Patent Publication Number: US-2022222291-A1

Title: File management device, file management method, and non-transitory computer readable medium

Description:
The present invention relates to a file management device, a file management method, and a program. 
     BACKGROUND ART 
     For example, Patent Literature 1 discloses a document processing device including a classification rule registering means for registering a combination of a first rule and a second rule applied to the first rule as a classification rule for classifying a document; and a classification rule integrating means for integrating a plurality of different classification rules registered by the classification rule registering means while excluding overlapping contents between the plurality of different classification rules. 
     In addition, Patent Literature 2 discloses a classification rule creation support method executed by a computer, the method including the steps of storing a new data item and a category of the new data item in a storage device; extracting a feature pattern including a condition including a feature element of the new data item stored in the storage device and a corresponding category from data stored in a correct data storage unit that stores the data item and the category of the data item, and storing the feature pattern in a feature pattern storage unit; and grouping the feature pattern stored in the feature pattern storage unit into a first set matching the category of the new data item stored in the storage device and a second set not matching the category of the new data item stored in the storage device, and storing a grouping result in a group data storage unit. 
     Furthermore, Patent Literature 3 discloses a document processing device including a storage means; an input means to which document image data representing a document is input; a specifying means that performs layout analysis on the document image data input to the input means and specifies a layout of the document representing the document image data; a determination means that performs character analysis on the document image data input to the input means and determines an attribute of each described item of the document representing the document image data; a generation means that specifies a hierarchical structure between the described items on the basis of the layout specified by the specifying means and the attribute of each described item determined by the determination means and generates rule data representing the hierarchical structure; and a writing means that writes the rule data generated by the generation means to the storage unit. 
     CITATIONS LIST 
     Patent Literature 
     
         
         Patent Literature 1: Japanese Laid-Open Patent No. 2013-251610 
         Patent Literature 2: Japanese Laid-Open Patent No. 2007-052744 
         Patent Literature 3: Japanese Laid-Open Patent No. 2007-052615 
       
    
     SUMMARY OF INVENTION 
     Technical Problems 
     An object of the present invention is to provide a file management device that can promote the use of tags. 
     Solutions to Problems 
     A file management device according to the present invention includes a rule storage unit that stores a feature included in a data file and a tag provided to the data file in association with each other as a provision rule; a tag providing unit that provides a tag to a newly input data file based on the provision rule stored in the rule storage unit; and a rule display unit that displays the provision rule stored in the rule storage unit. 
     Preferably, the rule display unit displays the provision rule using a character string. 
     Preferably, the rule display unit displays the provision rule in an editable state. 
     Preferably, a common feature extracting unit that extracts a feature common to a plurality of data files to which the same tag is added from the data files is further provided, and the rule storage unit stores the feature extracted by the common feature extracting unit as a part of the provision rule. 
     Preferably, a rule updating unit that updates the provision rule stored in the rule storage unit based on a newly input data file, and a fixed condition setting unit that sets a fixed condition in which automatic update by the rule updating unit is prohibited among the provision rules stored in the rule storage unit according to an input of a user are further provided. 
     Preferably, when the user specifies one of the data files, the rule display unit displays the provision rule of a tag provided by the tag providing unit to the specified data file. 
     Preferably, the rule display unit displays a list of tags of the provision rules stored in the rule storage unit, and displays the provision rule of the selected tag when the user selects one of the tags. 
     Preferably, the provision rule stored in the rule storage unit includes a plurality of determination elements expressible by a character string, and the rule updating unit selects a feature registered as the determination element of the provision rule based on at least one of an appearance frequency, a closeness, and an appearance position and a uniqueness from among the features common to the plurality of data files. 
     A file management method according to the present invention includes a tag providing step of providing a tag to a newly input data file with reference to a database that stores a feature included in a data file and a tag provided to the data file in association with each other as a provision rule; and a rule displaying step of displaying the provision rule stored in the database. 
     A program according to the present invention causes a computer to execute a tag providing step of providing a tag to a newly input data file with reference to a database that stores a feature included in a data file and a tag provided to the data file in association with each other as a provision rule; and a rule displaying step of displaying the provision rule stored in the database. 
     Advantageous Effects of Invention 
     The read image can be appropriately classified. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a diagram illustrating an overall configuration of a file management system  1 . 
         FIG. 2  is a diagram illustrating a hardware configuration of a file management device  5 . 
         FIG. 3  is a diagram illustrating a functional configuration of the file management device  5 . 
         FIG. 4A  is a table for describing a tagging rule,  FIG. 4B  is a table for describing a tagging rule of the tag “estimate”, and  FIG. 4C  is a diagram illustrating features extracted by the common feature extracting unit  502 . 
