JP5050724B2 - Document monitoring program, document monitoring apparatus, and document monitoring method - Google Patents

Description

  The present invention relates to a document monitoring program, a document monitoring apparatus, and a document monitoring method for monitoring a document to be transmitted.

  In recent years, user participation media such as blogs, SNSs (Social Networking Services), bulletin boards, and the like have emerged on the Internet. These are called CGM (Consumer Generated Media) and attract attention as a place where general users can freely express their opinions and impressions.

As a related art related to the present invention, there is a publication information deletion request agency system that monitors published information and requests deletion of an article when there is an article that hits a registered keyword (for example, Patent Document 1). In addition, there is an information sharing system that selects and introduces persons with abundant knowledge with respect to information to be known (see, for example, Patent Document 2).
JP 2002-109085 A JP 2004-220177 A

  However, because of the ease with which anyone can easily send information, cases where personal information is posted and posted are problematic, especially for children. On the other hand, a service has been launched that circulates and monitors blogs, SNSs, bulletin boards, etc., finds and notifies inappropriate information, and deletes it. However, since most of these services are manually patroled and monitored, there are limits to the number of targets and monitoring intervals.

  Moreover, since the technique of Patent Document 1 automatically performs monitoring to a deletion request, it is possible to monitor over a wider range and in a shorter cycle than manual operation. However, there are problems in that only articles already published on the Internet can be monitored, and only articles that completely match the registered keywords can be found.

  SUMMARY An advantage of some aspects of the invention is to provide a document monitoring program, a document monitoring apparatus, and a document monitoring method for preventing disclosure of information related to an individual.

  In order to solve the above-described problem, one aspect of the present invention is a document monitoring program that causes a computer to monitor a document created by a user, the first character string being a character string representing the user's address. Obtaining a second character string that is a character string representing an address indicated by the noun by extracting a noun from the document created by the user and searching for the noun in a database; and the first character string And the second character string are calculated from the degree of risk, and the computer is caused to display the second character string based on the degree of risk.

  According to another aspect of the present invention, there is provided a document monitoring apparatus that monitors a document created by a user, a first acquisition unit that acquires a first character string that is a character string representing an address of the user, the user An extraction unit that extracts a noun from the document created by the above, a second acquisition unit that acquires a second character string that is a character string representing an address indicated by the noun by searching for the noun in a database, and the second A calculation unit that calculates a risk level from a similarity between one character string and the second character string, and a display unit that displays the second character string based on the risk level.

  Another aspect of the present invention is a document monitoring method for monitoring a document created by a user, wherein the first character string that is a character string representing the address of the user is acquired and created by the user. By extracting a noun from a document and searching for the noun in a database, a second character string that is a character string representing an address indicated by the noun is obtained, and the similarity between the first character string and the second character string The degree of danger is calculated from the degree, and the display relating to the second character string is performed based on the degree of danger.

  According to the present invention, disclosure of information related to an individual can be prevented.

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

Embodiment 1 FIG.
In the following embodiment, an example will be described in which the document monitoring apparatus of the present invention is applied to a posting system for posting CGM such as a blog, an SNS, and a bulletin board.

  First, the configuration of the document monitoring apparatus according to the present embodiment will be described.

  FIG. 1 is a block diagram showing an example of the configuration of the document monitoring apparatus according to the present embodiment. This document monitoring apparatus includes a user information registration unit 11, a user information DB (Database) 12, a user authentication unit 13, a user information acquisition unit 14, a document reception unit 21, a document DB 22, a keyword extraction unit 24, an extraction keyword DB 26, a latitude and longitude. An acquisition unit 31, a latitude / longitude DB 32, a distance calculation unit 33, a danger keyword DB 34, a determination unit 35, a warning unit 42, a correction unit 43, and a document transmission unit 44 are provided. The document monitoring apparatus is connected to a user terminal 1 for creating and posting a document by a user and a server 2 for publishing posted articles via a network. This document monitoring apparatus monitors a document posted from the user terminal 1 to the server 2 before posting.

  Information about the user who makes the posting is registered in advance as user information. The user information registration unit 11 receives user information such as the user's address and name input by the user, and registers the user information in the user information DB 12. The latitude / longitude DB 32 stores a place name (place name), which is a noun indicating a place such as a park, a school, or a store, and the latitude and longitude of the place in association with each other.

