JP2018133026A - Document conversion device and document conversion program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a document conversion device capable of increasing estimation accuracy of a user's learning level, and for converting an original document into the optimal document in accordance with the user's learning level.SOLUTION: The document conversion device comprises: an input part 101 for, when receiving the input of a document by a user, storing the received user's document input information in a first database 151; a learning level estimation part 102 for comparing the user's document input information stored in the first database with document component information in a second database 152 in which document component information preliminarily classified by a learning level is stored to estimate a user's learning level; and a conversion part 103 for decomposing an original document into components, and for converting the composed components in conformity with a level of corresponding components in the second database 152 in accordance with the learning level estimated by the learning level estimation part 102.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a document conversion apparatus and a document conversion program for converting an original document into a document according to a user's learning level.

  When providing an original document (including content having a document) to users with different learning levels, it is desirable to provide the original document after converting it to one using kanji, words, or phrases according to the learning level of each user.

  For example, when an original document is distributed to a child, the learning level differs depending on the child. Therefore, it is desirable to convert the document so that it is easy to read according to the reader.

  Also, if the original document is a document translated by translation software, the translated document will be the only level of content that can be converted by the translation software, so the level of the translated content is converted according to the partner. It is desirable to provide it.

  Alternatively, when providing documents for foreigners working in Japan, Japanese is often not sufficient, so it is desirable to provide kanji / word / phrase levels according to each person's level.

  Such conversion of the original document in accordance with the user's learning level has been conventionally performed by manual replacement, which is troublesome.

  Therefore, various techniques for creating a document according to the user's learning level have been proposed. For example, Patent Document 1 proposes a technique that can perform kana-kanji conversion processing in accordance with the user's kanji learning level and enhance the user's kanji learning effect.

  Patent Document 2 proposes a technique that enables kana-kanji conversion levels to be set appropriately in accordance with the progress of actual classes, and enables kana-kanji conversion that matches the purpose of use or the user. .

  Further, Patent Literature 3 proposes a learning support apparatus that can automatically generate and collect various learning example sentences suitable for the learner's vocabulary level and present them to the learner.

  Patent Document 4 proposes a technique for automatically generating a new learning practice question for a selected learning item based on a model of the current ability possessed by a specific learner and other information. ing.

JP 2002-73597 A JP-A-8-329064 JP 2007-121484 A JP 2010-266855 A

  However, the techniques of Patent Literature 1 and Patent Literature 2 are troublesome because it is necessary to input user level information such as the grade and age of the user. Moreover, there is a problem in that the estimation accuracy of the learning level is low because there is a difference in the individual learning level even if the user's grade and age are the same.

  In the technique described in Patent Document 3, the word level used on the website accessed by the user is set as the user level. However, the browsing site does not always match the user's level, and the estimation accuracy of the learning level is not limited. There is a problem that is low.

  Further, the technique described in Patent Document 4 sets the learner's knowledge level based on selection from a word or word group from text displayed on the user interface, the number of times the word is viewed, and interaction with the word. The knowledge level is determined based on the result of performing the above, and there is still a problem that the level estimation accuracy is low.

  As described above, all of the conventional techniques have a problem that the estimation accuracy of the learning level is low, and it is not possible to provide a document optimal for the learning level of the user.

  The present invention has been made to solve such a problem, and can improve the estimation accuracy of a user's learning level and convert an original document into an optimal document according to the user's learning level. It is an object to provide a conversion device and a document conversion program.