         FIG. 5A  is a table illustrating a keyword and position information of the keyword,  FIG. 5B  is a table illustrating date and position information of the date, and  FIG. 5C  is a table illustrating an image size and the number of colors used. 
         FIG. 6  is a flowchart illustrating a process of registering and updating a tagging rule by the file management device  5  (S 10 ). 
         FIG. 7  is a screen example of a tagging operation by the user. 
         FIG. 8A  is a callout example 1 of a customized screen of a tagging rule, and  FIG. 8B  is an example of a customized screen of a tagging rule by a user. 
         FIG. 9A  is a callout example 2 of a customized screen of a tagging rule, and  FIG. 9B  is a callout example 3 of the customized screen of the tagging rule. 
         FIG. 10  is a flowchart illustrating tagging and tag proposing process (S 20 ) by the file management device  5 . 
         FIG. 11  is a flowchart illustrating a process of updating a tagging rule in accordance with a response of a user to a tagging proposal (S 30 ). 
         FIG. 12  is a diagram illustrating a user&#39;s response operation screen for a tagging proposal. 
         FIG. 13A  is a diagram illustrating condition candidates of a tagging rule of “claim (2018)” and the document C,  FIG. 13B  is a table illustrating scores of keywords of the condition candidates, and  FIG. 13C  is an update example of a tagging rule. 
         FIG. 14A  is a diagram illustrating a tagging rule of the “claim” and features of the document D,  FIG. 14B  is a table illustrating scores of keywords of the condition candidates, and  FIG. 14C  is an update example of a tagging rule. 
         FIG. 15A  is a diagram illustrating the tagging rule of “AA company_claim” and the feature of the newly tagging document G which is the claim of the BB company,  FIG. 15B  is a diagram illustrating the tagging rule of “∘∘ company_claim”,  FIG. 15C  is a table illustrating the scores of the keywords of the condition candidates, and  FIG. 15D  is an update example of the tagging rule data. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Hereinafter, an embodiment of the present invention will be described with reference to the drawings. 
       FIG. 1  is a diagram illustrating an overall configuration of a file management system  1 . 
     As illustrated in  FIG. 1 , the file management system  1  includes a plurality of scanners  3   a ,  3   b ,  3   c , a file management device  5 , and a user terminal  7 , which are connected to each other via a network  9 . The scanner  3   a , the scanner  3   b , and the scanner  3   c  are collectively referred to as a scanner  3 , and the user terminal  7   a  and the user terminal  7   b  are collectively referred to as a user terminal  7 . 
     The scanner  3  is an optical reading device, and transmits acquired image data to the file management device  5 . 
     The file management device  5  is a computer terminal, and provides a tag for classifying image data received from the scanner  3  to the image data. Specifically, the file management device  5  holds a rule for tagging, which is a tagging rule, and provides a suitable tag to a data file based on the tagging rule and a feature of the data file obtained by performing OCR processing on the image data. Further, the file management device  5  generates and updates the tagging rule according to the user&#39;s operation. Note that the tagging rule is an example of provision rule according to the present invention. 
     The user terminal  7  is a computer terminal operated by a user, and displays a user interface provided by the file management device  5 . 
       FIG. 2  is a diagram illustrating a hardware configuration of the file management device  5 . 
     As illustrated in  FIG. 2 , the file management device  5  includes a CPU  200 , a memory  202 , an HDD  204 , a network interface  206  (network IF  206 ), a display device  208 , and an input device  210 , which components are connected to each other via a bus  212 . 
     The CPU  200  is, for example, a central processing unit. 
     The memory  202  is, for example, a volatile memory, and functions as a main storage device. 
     The HDD  204  is, for example, a hard disk drive device, and stores a computer program (for example, a file management program  50  in  FIG. 3 ) and other data files (for example, a tagging rule database  600  of  FIG. 3 ) as a nonvolatile recording device. 
     The network IF  206  is an interface for wired or wireless communication, and for example, realizes communication in an internal network  9 . 
     The display device  208  is, for example, a liquid crystal display. 
     The input device  210  is, for example, a keyboard and a mouse. 
       FIG. 3  is a diagram illustrating a functional configuration of the file management device  5 . 
     As illustrated in  FIG. 3 , in the file management device  5  of the present example, the file management program  50  is installed, and the tagging rule database  600  (tagging rule DB  600 ) is configured. 
     The file management program  50  includes an acquisition unit  500 , a common feature extracting unit  502 , a collation unit  504 , a score calculating unit  506 , a tag providing unit  508 , a rule updating unit  510 , a fixed condition setting unit  512 , and a rule display unit  514 . 