  Next, the operation of the document monitoring apparatus according to this embodiment will be described.

  FIG. 2 is a flowchart showing an example of the operation of the document monitoring apparatus according to the present embodiment. First, when receiving an authentication request from the user terminal 1, the user authentication unit 13 authenticates a user who makes a posting and acquires a user ID (S11). Hereinafter, this user is referred to as a target user. Next, the user information acquisition unit 14 acquires the user information of the target user from the user information DB 12 based on the user ID, and acquires the user address that is the address of the target user from the user information (S12).

  Next, the user information acquisition unit 14 searches the latitude / longitude DB 32 for the user address, and acquires the latitude and longitude of the user address (S13). Next, the document receiving unit 21 receives a document transmitted from the user terminal 1 for posting and registers it in the document DB 22 (S16). Hereinafter, this document is the target document. Next, the keyword extracting unit 24 extracts a noun from the target document by performing morphological analysis of the received document, and registers it in the extracted keyword DB 26 (S17).

  FIG. 3 is a table showing an example of the contents of the latitude / longitude DB according to the present embodiment. The latitude / longitude DB 32 is created in advance based on map information, and stores location name, latitude, and longitude information for each location. The place name also includes an address character string such as a prefecture name, a municipality name, and a street address. In the latitude / longitude DB 32, for example, locations throughout Japan are registered.

  Next, keyword determination processing (processing S22 to S33) is performed.

  First, the latitude / longitude acquisition unit 31 selects one of the keywords stored in the extracted keyword DB 26 as a selected keyword (S22). Next, the latitude / longitude acquisition unit 31 searches the latitude / longitude DB 32 for the selected keyword and determines whether or not a hit has been made (S23). Note that the latitude / longitude acquisition unit 31 may search for the selected keyword in the latitude / longitude DB 32 only in the vicinity of the user address.

  If there is no hit (S23, N), it is determined that the selected keyword is not a place name, and the process returns to process S22 to process the next selected keyword.

  On the other hand, when a hit occurs (S23, Y), the latitude / longitude acquisition unit 31 determines that the selected keyword is a place name, and acquires the latitude and longitude corresponding to the place name (S25).

  Next, the distance calculation unit 33 calculates the distance between the user address and the selected keyword from the latitude and longitude of the user address and the latitude and longitude of the selected keyword (S31). Next, the distance calculation unit 33 determines whether or not the distance between the user address and the selected keyword is equal to or less than a distance threshold (S32). Here, the distance threshold is, for example, 5 km.

  When the distance between the user address and the selected keyword is not less than the predetermined distance (S32, N), the process proceeds to S41. On the other hand, when the distance between the user address and the selected keyword is equal to or less than the predetermined distance (S32, Y), the distance calculation unit 33 sets the selected keyword as a risk keyword and stores the risk keyword, the user ID of the target user, and the like in the risk keyword DB 34. Register (S33) and proceed to step S41. By this process, a keyword representing a place close to the user address can be detected.

  FIG. 4 is a table showing an example of the contents of the dangerous keyword DB according to the present embodiment. The dangerous keyword DB 34 stores an entry for each user ID and each dangerous keyword. Each entry stores a dangerous keyword location name, user ID, latitude and longitude corresponding to the location name, and the distance from the posted user's user address to the location of the dangerous keyword.

  Next, the latitude / longitude acquisition unit 31 determines whether or not the keyword determination process has been completed for all keywords in the target document (S41). If the keyword determination process has not ended (S41, N), this flow returns to process S22. On the other hand, when the keyword determination process is completed for all keywords in the target document (S41, Y), the determination unit 35 counts the number of dangerous keywords of the user in the dangerous keyword DB 34 (S42), and the number of dangerous keywords is dangerous. It is determined whether or not the keyword count threshold value is exceeded (S43). Here, the threshold number of dangerous keywords is, for example, five.

  When the target user has posted a document in the past, since the past risk keywords are also stored in the risk keyword DB 34, the determination in step S43 is performed for all the risk keywords up to the present.