The above problem is solved by the following means.
(1) An input unit that accepts a user's input of a document and stores and stores the received user's document input information in a first database; a user's document input information stored in the first database; Learning level estimation means for estimating the user's learning level by comparing the document component information in the second database in which the document component information classified according to the learning level is stored, and the original document as the component And converting means for converting the decomposed components in accordance with the level of the corresponding component in the second database according to the learning level estimated by the learning level estimating means. Document conversion device characterized by this.
(2) The document conversion apparatus according to item 1 above, wherein the document component is a Chinese character.
(3) The document conversion apparatus according to (2), wherein the conversion unit applies a reading to a Chinese character.
(4) The document conversion apparatus according to item 1, wherein the document component is a word.
(5) The document conversion apparatus according to item 4, wherein the word is a foreign language word.
(6) The document conversion apparatus according to (1), wherein the document component is at least one of a picture and a chart.
(7) The document conversion device according to any one of items 1 to 6, wherein the document input information of the user is information input using an application used by the user.
(8) The document conversion apparatus according to any one of Items 1 to 6, further comprising character recognition processing means, wherein the document input information of the user is information obtained by performing character recognition processing on a document handwritten by the user by the character recognition processing means. .
(9) The learning level estimation means according to any one of the preceding items 1 to 8, wherein the level positioned at the top when the levels of the document components of the user's document input information are arranged in order of level is estimated as the user's learning level. The document conversion device described.
(10) The document conversion apparatus according to any one of Items 1 to 8, wherein the learning level estimation unit estimates the highest level among the document component levels of the user's document input information as the user's learning level.
(11) The learning level estimation means compares the document input information within a certain period of the user's document input information stored in the first database with the document components in the second database, thereby 11. The document conversion device according to any one of 1 to 10 above, wherein the learning level is estimated.
(12) The document conversion apparatus according to any one of the preceding items 1 to 11, further comprising a deletion unit that deletes the document input information after a predetermined period of time from among the user's document input information stored in the first database. .
(13) The document conversion device according to any one of items 1 to 12, wherein the user is a group user including a plurality of individual users.
(14) receiving an input of a document by a user, storing and storing the received user's document input information in the first database, the user's document input information stored in the first database, A learning level estimation step for estimating the learning level of the user by comparing the document component information in the second database in which the document component information classified according to the learning level is stored; A conversion step of converting the decomposed component into a corresponding component level in the second database according to the learning level estimated by the learning level estimation means. Document conversion program to be executed by any computer.
(15) The document conversion program according to item (14), wherein the document component is kanji.
(16) The document conversion program according to item 15 above, wherein in the conversion step, the computer executes a process of applying a reading to a kanji.
(17) The document conversion program according to item 14, wherein the document component is a word.
(18) The document conversion program according to item 17 above, wherein the word is a foreign language word.
(19) The document conversion program according to item 14, wherein the document component is at least one of a picture and a chart.
(20) The document conversion program according to any one of Items 14 to 19, wherein the document input information of the user is information input using an application used by the user.
(21) The character recognition processing step is further executed by the computer, and the document input information of the user is information obtained by performing character recognition processing on the document handwritten by the user by the character recognition processing step. Document conversion program described.
(22) In the learning level estimation step, the computer executes a process of estimating, as the learning level of the user, a level positioned higher when the document component levels of the user's document input information are arranged in order of level. The document conversion program according to any one of 14 to 21.
(23) In the learning level estimation step, according to any one of items 14 to 21 described above, wherein the computer executes a process of estimating the highest level among the document component levels of the user's document input information as the user's learning level. Document conversion program described.
(24) In the learning level estimation step, by comparing the document input information within a certain period of the user's document input information stored in the first database with the document components in the second database, 24. The document conversion program according to any one of items 14 to 23, which causes the computer to execute a process of estimating a learning level.
(25) The document according to any one of the above items 14 to 24, wherein the computer is caused to execute a deletion step of deleting the document input information after a predetermined period of time from among the user's document input information stored in the first database. Conversion program.
(26) The document conversion program according to any one of (14) to (25), wherein the user is a group user including a plurality of individual users.

  According to the inventions described in the preceding items (1) and (14), the input of the document by the user is accepted, and the received document input information of the user is stored and accumulated in the first database. The user's document input information stored in the first database is compared with the document component information in the second database in which the document component information classified in advance by the learning level is stored, and the user's learning level is determined. presume. Then, the original document is decomposed into constituent elements, and the decomposed constituent elements are converted in accordance with the level of the corresponding constituent elements in the second database according to the estimated learning level.