     A part or all of the file management program  50  may be realized by hardware such as ASIC, or may be realized by borrowing a part of a function of an operating system (OS). 
     In the file management program  50 , the acquisition unit  500  acquires image data read by the scanner  3 . 
     The common feature extracting unit  502  extracts features common to a plurality of data files to which the same tag is provided from the data files. For example, a data file refers to that in which optical character recognition (OCR) processing is performed on the image data. Specifically, the common feature extracting unit  502  performs the OCR processing on the image data acquired from the acquisition unit  500 , and extracts a feature of the data file based on an OCR processing result. More specifically, the common feature extracting unit  502  extracts, as features, at least one of a character string described in a data file, a date, an image size of the data file, and the number of colors used for an image of the data file. 
     Here, the tagging rule DB  600  will be described. 
     The tagging rule DB  600  stores the features extracted by the common feature extracting unit  502  and the tags provided to these data files in association with each other as a tagging rule. Specifically, the tagging rule DB  600  stores a tag name and “condition candidates” and “conditions” associated with the tag name. The “condition” is a constraint for providing a “tag name” associated with a data file, and is a common feature extracted from a plurality of data files to which the same tag is provided. Similarly, the “condition candidate” is a common feature extracted from a plurality of data files, and the “condition” is selected from among the “condition candidates”. The tagging rule DB  600  is an example of a rule storage unit according to the present invention. 
     The collation unit  504  collates newly input data file with the feature registered as the tagging rule. The newly input data file refers to a data file in which OCR processing is performed on the image data acquired by the acquisition unit  500 . Specifically, the collation unit  504  determines a matching degree between the data file subjected to the OCR processing by the common feature extracting unit  502  and the feature registered in the tagging rule stored in the tagging rule DB  600 . 
     The score calculating unit  506  calculates a score to be a determination element of each “condition candidate”, and selects the “condition” from among the “condition candidates” having a score greater than or equal to a threshold value. Specifically, the score calculating unit  506  calculates scores of the appearance frequency, the closeness, the appearance position, and the uniqueness of each “condition candidate”, adds the scores while weighting each score, and calculates the superiority of the “condition candidate”. 
     The tag providing unit  508  provides a tag to a newly input data file based on a tagging rule stored in the tagging rule DB  600 . 
     Specifically, the tag providing unit  508  searches for a feature registered as a tagging rule from a newly input data file, and provides a tag associated with this feature to the newly input data file when any feature is found. 
     More specifically, in a case where a part of a feature registered as a tagging rule is found from a newly input data file, the tag providing unit  508  proposes a tag associated with this feature to the user, and provides the tag according to an operation of the user. A case where a part of the features is found from the newly input data file refers to a case where the matching rate between the features extracted by the common feature extracting unit  502  and the features of the tagging rule is 50% to 99%. 
     The rule updating unit  510  generates and updates the tagging rule. Specifically, the rule updating unit  510  selects a feature to be registered as a determination element of the tagging rule based on at least one of the appearance frequency, the closeness, and the appearance position and the uniqueness from among the features common to the plurality of data files. More specifically, the rule updating unit  510  selects the “condition” from the “condition candidates” in which the total score calculated by the score calculating unit  506  is higher than the threshold value, and updates the tagging rule. 
     Furthermore, specifically, when the collation unit  504  determines that the newly input data file matches a part of the features registered as the tagging rule and the user adopts the proposed tag, the rule updating unit  510  updates the tagging rule such that the newly input data file matches the features registered as the tagging rule. 
     Moreover, when the collation unit  504  determines that the newly input data file matches a part of the features registered as the tagging rule and the user refuses the proposed tag, the rule updating unit  510  updates the tagging rule such that the newly input data file does not match the features registered as the tagging rule. 
     The fixed condition setting unit  512  sets a fixed condition in which automatic update by rule updating unit  510  is prohibited among the tagging rules stored in tagging rule DB  600  according to the input of the user. That is, the fixed condition is a part of the tagging rule, and is a part where automatic update by the rule updating unit  510  is prohibited. For example, in a case where the user edits a part of the tagging rule, the fixed condition setting unit  512  sets the edited part as the fixed condition. As illustrated in  FIG. 8B , the fixed condition setting unit  512  of the present example sets the “condition” selected by the user as the fixed condition. 