  If the number of dangerous keywords is not equal to or greater than the threshold number of dangerous keywords (S43, N), the document transmission unit 44 transmits the target document to the server 2 (S59), and this flow ends. On the other hand, when the number of dangerous keywords is equal to or greater than the threshold number of dangerous keywords (S43, Y), the warning unit 42 performs a dangerous keyword display process (S56). The correction unit 43 performs a correction process for correcting the dangerous keyword in the target document, and stores the corrected target document in the document DB 22 (S57). In the correction process, the correction unit 43 replaces the dangerous keyword in the target document with another character (abbreviated character). Next, the correcting unit 43 deletes the dangerous keyword entry deleted from the target document by the correcting process from the dangerous keyword DB 34 (S58).

  Next, the document transmission unit 44 transmits the target document stored in the document DB 22 to the user terminal 1 and the server 2 (S59), and this flow ends. The server 2 publishes the target document received from the document monitoring apparatus.

  Next, the dangerous keyword display process will be described.

  The warning unit 42 displays information related to the risk keyword on the user terminal 1. FIG. 5 is a screen showing an example of display by the dangerous keyword display process according to the present embodiment. In the danger keyword display process, the warning unit 42 displays a circle with the distance threshold as a radius centered on the user address. Further, the warning unit 42 displays the relative position of the dangerous keyword with respect to the user address by using the latitude and longitude of the user address and the latitude and longitude of the dangerous keyword, and displays the dangerous keyword at the relative position. In the dangerous keyword display process, only the dangerous keyword may be displayed or a warning text may be displayed. In the correction process, the target document retransmitted from the user according to the display by the warning unit 42 may be used as the correction result.

  Note that the document monitoring apparatus may include one of the warning unit 42 and the correction unit 43.

  According to the present embodiment, based on latitude and longitude, information related to the user address is detected by detecting a keyword that is likely to identify the user address from the document to be posted and performing warning or correction. Can be prevented from being disclosed. Further, by accumulating dangerous keywords for each user, it is possible to determine the possibility that the user address is specified from a plurality of documents.

Embodiment 2. FIG.
First, the configuration of the document monitoring apparatus according to the present embodiment will be described.

  FIG. 6 is a block diagram showing an example of the configuration of the document monitoring apparatus according to the present embodiment. In this figure, the same reference numerals as those in FIG. 1 denote the same or corresponding parts as those in FIG. 1, and the description thereof is omitted here. Compared with FIG. 1, this figure replaces the latitude / longitude acquisition unit 31, the latitude / longitude DB 32, the distance calculation unit 33, the danger keyword DB 34, and the determination unit 35 with an address character string acquisition unit 51, an address character string DB 52 (address database). ), A risk calculation unit 53, a risk DB 54, and a determination unit 55.

  Next, the operation of the document monitoring apparatus according to this embodiment will be described.

  FIG. 7 is a flowchart showing an example of the operation of the document monitoring apparatus according to the present embodiment. In this figure, the same reference numerals as those in FIG. 2 denote the same or corresponding parts as those in FIG. 2, and the description thereof will be omitted here. First, similarly to the first embodiment, processes S11 and S12 are executed.

  Next, the user information acquisition unit 14 acquires a user address character string (first character string) that is a character string of the target user's address from the user information (S14), performs morphological analysis of the user address character string, and The address character string is divided into blocks (S15).

  FIG. 8 is a diagram showing an example of division of the user address character string according to the present embodiment. Each block is a unit such as a prefecture name, a municipality name, or a ward name.

  Next, the document receiving unit 21 receives the target document transmitted from the user terminal 1 for posting (S16). Next, the keyword extraction unit 24 extracts a noun from the target document by performing morphological analysis of the target document, and registers it in the extracted keyword DB 26 (S17). Next, the address character string acquisition unit 51 reads out the keyword with the highest risk level from the risk DB 54 and sets it as the maximum risk keyword. The address string corresponding to the maximum risk keyword is set as the maximum risk level. Is the maximum risk address character string (S18). Here, the risk level of a certain keyword is the similarity between the address character string corresponding to the keyword and the user address character string, and a specific calculation method will be described later.