  That is, according to the present invention, the actually input document input information is collected in the first database, and the collected document input information is compared with the document component information in the second database which is a criterion for learning level. Then, the learning level is estimated. Therefore, it is not necessary to input user level information such as the user's grade and age, the user's grade and age, the word level used on the website accessed by the user, the user's word selection and the number of times the word is viewed, etc. Unlike the technique of estimating the learning level using indeterminate information, the learning level can be estimated with high accuracy, and the original document can be converted into a document of the optimum level for the user and provided.

  According to the inventions described in the above items (2) and (15), the kanji input and accumulated by the user is compared with the kanji of the level determination criterion stored in the second database, thereby achieving a high-accuracy learning level. Can be estimated.

  According to the inventions described in the preceding items (3) and (16), it is possible to convert the original document into a document obtained by adding the reading to the Chinese character.

  According to the inventions described in the above items (4) and (17), a high-accuracy learning level is obtained by comparing the words input and accumulated by the user with the words of the level determination criteria stored in the second database. Can be estimated.

  According to the inventions described in the preceding paragraphs (5) and (18), by comparing the foreign language words inputted and accumulated by the user with the foreign language words of the level judgment criteria stored in the second database. Therefore, it is possible to estimate the learning level with high accuracy.

  According to the inventions described in (6) and (19) above, at least one of the pictures and diagrams input and accumulated by the user is compared with the pictures or diagrams of the level judgment criteria stored in the second database. Thus, it is possible to estimate the learning level with high accuracy.

  According to the inventions described in the preceding items (7) and (20), the information input using the application used by the user is compared with the information of the level determination criteria stored in the second database, thereby improving accuracy. A high learning level can be estimated.

  According to the inventions described in the preceding paragraphs (8) and (21), by comparing the information obtained by performing the character recognition processing on the document handwritten by the user with the information on the level determination criterion stored in the second database, the accuracy can be improved. A high learning level can be estimated.

  According to the inventions described in the preceding items (9) and (22), the level that is positioned higher when the document component levels of the user's document input information are arranged in level order is estimated as the user's learning level. A user's learning level can be estimated accurately.

  According to the inventions described in the above items (10) and (23), the highest level among the document component levels of the user's document input information is estimated as the user's learning level. Can be estimated.

  According to the inventions described in (11) and (24) above, the document input information within a certain period of the user's document input information stored in the first database is converted to the document component in the second database. Since the user's learning level is estimated by the comparison, the user's current learning level can be accurately estimated.

  According to the inventions described in the above items (12) and (25), the document input information after a certain period of time is deleted from the user's document input information stored in the first database. Can prevent the user's current learning level from being obstructed.

  According to the inventions described in (13) and (26) above, since the user is a group user including a plurality of individual users, the learning level of the group is estimated, and the original document is set to the estimated learning level of the group. It can be converted into a corresponding document.

It is a block diagram which shows the internal structure of the document conversion apparatus which concerns on one Embodiment of this invention. It is a block diagram which shows the function structure of the document conversion apparatus shown in FIG. It is a figure for demonstrating an example of the method of converting an original document according to a user's learning level. It is a figure for demonstrating the other example of the method of converting an original document according to a user's learning level. It is a block diagram which shows the function structure of the document conversion apparatus which concerns on other embodiment of this invention. It is a flowchart which shows the input process of the document input information performed by a document conversion apparatus. It is a flowchart which shows the estimation process of the learning level performed by the document conversion apparatus. It is a flowchart which shows the document conversion process with respect to the original document performed by the document conversion apparatus.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 is a block diagram showing an internal configuration of a document conversion apparatus 1 according to an embodiment of the present invention. In this embodiment, a multi-function digital image processing apparatus called MFP (Multi Function Peripherala) having a copy function, a printer function, a facsimile function, and the like is used as the document conversion apparatus 1. 1 is not limited to an image processing apparatus, but may be an information processing apparatus such as a personal computer, a tablet terminal, or a smartphone.