     The rule display unit  514  displays the tagging rule registered in the tagging rule DB  600  by using a character string, and receives an editing operation on the displayed tagging rule. For example, when the user specifies one of the data files, the rule display unit  514  displays a tagging rule of the tag provided by the tag providing unit  508  to the specified data file. In addition, the rule display unit  514  may display a list of tags of the tagging rules stored in the tagging rule DB  600 , and display a provision rule of the selected tag when the user selects one of the tags. 
     Next, the tagging rule stored in the tagging rule DB  600  will be described. 
       FIG. 4A  is a table for describing a tagging rule,  FIG. 4B  is a table for describing a tagging rule of the tag “estimate”, and  FIG. 4C  is a diagram illustrating features extracted by the common feature extracting unit  502 . 
     As illustrated in  FIG. 4A , the tagging rule has a “tag name” and a “condition” associated with the “tag name”. The “tag name” is a name for classifying a data file. The “condition” is a constraint for providing a “tag name”, and is a common feature extracted from data files to which the same tag is provided. When the data file retrieved next time corresponds to the “condition”, the file management device  5  automatically provides the “tag name” associated with the “condition” to the retrieved data file. 
     Furthermore, the “condition” is selected from the “condition candidates”. The “condition candidate” is a feature extracted from the data file by the common feature extracting unit  502 . Specifically, as illustrated in  FIG. 4B , “condition candidate” and “condition” are associated with the tag “estimate”, and the “condition candidate” is not included in the tagging “condition”, but is a feature extracted from a data file stored as a candidate of the “condition” for updating the tagging rule. 
     More specifically, the common feature extracting unit  502  extracts the “condition candidates” for each item from the data file illustrated in  FIG. 4C , as illustrated in  FIG. 4B . The score calculating unit  506  calculates a score representing the superiority of each condition candidate, and the rule updating unit  510  selects the “condition” from among the “condition candidates” having a score of greater than or equal to a threshold value on the basis of the total score of each “condition candidate”. 
       FIG. 5  is a diagram illustrating condition candidates extracted from a data file. 
     As illustrated in  FIG. 5 , the “condition candidate” is a feature extracted from a data file by the common feature extracting unit  502 , and includes a character string and vertical and horizontal lengths of an image. Specifically, the “condition candidate” includes a word (keyword) in the sentence of the data file, a value of the document date, a value of the vertical and horizontal length of the image, and the like. 
     For the keyword, as illustrated in  FIG. 5A , the common feature extracting unit  502  records a character string of the keyword in the data file and position information in which the character string is described as features. Specifically, the common feature extracting unit  502  performs the morphological analysis on the data file based on the result of the OCR processing, and sets the divided words as the keyword condition candidates. The common feature extracting unit  502  sets, as keyword conditions, a maximum of five keyword condition candidates whose scores satisfy a specific condition among the keyword condition candidates. 
     With respect to the document date, as illustrated in  FIG. 5B , the common feature extracting unit  502  decomposes the date in the data file into elements of year/month/day, and records position information in which the date is described as a feature. In a case where a date is written in the document, the common feature extracting unit  502  sets the respective elements of year, month, day, and day of the week as a document date condition candidate. The common feature extracting unit  502  sets, as the document date condition, at most one of the elements whose score satisfies the specific condition among the document date condition candidates. 
     With respect to the image size, as illustrated in  FIG. 5C , the common feature extracting unit  502  sets the vertical and horizontal lengths of the data file as image size condition candidates, and sets, as the image size condition, at most one of the elements whose score satisfies the specific condition among the image size condition candidates. 
     In addition, in addition to the keyword, the value of the document date, and the vertical and horizontal lengths of the image, the rule updating unit  510  may use “format”, “attribute value of business card or receipt (company name or address)”, and “color of image” as condition candidates, and create a tagging rule on the condition of matching or similarity thereof. 
     The tag providing unit  508  provides a tag to a data file that satisfies the “condition”. Specifically, the tag providing unit  508  provides the tag in a case where the feature of the data file matches the keyword of the tagging rule, is similar to the document date, and is similar to the vertical and horizontal lengths of the image. 
     For example, the condition of the keyword is satisfied by a specific character string being described in the data file. The similar condition of the document date is satisfied by the date described in the data file having a certain feature. The similar condition of the vertical and horizontal lengths of the image is satisfied by the vertical and horizontal sizes of the image having a certain feature. 
     Next, a method of calculating the score of the condition candidate will be described. 
     Each condition candidate has a score for appearance frequency, closeness, appearance position, and uniqueness. Each score increases or decreases between 0 and 10. 
     The score of the appearance frequency is calculated based on how many data files a certain feature appears in all the tagged data files. The score of the appearance frequency increases as the number of appearances increases. The score is 10 for a feature common to all the tagged data files. 