  FIG. 9 is a table showing an example of the contents of the risk DB according to the present embodiment. The risk DB 54 stores a place name, an address character string, and a risk for each keyword and each user.

  Next, keyword determination processing (processing S62 to S68) is performed.

  First, the address character string acquisition unit 51 selects one of the keywords stored in the extracted keyword DB 26 as a selected keyword (S62). Next, the address character string acquisition unit 51 searches the address character string DB 52 for the selected keyword and determines whether or not the selected keyword has been hit (S63).

  FIG. 10 is a table showing an example of the contents of the address character string DB according to the present embodiment. The address character string DB 52 is created in advance based on map information, and stores a place name and an address character string for each place. In the address character string DB 52, for example, locations throughout Japan are registered.

  When the selected keyword is hit (S63, Y), the risk calculating unit 53 calculates the risk of the selected keyword by the first risk calculating process (S64), and when the selected keyword is not hit (S63, N). ), The risk level calculation unit 53 calculates the risk level of the selected keyword by the second risk level calculation process (S65). Next, the risk level calculation unit 53 registers the selected keyword and the risk level in the risk level DB 54 (S66). Next, the risk level calculation unit 53 determines whether or not the risk level of the selected keyword is greater than the maximum risk level (S67).

  When the risk level of the selected keyword is equal to or lower than the maximum risk level (S67, N), the risk level calculation unit 53 proceeds to process S71. On the other hand, when the risk level of the selected keyword is greater than the maximum risk level (S67, Y), the risk level calculation unit 53 updates the maximum risk level keyword to the selected keyword (S68), and proceeds to processing S71.

  Next, the address character string acquisition unit 51 determines whether or not the keyword determination processing has been completed for all keywords in the target document (S71). If the keyword determination process has not ended (S71, N), this flow returns to process S62. On the other hand, when the keyword determination processing is completed for all keywords in the target document (S71, Y), the determination unit 55 sets the keywords whose risk level is equal to or higher than the risk threshold value in the risk level DB 54 as risk keywords. It is determined whether a dangerous keyword exists in the document (S73). Here, the risk threshold is 80%, for example.

  When the dangerous keyword does not exist (S73, N), the document transmission unit 44 transmits the target document stored in the document DB 22 to the server 2 (S79), and this flow ends. On the other hand, when a dangerous keyword exists (S73, Y), the warning unit 42 performs a dangerous keyword display process similar to that of the first embodiment (S76). The correction unit 43 performs the same correction process as in the first embodiment and stores the target document in the document DB 22 (S77). Next, the correcting unit 43 deletes the entry of the dangerous keyword deleted from the target document by the correcting process from the risk DB 54 (S78).

  Next, the document transmission unit 44 transmits the target document stored in the document DB 22 to the user terminal 1 and the server 2 (S79), and this flow ends. The server 2 publishes the target document received from the document monitoring apparatus.

  Next, the first risk level calculation process will be described.

  FIG. 11 is a flowchart showing an example of the operation of the first risk degree calculation process according to the present embodiment. First, the address character string acquisition unit 51 acquires an address character string corresponding to a place name that matches the selected keyword from the address character string DB 52 and sets it as a selected address character string (second character string) (S81). Note that the address character string acquisition unit 51 may search for the selected keyword only in the vicinity of the user address. Next, the risk level calculation unit 53 sets N as the larger one of the length of the selected address character string and the length of the maximum risk address character string (S96). Next, the selected address character string is compared with the maximum risk address character string, and the length of the character string that is continuously matched is set to M (S97). Next, the risk level calculation unit 53 sets (M / N × 100) as the risk level [%] of the selected keyword (S98), and this flow ends. The higher the risk of the selected keyword, the closer to the user address or the easier it is to identify the user address.

  According to the first risk level calculation process, the risk level can be increased as the user address character string and the address character string corresponding to the place name of the selected keyword are more similar.

  Next, the second risk level calculation process will be described.

  FIG. 12 is a flowchart showing an example of the operation of the second risk level calculation process according to the present embodiment. First, the risk level calculation unit 53 adds a block next to the maximum risk level address character string among the address character string blocks of the user address to the maximum risk level address character string and adds a search address character string (third character string). (S82). Next, the risk level calculation unit 53 searches the content database (index) on the Internet for content including both the selected keyword and the search address character string, and there is content including both the selected keyword and the search address character string. It is determined whether or not to perform (S83).