  The document conversion apparatus 1 includes a CPU 11, a ROM 12, a RAM 13, a scanner unit 14, a storage unit 15, a printer unit 16, an operation panel 17, a network controller (N1C) 18, a character recognition processing unit 19, and the like. I have.

  The CPU 11 comprehensively controls the entire document conversion apparatus 1 and controls basic functions such as a copy function, a printer function, a scan function, and a FAX function. In this embodiment, the input of the document by the user is accepted, and the input of the accepted document is stored in the storage unit 15 together with the date, and the first database in which the user's document input information is accumulated (hereinafter referred to as the database). DB (also referred to as DB) or by comparing the user's document input information stored in the first DB with the document component information stored in the second DB, which will be described later. The estimation and the original document (including the original content having the document) are decomposed into components, and the decomposed components are converted according to the estimated learning level. Details will be described later. .

  The ROM 12 is a memory that stores an operation program of the CPU 11 and the like, and the RAM 13 is a memory that provides a work area when the CPU 11 operates based on the operation program.

  The scanner unit 14 is a reading unit that reads an image of a document placed on a document table (not shown) and outputs image data.

  The storage unit 15 is configured by a non-volatile storage device such as a hard disk drive (HDD), for example, and stores job histories, document image data read by the scanner unit 14, data transmitted from a user terminal, and the like. Remembered. Furthermore, in this embodiment, the first DB 151 in which the user's document input information is stored together with the date information is formed for each user, and the second component element information serving as a criterion for determining the user's learning level is stored. DB 152 is formed. The document component information stored in the second DB 152 is classified in advance according to the learning level. Examples of document components include kanji, words, foreign words, phrases, pictures, charts, etc., and the second DB 152 also has DBs for kanji, words, foreign words, phrases, pictures, charts, respectively. In each DB, kanji, words, foreign words, phrases, pictures, charts, etc. are stored in levels.

  The printer unit 16 prints image data of a document read by the scanner unit 14 or print data from a user terminal in accordance with an instructed mode, and constitutes a printing unit.

  The operation panel 17 is used for various input operations and the like, and is a key input provided with a display unit including a touch panel type liquid crystal display for displaying a message, an operation screen, etc., and a ten key, a start key, a stop key, and the like. Department.

  The network controller 18 transmits and receives data by controlling communication with an external device or the like on the network 5.

  The character recognition processing unit 19 performs character recognition processing on the user's handwritten document read by the scanner unit 14 and converts it into character data.

  Note that the first DB 151 that stores the user's document input information may be stored not in the storage unit 15 of the document conversion apparatus 1 but in an external DB device including an external server. In this case, the document conversion device 1 transfers the input document input information to the external DB device together with user information and date information. In addition, the second DB 152 that stores document constituent element information that is a criterion for determining the learning level of the user may also exist in the external DB device. When the learning level is estimated, the document input information of the corresponding user is acquired from the first DB 151 of the external DB device, and the document component information for determination is acquired from the second DB 152. good.

  FIG. 2 is a block diagram showing a functional configuration of the document conversion apparatus 1 shown in FIG. The document conversion apparatus 1 includes an input unit 101, a learning level estimation unit 102, and a document conversion unit 103.

  The input unit 101 inputs a document such as a mail or a document created by the user using the operation panel 17 to the document conversion apparatus 1. The document input information input by the input unit 101 is stored together with date information in the first DB 151 created for each user. Each time there is a document input by the user, storage and accumulation in the first DB 151 are performed.

  The learning level estimation unit 102 compares the document input information of the user stored in the first DB 151 with the document component information classified in advance by the learning level stored in the second DB 152. Estimate the user's learning level. The learning level is estimated as follows.

