirit or essential features of the present invention. I can understand. Therefore, it is to be understood that the embodiments described above are exemplary in all respects and not restrictive.

Claims (14)

In an electronic commerce system including a server, a manager terminal, a seller terminal and a buyer terminal, a method performed by the server,
Receiving item information of a textbook from the manager terminal;
Storing the item information received from the manager terminal;
Receiving a request for item information on a specific textbook from the seller terminal;
Transmitting the item information on the specific teaching material to the seller terminal;
Receiving a selection of one or more items among a plurality of items included in the items for the specific teaching material from the seller terminal;
Receiving a purchase request for the selection information from the buyer terminal; And
Including the step of transmitting the selection information to the buyer terminal,
Receiving a selection for one or more items of a plurality of items included in the item from the seller terminal,
Randomly selecting two or more special indexes among indices for all items of the specific textbook before inputting the question prediction information by the seller terminal;
Receiving selection of one or more items from among a plurality of items included in the item from the seller terminal of the first seller after inputting the question prediction information by the seller terminal;
Storing each unique key as a plagiarism search key of a first seller if a unique key corresponding to the special index exists in a seller's selection item;
After inputting the question prediction information by the seller terminal and after receiving the selection of the first seller, selecting one or more items among the plurality of items included in the item from the seller terminal of the second seller. Receiving; And
When a plagiarism search key of a second seller, which is a unique key corresponding to the special index present in the selection item of the second seller, and a plagiarism search key of the first seller are compared, and there are more than a predetermined number of matching keys. , Transmitting a plagiarism guide message to a seller terminal of the second seller.
E-commerce method. The method of claim 1,
Receiving the item information on the specific teaching material from the manager terminal, the step of receiving the item information having a data structure of the table format from the manager terminal,
The storing of the item information includes converting the tabular data structure into a tree data structure.
E-commerce method. The method of claim 2,
The tree-type data structure is XML (eXtensible Markup Language),
E-commerce method. The method of claim 2,
The tree data structure is JSON (JavaScript Object Notation),
E-commerce method. The method of claim 2,
Converting the tabular data structure into a tree data structure,
Converting data of each row of the table into a tree structure,
Converting the data of each row of the table into a tree structure,
Creating a node by moving from an n (n = 2) th column of each row of the table to a first column of each row; And
Connecting the node created in the n-th column of each row as a child to the node of the previous row if the node created in the n-1th column of each row has no data in the n-2th column. Connecting the nodes of the current line to the children,
E-commerce method. The method of claim 5,
Generating the node,
Specifying a value of the data as a value of the generated node for a column with data and not specifying a value of the generated node for a column without data,
E-commerce method. The method of claim 2,
Converting the tabular data structure into a tree data structure,
Traversing the data of the transformed tree structure of each row of each of the tables to produce a single tree structure,
E-commerce method. delete delete delete delete delete The method of claim 1,
Sending a plagiarism guidance message to the seller terminal of the second seller,
Comparing the plagiarism search key of the second seller and the plagiarism search key of the first seller, and if there is less than a predetermined number of matching keys, further comprising the step of storing the one or more selected items,
E-commerce method. In the electronic commerce system including a server, a manager terminal, a seller terminal and a buyer terminal, the server,
One or more processors;
A memory for loading a computer program executed by the processor; And
Storage for storing the computer program,
The computer program,
Instructions for receiving item information of a textbook from the manager terminal;
Instructions for storing the item information received from the manager terminal;
An instruction for receiving a request for item information on a specific textbook from the seller terminal;
Instructions for transmitting the item information on the specific teaching material to the seller terminal;
Instructions for receiving a selection of one or more items among a plurality of items included in the items for the specific teaching material from the seller terminal;
Instructions for receiving a purchase request for the selection information from the buyer terminal; And
Including an instruction for transmitting the selection information to the buyer terminal,
Instructions for receiving a selection for one or more of the plurality of items included in the item from the seller terminal,
An instruction for randomly selecting two or more special indexes among indices for all items of the specific textbook before inputting the question prediction information by the seller terminal;
An instruction for receiving a selection of at least one item among a plurality of items included in the item from a seller terminal of a first seller after entry of prediction information by the seller terminal is allowed;
An instruction for storing each unique key as a plagiarism search key of a first seller if a unique key corresponding to the special index exists in a seller's selection item;
After inputting the question prediction information by the seller terminal and after receiving the selection of the first seller, selecting one or more items among the plurality of items included in the item from the seller terminal of the second seller. Receiving instruction;
When a plagiarism search key of a second seller, which is a unique key corresponding to the special index present in the selection item of the second seller, and a plagiarism search key of the first seller are compared, and there are more than a predetermined number of matching keys. Including an instruction for transmitting a plagiarism guidance message to the seller terminal of the second seller,
server.

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