     The score of closeness is calculated based on whether a certain feature corresponds to a recently input data file. The initial value of the score of closeness is a maximum value (10). In addition, when the feature does not apply to the added data file, the score of closeness decreases. 
     The score of the appearance position is calculated based on whether or not the appearance position is described at a close position on the data file. The score of the appearance position is the maximum value (10) for the same place, and the score of the appearance position decreases as the position moves away. 
     The score of the uniqueness is calculated based on whether or not the feature is unique to the tagging rule. When a tagging proposal is made to a data file corresponding to the tagging rule and when the user refuses the proposal, the score calculating unit  506  adds the uniqueness scores of the “condition” and the “condition candidate” that exist in the tagging rule but do not exist in the data file. 
     The score calculating unit  506  calculates the scores of the appearance frequency, the closeness, the appearance position, and the uniqueness, adds the scores while weighting each score, and calculates the superiority of the “condition candidate”. The score calculating unit  506  calculates the total score by using the expression “total score=α×score of appearance frequency+β×score of closeness+γ×score of appearance position+δ×score of uniqueness”. The rule updating unit  510  selects a “condition” from condition candidates in which the total score calculated by the score calculating unit  506  is higher than a threshold value. 
       FIG. 6  is a flowchart illustrating the process of registering and updating a tagging rule by the file management device  5  (S 10 ). In  FIG. 6 , the registration and update of the tagging rule when a user provides tag “A” to the data file will be described. 
     As illustrated in  FIG. 6 , in step  100  (S 100 ), the rule updating unit  510  detects that a tag is provided to the data file by the tagging operation of the user. Specifically, as illustrated in  FIG. 7 , the user selects a tag or inputs a new tag name on the tagging operation screen, and performs a tagging operation (providing a tag “A”) on the data file, and the rule updating unit  510  detects the tagging operation by the user. 
     In step  105  (S 105 ), the collation unit  504  searches the tagging rule DB  600  for the presence or absence of a tagging rule of tag “A”. When the tagging rule exists, the collation unit  504  proceeds to S 135 , and when the tagging rule does not exist, the collation unit  504  proceeds to S 110 . 
     In step  110  (S 110 ), when there are two or more data files to which the tag “A” has been added by the user and which have been searched by the collation unit  504 , the collation unit  504  proceeds to S 115 . When there is only one data file to which the tag “A” is provided by the user, the rule updating unit  510  terminates the process of registering and updating the tagging rule (S 10 ). If there is only one data file to which the tag “A” is provided, a common feature in the data file to which the same tag “A” is provided cannot be extracted, and thus the tagging rule is not generated. 
     In step  115  (S 115 ), the common feature extracting unit  502  extracts features of the data file to which the tag “A” is provided. Specifically, the common feature extracting unit  502  extracts at least one of a character string, a date, an image size, and the number of colors used for an image of a data file. 
     In step  120  (S 120 ), when the common feature extracting unit  502  extracts the features of all the data files to which the tag “A” is provided, the process of registering and updating the tagging rule (S 10 ) proceeds to S 125 , and when the features of all the data files are not extracted, the process of registering and updating the tagging rule (S 10 ) proceeds to S 115 . 
     In step  125  (S 125 ), the common feature extracting unit  502  extracts a feature common to all the data files to which the tag “A” is provided as a “condition candidate”. 
     In step  130  (S 130 ), the score calculating unit  506  calculates scores of the appearance frequency, the closeness, the appearance position, and the uniqueness of each “condition candidate”, and a total score. The rule updating unit  510  selects a “condition candidate” in which a total score is high and in which each score is greater than or equal to a threshold value as a “condition”, generates a tagging rule of tag “A”, and registers the tagging rule in tagging rule DB  600 . 
     In step  135  (S 135 ), the collation unit  504  acquires the tagging rule of tag “A”. 
     In step  140  (S 140 ), the common feature extracting unit  502  extracts a feature of a data file to which a tag “A” is provided by the user. Specifically, the common feature extracting unit  502  acquires at least one of a character string, a date, an image size, and the number of colors used for an image of a data file. 
     In step  145  (S 145 ), the rule updating unit  510  deletes the condition not corresponding to the feature extracted by common feature extracting unit  502  in S 140  from the “condition” of the tagging rule acquired by the collation unit  504  in S 135 . Furthermore, in S 135 , the score calculating unit  506  recalculates the score of each “condition candidate” acquired in S 140  including the “condition candidate” of the tagging rule acquired by the collation unit  504 . In a case where the fixed condition is set by user customization, a condition candidate for which the fixed condition is set is selected as the “condition” regardless of the value of the score. Furthermore, the rule updating unit  510  additionally selects, as a “condition”, a condition candidate in which a total score is high and in which each score is greater than or equal to a threshold value from the other condition candidates. 