  When there is no content including both the selected keyword and the search address character string (S83, N), the process proceeds to S95. On the other hand, when there is content including both the selected keyword and the search address character string (S83, Y), the next block of the search address character string is selected as the search address character string from among the address character string blocks of the user address. In addition, a new search address character string is set (S84), and the process returns to step S83.

  Next, an address character string obtained by deleting the last block from the search address character string is set as a selected address character string (second character string) (S95). Next, processes S96 to S98 similar to the first risk degree calculation process are executed, and this flow ends.

  FIG. 13 is a diagram showing an example of information related to the second risk degree calculation process according to the present embodiment. Here, an example of the address of the maximum risk address character string, the selected keyword, and the selected keyword is shown. FIG. 14 is a diagram showing an example of the second risk degree calculation process according to the present embodiment.

  In the first search, a search is performed with the selected keyword and a search address character string obtained by adding one block to the maximum risk address character string, and the search address character string is included in the address of the selected keyword. To hit. Similarly, in the second search, a search is performed using the selected keyword and a search address character string obtained by adding two blocks to the maximum risk address character string, and the search address character string is included in the address of the selected keyword. Hits the site about the selected keyword. In the third search, a search is performed based on the selected keyword and the search address character string obtained by adding 3 blocks to the maximum risk address character string, and the search address character string is not included in the address of the selected keyword. To do. Here, the selected address character string is obtained by deleting the last one block from the search address character string.

  According to the second risk level calculation process, an address character string corresponding to the selected keyword is generated based on contents on the Internet even if an address character string corresponding to the place name of the selected keyword is not obtained from the address character string DB 52. And the degree of risk can be calculated.

  Note that all risk levels may be calculated by the second risk level calculation process without using the address character string DB 52.

  According to this embodiment, based on an address character string, a keyword that is likely to identify a user address is detected from a document that the user intends to post, and a warning or correction is performed. The disclosure of related information can be prevented.

  The first acquisition unit corresponds to the user information acquisition unit in the embodiment. The extraction unit corresponds to the keyword extraction unit in the embodiment. The second acquisition unit and the calculation unit correspond to the risk calculation unit in the embodiment. The display unit corresponds to the warning unit, the correction unit, and the document transmission unit in the embodiment.

  Furthermore, it is possible to provide a program for executing the above steps in a computer constituting the document monitoring apparatus as a document monitoring program. By storing the above-described program in a computer-readable recording medium, the computer constituting the document monitoring apparatus can be executed. Here, examples of the recording medium readable by the computer include an internal storage device such as a ROM and a RAM, a portable storage such as a CD-ROM, a flexible disk, a DVD disk, a magneto-optical disk, and an IC card. It includes a medium, a database holding a computer program, another computer and its database, and a transmission medium on a line.