  That is, the document component in the user's document input information stored in the first DB 151 is compared with the document component information for determination stored in the second DB 152. When the document component is, for example, a kanji, all kanji used in the user's document input information are compared with kanji divided into levels stored in the second DB 152 for kanji, and the learning level To determine if the kanji is used. Then, when all the used Chinese characters are arranged in descending order, the level located at the top, for example, the level located at the top 20%, is estimated as the user's learning level.

  Or you may estimate the most level among the levels of all the used Chinese characters as a user's learning level.

  When the document component is set to a word, the word included in the user's document input information is compared with the level-divided word stored in the second DB 152 for the word, and the same as in the case of kanji. Estimate the user's learning level.

  Similarly, when the document component is set to a foreign language word, or to a phrase, picture, chart, etc., the level-divided foreign language stored in the second DB 152 for the foreign language word is also used. Leveled phrases stored in the second DB 152 for words, phrases, leveled pictures stored in the second DB 152 for pictures, and stored in the second DB 152 for diagrams Compare with the leveled charts and estimate the user's learning level. Note that the learning level may be estimated from two or more components instead of estimating from one component of kanji, words, foreign language words, phrases, pictures, and diagrams.

  The document conversion unit 103 decomposes the original document 200 input to the document conversion apparatus 1 into components, and converts the decomposed components according to the learning level estimated by the learning level estimation unit 102 and outputs the converted component It is. The example of FIG. 2 shows the case where the document component is a kanji character. For this purpose, the kanji extraction unit 103a that extracts the kanji character by decomposing the component element of the input original document and the extracted kanji character for the user. Has a kanji conversion unit 103b for converting according to the learning level. The document into which the kanji has been converted is output by printing or the like and provided to the user as the provision document 300.

  An example of a method for converting the original document 200 according to the learning level of the user will be described with reference to FIG. This example shows a case where the document component is a Chinese character.

  For example, when the original document 200 includes a kanji character “... with confidence ...”, the kanji character “relief” is converted according to the learning level of the user. In the second DB 152 for kanji, as shown in FIG. 3, kanji classified into level 1, level 2, level 3... Are stored. “Low” is classified as Level 3 and “Heart” is classified as Level 2.

  The document conversion unit 103 refers to the learning level of the user estimated by the learning level estimation unit 102 and the kanji level in the second DB 152. If the learning level of the user is 1, both “low” and “heart” Since it is not a level 1 kanji, it converts “reliable” to “reliable”. When the user's learning level is 2, “heart” is converted to “anshin” because “heart” is a level 2 Chinese character.

  When the original document includes hiragana notation such as “Anshin”, all or part of “reliable” or “anshin” may be converted into kanji according to the learning level of the user.

  Further, as shown in FIG. 4, the constituent elements obtained by decomposing the original document may be subjected to reading according to the level of the corresponding constituent elements in the second DB 152 according to the estimated learning level. Specifically, if the decomposed component is “safe”, and the user's learning level is 1, neither “cheap” nor “mind” is a level 1 Kanji character, so “anshin” is used. When the user's learning level is 2, since “mind” is a level 2 kanji and “an” is a level 3 kanji, only “an” is spelled “an”.

  FIG. 5 is a block diagram showing a functional configuration of the document conversion apparatus 1 according to another embodiment of the present invention. In this embodiment, the input unit 101 reads a user's handwritten document by the scanner unit 14 and stores and accumulates information subjected to character recognition processing by the character recognition processing unit 19 in the first DB 151 as user document input information. It has become. The configurations of the learning level estimation unit 102, the document conversion unit 103, the first DB 151, and the second DB 152 are the same as those of the document conversion apparatus 1 shown in FIG. Further, the learning level estimation unit 102 estimates the learning level, and the document conversion unit 103 performs document conversion on the original document in the same manner as the document conversion apparatus 1 shown in FIG.