     In step  150  (S 150 ), the rule updating unit  510  replaces the “condition” of the tagging rule of the tag “A” with the selected new “condition” and updates the tagging rule. A tagging rule with a higher matching rate can be generated by replacing with a new “condition”. 
     Next, customization of the tagging rule by the user will be described. 
     The user can call out a customized screen of the tagging rule at an arbitrary timing to check and customize the tagging rule. Specifically, as illustrated in  FIG. 8A , the rule display unit  514  displays a “check tagging rule” menu from the tag “invoice”, and displays a customized screen of the tagging rule by the user&#39;s selection. Furthermore, as illustrated in  FIG. 8B , the rule display unit  514  accepts customization such as addition, deletion, and change of date of a keyword associated with a tag according to the operation of the user. Furthermore, the fixed condition setting unit  512  sets the “condition” associated with the tag as a fixed condition to be fixed according to the operation of the user. The “condition” set as the fixed condition is always held as the “condition” without being removed when the rule is updated by the tagging operation of the user. 
     Furthermore, as illustrated in  FIGS. 9A and 9B , the rule display unit  514  calls out and displays a customized screen of the tagging rule from the tag list which is the search result of the tag when the tag is proposed to the user. As described above, since the user can check the tagging rule and modify the tagging rule as necessary, even a tagging rule that cannot be handled by updating the tagging rule by the file management device  5  can be generated. 
       FIG. 10  is a flowchart illustrating the tagging and tag proposing process (S 20 ) by the file management device  5 . 
     As illustrated in  FIG. 10 , in step  200  (S 200 ), the acquisition unit  500  acquires image data of a document scanned by the scanner  3 . The common feature extracting unit  502  acquires the data file in which the OCR processing is performed on the image data acquired by acquisition unit  500 . The common feature extracting unit  502  extracts at least one of a character string, a date, an image size, and the number of colors used for an image of a data file as a feature. 
     In step  205  (S 205 ), the collation unit  504  collates the feature of the data file with the tagging rule stored in the tagging rule DB  600 . 
     In step  210  (S 210 ), the collation unit  504  proceeds to S 215  when the feature of the data file is collated with all the tagging rules, and proceeds to S 205  when the feature of the data file is not collated with all the tagging rules. 
     In step  215  (S 215 ), the collation unit  504  selects the tagging rule having the highest matching rate with the feature of the data file as a result of the collation. 
     In step  220  (S 220 ), when the matching rate of the tagging rules selected in S 215  is 100%, the process proceeds to S 225 , and when the matching rate is not 100%, the process proceeds to S 235 . 
     In step  225  (S 225 ), the tag providing unit  508  automatically provides the tag of the tagging rule with the matching rate of 100% to the data file. 
     In step  230  (S 230 ), the rule updating unit  510  updates and registers the tagging rule. Specifically, the condition that does not correspond to the feature extracted by the common feature extracting unit  502  is deleted from the tagging rules selected in S 215 . Furthermore, the “condition” is selected based on the score of each condition candidate, the fixed condition, and other condition candidates, and the “condition” of the tagging rule is replaced with the selected new “condition” and registered in the tagging rule DB  600 . 
     In step  235  (S 235 ), the tag providing unit  508  proceeds to S 240  when the tagging rule selected in S 215  and the feature of the data file have a matching rate of greater than or equal to 50% and less than 99% (similar), and terminates the process without providing a tag when the matching rate is less than or equal to 49%. 
     In step  240  (S 240 ), the tag providing unit  508  proposes providing the tag of the tagging rule determined to be similar to the data file, and asks the user to decide whether or not to provide the tag. 
       FIG. 11  is a flowchart illustrating a process of updating a tagging rule in accordance with a response of the user to a tagging proposal (S 30 ). In  FIG. 11 , a case where the file management device  5  proposes the provision of the tag “AAA” to the user will be described. 
     As illustrated in  FIG. 11 , in step  300  (S 300 ), the tag providing unit  508  proposes the provision of a tag “AAA” to the user as illustrated in  FIG. 12 . Specifically, the tag providing unit  508  presents provision of a tag “AAA”, no provision of a tag, and provision of another tag as the response operation of the user. 
     In step  305  (S 305 ), in a case where the user decides that the tag “AAA” is valid in response to the tag proposal by the tag providing unit  508 , the process proceeds to S 310 , and in a case where the user does not decide that the tag “AAA” is valid, the process proceeds to S 320 . 