(Supplementary Note 1) A document monitoring program for causing a computer to monitor a document created by a user,
Obtaining a first character string that is a character string representing the address of the user;
Extracting nouns from the document created by the user,
By searching for the noun in the database, a second character string that is a character string representing the address indicated by the noun is obtained,
Calculating the degree of risk from the similarity between the first character string and the second character string;
A document monitoring program for causing a computer to execute display related to the second character string based on the degree of risk.
(Appendix 2) In the document monitoring program described in Appendix 1,
A character string included in the first character string is set as a third character string, a content including both the third character string and the noun is searched in a content database on the Internet, and the content is found when the content exists. A document monitoring program that uses three character strings as the second character string.
(Appendix 3) In the document monitoring program described in Appendix 2,
A document monitoring program for generating the third character string using a second character string having the highest similarity to the first character string.
(Appendix 4) In the document monitoring program described in Appendix 3,
A document monitoring program for dividing the first character string into a plurality of blocks and adding the block to the third character string to generate a new third character string.
(Appendix 5) In the document monitoring program described in Appendix 3,
The document monitoring program for generating the third character string by using the second character string having the highest similarity to the first character string among all the second character strings.
(Appendix 6) In the document monitoring program described in Appendix 1,
In an address database in which a place name and a character string indicating an address of the place name are associated with each other, a place name that matches the noun is searched. When a place name that matches the noun exists, a character string that indicates the address of the place name is A document monitoring program acquired from the database and used as the second character string.
(Appendix 7) In the document monitoring program described in Appendix 1,
In an address database that stores a place name and a character string indicating an address of the place name in association with each other, a place name that matches the noun is searched, and if there is no place name that matches the noun, the place name is included in the first character string. Document monitoring using a third character string as a character string, searching for contents including both the third character string and the noun on the Internet, and using the third character string as the second character string when the content exists program.
(Appendix 8) In the document monitoring program described in Appendix 1,
A document monitoring program that performs morphological analysis of a document created by the user and extracts nouns from the document.
(Appendix 9) In the document monitoring program described in Appendix 1,
A document monitoring program for calculating the similarity based on a length of a character string that continuously matches in the first character string and the second character string.
(Appendix 10) In the document monitoring program described in Appendix 1,
A document monitoring program for displaying a warning when a similarity between the first character string and the second character string satisfies a predetermined condition.
(Appendix 11) In the document monitoring program described in Appendix 1,
A document monitoring program for correcting a second character string in the document when a similarity between the first character string and the second character string satisfies a predetermined condition.
(Supplementary Note 12) A document monitoring program for causing a computer to monitor a document created by a user,
Obtain the user's address,
Extracting nouns from the document created by the user,
By retrieving the noun in the database, the position indicated by the noun is obtained,
Calculating the relevance between the user's address and the location;
A document monitoring program that causes a computer to execute display related to the noun based on the association.
(Supplementary note 13) In the document monitoring program described in supplementary note 12,
In a latitude / longitude database that stores the place name and the latitude and longitude of the place name in association with each other, search for a place name that matches the noun, and if a place name that matches the noun exists, A document monitoring program for calculating a distance from the place name to the user's address and displaying the noun when the distance satisfies a predetermined condition.
(Supplementary Note 14) A document monitoring apparatus that monitors a document created by a user,
A first acquisition unit that acquires a first character string that is a character string representing the address of the user;
An extractor for extracting nouns from the document created by the user;
A second acquisition unit that acquires a second character string that is a character string representing an address indicated by the noun by searching for the noun in a database;
A calculation unit for calculating a risk level from a similarity between the first character string and the second character string;
A display unit for displaying the second character string based on the degree of risk;
A document monitoring apparatus comprising:
(Supplementary Note 15) In the document monitoring apparatus according to Supplementary Note 14,
The second acquisition unit uses a character string included in the first character string as a third character string, searches a content database on the Internet for content including both the third character string and the noun, A document monitoring program that uses the third character string as the second character string when there is a file.
(Supplementary Note 16) In the document monitoring program described in Supplementary Note 15,
The second acquisition unit is a document monitoring program that generates the third character string using a second character string having a predetermined degree of similarity with the first character string.
(Supplementary note 17) In the document monitoring program according to supplementary note 16,
The second acquisition unit is a document monitoring program that divides the first character string into a plurality of blocks and adds the block to the third character string to generate a new third character string.
(Supplementary note 18) In the document monitoring program described in supplementary note 14,
In an address database in which a place name and a character string indicating an address of the place name are associated with each other, a place name that matches the noun is searched. When a place name that matches the noun exists, a character string that indicates the address of the place name is A document monitoring program acquired from the database and used as the second character string.
(Supplementary note 19) In the document monitoring program according to supplementary note 14,
In an address database that stores a place name and a character string indicating an address of the place name in association with each other, a place name that matches the noun is searched, and if there is no place name that matches the noun, it is included in the first character string. Document monitoring using a third character string as a character string, searching for contents including both the third character string and the noun on the Internet, and using the third character string as the second character string when the content exists program.
(Supplementary note 20) A document monitoring method for monitoring a document created by a user,
Obtaining a first character string that is a character string representing the address of the user;
Extracting nouns from the document created by the user,
By searching for the noun in the database, a second character string that is a character string representing the address indicated by the noun is obtained,
Calculating the degree of risk from the similarity between the first character string and the second character string;
A document monitoring method for performing display related to the second character string based on the risk level.