  In addition to the information obtained by reading the user's handwritten document by the scanner unit 14 and performing character recognition processing, the user's document input information input by the input unit 101 uses, for example, an application used by the user such as a character input application. It may be input information.

  FIG. 6 is a flowchart showing input processing of document input information executed by the document conversion apparatus 1. The processes shown in the flowchart of FIG. 6 and the flowcharts shown in FIG. 7 and subsequent figures are executed by the CPU 11 of the document conversion apparatus 1 operating according to an operation program stored in the ROM 12 or the like.

  In step S01, user input of a document is performed, and in step S02, input contents (document input information) are stored in the first DB 151 together with date information. Every time there is user input of a document, document input information is accumulated in the first DB 151. In step S03, the document input information after a certain period has been deleted. Since the user's learning level often changes between the past and the present, by deleting the document input information after a certain period of time, the existence of old document input information can be used to estimate the user's current learning level. Can be prevented, and the latest learning level can be estimated. Of course, it is not necessary to delete the document input information. Although not deleted, only the document input information within a certain period may be extracted and used to estimate the learning level. Also in this case, the latest learning level of the user can be accurately estimated.

  FIG. 7 is a flowchart showing a learning level estimation process executed by the document conversion apparatus 1.

  In step S11, the component of the document input information stored in the first DB 151 is compared with the level-divided document component stored in the second DB 152, and based on the comparison result in step S12. Estimate the user's learning level.

  FIG. 8 is a flowchart showing document conversion processing for the original document executed by the document conversion apparatus 1.

  After inputting the original document in step S21, in step S22, the original document is decomposed into components such as kanji, words, phrases, and extracted. Next, in step S23, the estimated learning level (step S12) is acquired, and in step S24, conversion is performed in accordance with the levels of kanji, words, and phrases in the second DB 152. In step S25, the converted provided document is output.

  As described above, in this embodiment, the document input information actually input by the user is collected in the first DB 151, and the collected document input information is stored in the second DB 152 serving as a criterion for determining the learning level. The learning level is estimated in comparison with the document component information. Therefore, it is not necessary to input user level information such as the user's grade and age, the user's grade and age, the word level used on the website accessed by the user, the user's word selection and the number of times the word is viewed, etc. Unlike the technique of estimating the learning level using indeterminate information, the learning level can be estimated with high accuracy, and the original document can be converted into a document of the optimum level for the user and provided.

  Therefore, when the original document is distributed to children, the document can be converted and provided so as to be easy to read according to the learning level of the child.

  In addition, when providing business documents, Kanji, words, phrases, etc. of the created documents are changed according to the learning level of the other party, or translated documents are converted using translation software. Therefore, the content level after translation can be converted and provided according to the other party.

  In addition, when providing documents for foreigners working in Japan, it is also possible to convert kanji, words, phrases, etc. in the document according to the learning level for foreigners who do not have sufficient Japanese. Become.

  Although one embodiment of the present invention has been described above, the present invention is not limited to the above embodiment. For example, the user whose learning level is to be estimated is not limited to an individual, and may be a group user including a plurality of individual users. In this case, the document information input by the users constituting the group may be stored and accumulated in one first DB 151 and collected. In this way, by estimating the learning level of the group user and converting the original document according to the estimated learning level, for example, when a business document is transmitted to the organization, a change according to the destination customer is made. It becomes possible. Specifically, when sending to the technical department, the organization usually uses technical terms, so send documents containing technical terms, and when sending to the sales department, convert technical terms into general terms and send them. , Can be used properly.