     In step  310  (S 310 ), the tag providing unit  508  provides a tag “AAA” to a data file. 
     In step  315  (S 315 ), the rule updating unit  510  updates and registers the tagging rule of the tag “AAA”. Specifically, the rule updating unit  510  selects the “condition” such that a matching rate between the feature of the data file and the tagging rule of the tag “AAA” becomes 100%, and replaces the “condition” of the tagging rule of the existing “AAA” with the “condition”. Instead of replacing the “condition”, the rule updating unit  510  may increase the matching rate by partially deleting the “condition” (for example, a condition is relieved such that a character string satisfies a condition when two characters match from when three characters match). 
     In a case where the user has selected providing a tag different from “AAA” in step  320  (S 320 ), here, the process proceeds to S 325  when the user selects to provide the tag “BBB”, and otherwise, the process proceeds to S 340 . 
     In step  325  (S 325 ), the tag providing unit  508  provides a tag “BBB” to a data file. 
     In step  330  (S 330 ), when the user selects “provide tag “BBB””, the rule updating unit  510  updates the tagging rule of the tag “AAA” so that a matching rate between the feature of the data file and the tagging rule of the tag “AAA” becomes less than or equal to 49%. Specifically, the rule updating unit  510  selects the “condition” such that a matching rate between the feature of the data file and the tagging rule of the tag “AAA” becomes less than or equal to 49%. Furthermore, the rule updating unit  510  replaces the selected “condition” with the “condition” of the tagging rule of the existing “AAA”. This prevents the feature of the data file and the tagging rule of the tag “AAA” from being determined to be similar. In addition, instead of “replacing” the condition, the rule updating unit  510  may add the “condition” (strengthening the condition) to lower the matching rate. 
     In step  335  (S 335 ), the rule updating unit  510  updates the tagging rule of the tag “BBB” so that a matching rate between the feature of the data file and the tagging rule of the tag “BBB” becomes 100%. Specifically, the rule updating unit  510  selects the “condition” such that a matching rate between the feature of the data file and the tagging rule of the tag “BBB” becomes 100%. Furthermore, the rule updating unit  510  replaces the selected “condition” with the “condition” of the tagging rule of the existing “BBB”. Accordingly, it is determined that the feature of the data file matches the tagging rule of the tag “BBB”. In addition, instead of “replacing” the condition, the rule updating unit  510  may partially delete the “condition” (relieving the condition) to raise the matching rate. 
     In step  340  (S 340 ), when the user selects “not provide tag “AAA””, the rule updating unit  510  updates the tagging rule of the tag “AAA” so that a matching rate between the feature of the data file and the tagging rule of the tag “AAA” becomes less than or equal to 49%. More specifically, the rule updating unit  510  selects the “condition” such that a matching rate between the feature of the data file and the tagging rule of the tag “AAA” becomes less than or equal to 49%. Then, the rule updating unit  510  then replaces the selected “condition” with the “condition” of the tagging rule of “AAA”. This prevents the feature of the data file and the tagging rule of the tag “AAA” from being determined to be similar. In addition, instead of “replacing” the condition, the rule updating unit  510  may add the “condition” (strengthening the condition) to lower the matching rate. 
     In step  345  (S 345 ), the rule updating unit  510  registers the replaced “condition” in the tagging rule DB  600  as a condition of the tagging rule. 
     Next, an update example of the tagging rule in a case where the existing tag “claim (2018)” provided to the document A and the document B is provided to the newly tagging document C will be described. 
       FIG. 13A  is a diagram illustrating a tagging rule of “claim (2018)” and features of the document C, and illustrates keywords, document dates, and sizes of the document A, the document B, and the document C. As illustrated in  FIG. 13A , the document C does not include character strings “below” and “Tokyo” as in the documents A and B. 
       FIG. 13B  is a table illustrating scores of keywords of the condition candidates. 
       FIG. 13C  illustrates an update example of the tagging rule data. 
     The rule updating unit  510  selects a keyword to be adopted as the “condition” based on the score of the “condition candidate” included in the document C. Specifically, as illustrated in  FIG. 13B , the appearance frequencies of “below” and “Tokyo” calculated by the score calculating unit  506  decrease from “10” to “7”, and the appearance positions of “claim” and “tax amount” are added. As a result, the total score of “below” and “Tokyo” decreases, and the total score of “claim” and “tax amount” increases. Therefore, as illustrated in  FIG. 13C , the rule updating unit  510  updates the tagging rule generated based on the documents A and B to the tagging rule for providing a tag “claim (2018)” to a data file having “claim”, “amount”, “transfer”, “tax amount”, and “due date” as keywords, “2018” as document date, and “A4” as size. 