1 is a block diagram illustrating an example of a configuration of a document monitoring apparatus according to Embodiment 1. FIG. 6 is a flowchart illustrating an example of an operation of the document monitoring apparatus according to the first embodiment. 4 is a table showing an example of contents of a latitude / longitude DB according to the first embodiment. 4 is a table showing an example of contents of a danger keyword DB according to Embodiment 1. 6 is a screen showing an example of display by dangerous keyword display processing according to Embodiment 1. 6 is a block diagram illustrating an example of a configuration of a document monitoring apparatus according to Embodiment 2. FIG. 10 is a flowchart illustrating an example of an operation of the document monitoring apparatus according to the second embodiment. It is a figure which shows an example of the division | segmentation of the user address character string which concerns on Embodiment 2. FIG. 10 is a table showing an example of contents of a risk DB according to the second embodiment. It is a table | surface which shows an example of the content of the address character string DB which concerns on Embodiment 2. FIG. 10 is a flowchart illustrating an example of an operation of a first risk degree calculation process according to the second embodiment. 12 is a flowchart illustrating an example of an operation of a second risk degree calculation process according to the second embodiment. 10 is a diagram illustrating an example of information related to a second risk degree calculation process according to Embodiment 2. FIG. It is a figure which shows an example of the 2nd risk degree calculation process which concerns on Embodiment 2. FIG.

Explanation of symbols

  1 User terminal, 2 server, 11 User information registration unit, 12 User information DB, 13 User authentication unit, 14 User information acquisition unit, 21 Document reception unit, 22 Document DB, 24 Keyword extraction unit, 26 Extraction keyword DB, 31 Latitude Longitude acquisition unit, 32 latitude / longitude DB, 33 distance calculation unit, 34 danger keyword DB, 35 determination unit, 42 warning unit, 43 correction unit, 44 document transmission unit, 51 address character string acquisition unit, 52 address character string DB, 53 Risk level calculation unit, 54 Risk level DB, 55 determination unit.

Claims (7)

A document monitoring program for causing a computer to monitor a document created by a user,
Obtaining a first character string that is a character string representing the address of the user;
Extracting nouns from the document created by the user,
By searching for the noun in the database, a second character string that is a character string representing the address indicated by the noun is obtained,
Calculating the degree of risk from the similarity between the first character string and the second character string;
A document monitoring program for causing a computer to execute display related to the second character string based on the degree of risk. The document monitoring program according to claim 1,
A character string included in the first character string is set as a third character string, a content including both the third character string and the noun is searched in a content database on the Internet, and the content is found when the content exists. A document monitoring program that uses three character strings as the second character string. The document monitoring program according to claim 2,
A document monitoring program for generating the third character string using a second character string having the highest similarity to the first character string. The document monitoring program according to claim 2,
In an address database that stores a place name and a character string indicating an address of the place name in association with each other, a place name that matches the noun is searched, and if there is no place name that matches the noun, the place name is included in the first character string. Document monitoring using a third character string as a character string, searching for contents including both the third character string and the noun on the Internet, and using the third character string as the second character string when the content exists program. The document monitoring program according to any one of claims 1 to 4,
In an address database in which a place name and a character string indicating an address of the place name are associated with each other, a place name that matches the noun is searched. When a place name that matches the noun exists, a character string that indicates the address of the place name is A document monitoring program acquired from the database and used as the second character string. A document monitoring apparatus for monitoring a document created by a user,
A first acquisition unit that acquires a first character string that is a character string representing the address of the user;
An extractor for extracting nouns from the document created by the user;
A second acquisition unit that acquires a second character string that is a character string representing an address indicated by the noun by searching for the noun in a database;
A calculation unit for calculating a risk level from a similarity between the first character string and the second character string;
A display unit for displaying the second character string based on the previous risk level;
A document monitoring apparatus comprising: A document monitoring method for monitoring a document created by a user,
Obtaining a first character string that is a character string representing the address of the user;
Extracting nouns from the document created by the user,
By searching for the noun in the database, a second character string that is a character string representing the address indicated by the noun is obtained,
Calculating the degree of risk from the similarity between the first character string and the second character string;
A document monitoring method for performing display related to the second character string based on the risk level.

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