1 Document Conversion Device 11 CPU
12 ROM
DESCRIPTION OF SYMBOLS 14 Scanner part 19 Character recognition process part 101 Input part 102 Learning level estimation part 103 Document conversion part 103a Kanji extraction part 103b Kanji conversion part

Claims (26)

An input means for receiving a document input by a user and storing and storing the received user document input information in the first database;
By comparing the user's document input information stored in the first database with the document component information in the second database in which the document component information classified in advance by the learning level is stored, the user Learning level estimation means for estimating the learning level of
Conversion means for decomposing the original document into constituent elements and converting the decomposed constituent elements in accordance with the level of the corresponding constituent elements in the second database according to the learning level estimated by the learning level estimating means; ,
A document conversion apparatus comprising:   The document conversion apparatus according to claim 1, wherein the document component is a Chinese character.   The document conversion apparatus according to claim 2, wherein the conversion unit adds a reading to a Chinese character.   The document conversion apparatus according to claim 1, wherein the document component is a word.   The document conversion apparatus according to claim 4, wherein the word is a foreign language word.   The document conversion apparatus according to claim 1, wherein the document component is at least one of a picture and a chart.   The document conversion apparatus according to claim 1, wherein the document input information of the user is information input using an application used by the user. Equipped with character recognition processing means,
The document conversion apparatus according to claim 1, wherein the document input information of the user is information obtained by performing character recognition processing on a document handwritten by the user by the character recognition processing unit.   9. The learning level estimation unit according to claim 1, wherein the learning level estimation means estimates a level positioned higher when the levels of document constituent elements of the user's document input information are arranged in order of levels as a user learning level. Document conversion device.   The document conversion apparatus according to claim 1, wherein the learning level estimation unit estimates the highest level among the document component levels of the user's document input information as the user's learning level.   The learning level estimation means compares the document input information within a certain period of the user's document input information stored in the first database with the document component in the second database, thereby obtaining the user's learning level. The document conversion apparatus according to claim 1, wherein   The document conversion apparatus according to claim 1, further comprising a deletion unit that deletes document input information after a predetermined period of time from among the user's document input information stored in the first database.   The document conversion apparatus according to claim 1, wherein the user is a group user including a plurality of individual users. An input step for receiving a document input by the user and storing and storing the received user document input information in the first database;
By comparing the user's document input information stored in the first database with the document component information in the second database in which the document component information classified in advance by the learning level is stored, the user A learning level estimation step for estimating the learning level of
A conversion step of decomposing the original document into constituent elements and converting the decomposed constituent elements in accordance with the level of the corresponding constituent element in the second database according to the learning level estimated by the learning level estimating means; ,
Conversion program for causing a computer of the document conversion apparatus to execute the program.   The document conversion program according to claim 14, wherein the document component is a Chinese character.   The document conversion program according to claim 15, wherein in the conversion step, the computer is caused to execute a process of adding kana to kanji.   The document conversion program according to claim 14, wherein the document component is a word.   The document conversion program according to claim 17, wherein the word is a foreign language word.   The document conversion program according to claim 14, wherein the document component is at least one of a picture and a chart.   20. The document conversion program according to claim 14, wherein the document input information of the user is information input using an application used by the user. Causing the computer to further perform a character recognition processing step;
The document conversion program according to any one of claims 14 to 19, wherein the user's document input information is information obtained by performing character recognition processing on a document handwritten by the user in the character recognition processing step.   The said learning level estimation step makes the said computer perform the process which estimates the level located higher when the level of the document component of a user's document input information is arranged in order of a level as a user's learning level. 21. The document conversion program according to any one of 21.   The said learning level estimation step makes the said computer perform the process which estimates the largest level among the levels of the document component of a user's document input information with a user's learning level. Document conversion program.   In the learning level estimation step, the user's learning level is determined by comparing the document input information within a certain period of the user's document input information stored in the first database with the document components in the second database. The document conversion program according to any one of claims 14 to 23, which causes the computer to execute a process for estimating the image.   The document conversion program according to any one of claims 14 to 24, which causes the computer to execute a deletion step of deleting document input information after a predetermined period of time from among the user's document input information stored in the first database. .   The document conversion program according to any one of claims 14 to 25, wherein the user is a group user including a plurality of individual users.

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