     Next, an update example of the tagging rule in a case where the tagging rule with the matching rate of 100% cannot be generated with only one condition will be described. Specifically, a case where the user provides an existing tag “claim” to the newly tagging document D will be described. 
       FIG. 14A  is a diagram illustrating a tagging rule of “claim” and features of the document D, and illustrates keywords and document dates of the document A, the document B, the document C, and the document D. As illustrated in  FIG. 14A , the document D does not include the character string “claim” as in the documents A to C, and the documents A to C and the newly tagging document D do not have a feature of a common data file. That is, the tag “claim” cannot be provided to the document D only by the tagging rule of the existing tag “claim” of No.  1  in  FIG. 14C . 
       FIG. 14B  is a table illustrating scores of keywords of the condition candidates. 
       FIG. 14C  illustrates an update example of the tagging rule data. 
     As illustrated in  FIGS. 14B and 14C , the score calculating unit  506  recalculates the score of the keyword of the “condition candidate”, and the rule updating unit  510  selects the “payee” and the “payment due date” having a high total score as the “condition” so that the document D corresponds to the tag “claim”, and adds the same as the tagging rule of the tag “claim” in addition to the tagging rule (No.  1 ) before update. Therefore, the rule updating unit  510  registers the conditions “No.  1 ” and “No.  2 ” as the tagging rule of the tag “claim”. Accordingly, the tag “claim” is provided when the condition of the tagging rule corresponds to “No.  1 ” or “No.  2 ”. 
     Next, an update example of the tagging rule in a case where the user refuses the proposal after the tagging is proposed will be described. Specifically, a case where the user refuses the proposal of the existing tag “AA company_claim” for the newly tagging document G which is a claim of BB company will be described. 
       FIG. 15A  is a diagram illustrating the tagging rule of “AA company_claim” and the feature of the newly tagging document G which is the claim of the BB company,  FIG. 15B  is a diagram illustrating the tagging rule of “∘∘ company_claim”,  FIG. 15C  is a table illustrating the scores of the keywords of the condition candidates, and  FIG. 15D  is an update example of the tagging rule data. 
     In the tagging rule of “∘∘ company_claim” illustrated in  FIG. 15B , a proposal to provide the tag “AA company_claim” also to the claim of the BB company is made. 
     Therefore, as illustrated in  FIG. 15A , the score calculating unit  506  compares the feature of the document G of which tagging is refused with the “condition candidate” of the tagging rule of the tag “AA company_claim”. If there is a “condition candidate” not included in the features of the document G among the “condition candidates” of the tagging rule of the tag “AA company_claim”, the score calculating unit  506  adds a score of uniqueness of such “condition candidate”. Specifically, as illustrated in  FIG. 15C , the score calculating unit  506  provides a uniqueness score to “AA company” which is a condition candidate of a keyword included in the document E and the document F but not included in the document G. As a result of recalculation of the score by the score calculating unit  506 , as illustrated in  FIG. 15D , the rule updating unit  510  updates the tagging rule to a tagging rule having the tag name “AA company_claim” and the keywords ““AA company”, “claim”, “payee”, “payment due date”, and “claimed amount””. As a result, the tag providing unit  508  no longer proposes the tag “AA company_claim” to the document G which is the claim of the BB company. 
     As described above, according to the file management device  5 , the user can check the tagging rule and modify and customize the tagging rule as necessary by expressing the tagging rule in a format (character string) that a person can understand. Thus, understanding and reliability of the tag automatically provided to the data file are deepened, and promotion in using the tag can be expected. Furthermore, a tag can be automatically provided to a data file acquired from the scanner  3  without user intervention based on a feature of the data file and a tagging rule. Then, since the tagging rule is updated based on the matching rate between the document to be tagged and the tagging rule, a more accurate tagging rule is established by use. 
     In the embodiment described above, the file management device  5  provides the tag to the image data read by the scanner  3 , but this is not the sole case, and the scanner  3  may have the function of the file management device  5  and read the image data, and provide the tag to the data file. Furthermore, the user terminal  7  may have the function of the file management device  5 , and the user terminal  7  may provide a tag to a data file. 
     REFERENCE SIGNS LIST 
     
         
           1  file management system 
           3  scanner 
           5  file management device 
           50  file management program 
           500  acquisition unit 
           502  common feature extracting unit 
           504  collation unit 
           506  score calculating unit 
           508  tag providing unit 
           510  rule updating unit 
           512  fixed condition setting unit 
           514  rule display unit 
           600  tagging rule database