JP5535270B2 - Document component analysis apparatus and program - Google Patents

Description

  Embodiments described herein relate generally to a document component analysis apparatus and a program.

  In general, when a document (document) in which the contents of a project such as system development is described is created, the evaluator confirms the contents of the created document so that the document can be evaluated. It has been broken.

  In this case, the evaluator needs to read through all of the documents and check whether the documents conform to a predetermined standard or standard.

JP 2011-186762 A Japanese Patent Laid-Open No. 11-288414

  The evaluation of the document by the evaluator described above must be performed from the viewpoint of completeness (whether all the standards or standards are described) and the amount of description (whether there is a sufficient amount of description), and requires a lot of time. It becomes. Further, when there is a large amount of document description, it is necessary for the evaluator to spend more time in order to grasp all the contents of the document.

  Therefore, a problem to be solved by the present invention is to provide a document component analysis apparatus and program capable of supporting evaluation of a document by an evaluator.

  The document component analysis apparatus according to the embodiment includes viewpoint information storage means, document input means, identification means, determination means, generation means, and presentation means.

  The viewpoint information storage means associates a first character string representing an item to be described in the document as a predetermined reference or standard and a second character string representing an item more detailed than the first character string. Store.

  The document input means is a document composed of a plurality of components including a character string, and inputs a document in which the first character string stored in the viewpoint information storage means is designated.

  For each component constituting the input document, the specifying unit associates the specified first character string included in the component with the second character stored in the viewpoint information storage unit. Specify the number of columns.

  The determining unit determines, for each constituent element, a second character string representing the viewpoint of the constituent element based on the number of second character strings specified for each constituent element.

The generation unit arranges a partial document name indicating the partial document and the stored second character string on each axis, and as data corresponding to an intersection of the partial document name and the second character string, A first component matrix is generated in which data indicating the number of components for which the second character string is determined among a plurality of components constituting the partial document indicated by the partial document name .

  The presenting means presents the generated first component matrix.

The block diagram which shows the hardware constitutions of the document component analyzer which concerns on embodiment. FIG. 2 is a block diagram mainly showing a functional configuration of the document component analysis apparatus 30 shown in FIG. 1. The figure which shows an example of the data structure of the viewpoint information storage part 22 shown in FIG. The figure which shows an example of the data structure of the project information stored in the results storage part 23 shown in FIG. The figure which shows an example of the information which shows the area | region where each component matrix is stored. The figure which shows an example of the data structure of the evaluation information stored in the performance storage part 23 shown in FIG. 6 is a flowchart showing a processing procedure of the document component analysis apparatus 30 according to the present embodiment. FIG. 4 is a diagram illustrating an example of a data structure of a document input by a document input unit 31. The flowchart which shows the process sequence of the viewpoint (medium) component matrix production | generation process shown in FIG. The figure which shows an example of the data structure of the viewpoint (middle) component matrix produced | generated by the component matrix production | generation part 33. FIG. The flowchart which shows the process sequence of the total number component matrix production | generation process shown in FIG. The figure which shows an example of the data structure of the total number component matrix produced | generated by the component matrix production | generation part 33. FIG. The flowchart which shows the process sequence of the viewpoint (large) component matrix production | generation process shown in FIG. The figure which shows an example of the data structure of the viewpoint (large) component matrix produced | generated by the component matrix production | generation part 33. FIG. The flowchart which shows the process sequence of the automatic evaluation process shown in FIG.

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

  FIG. 1 is a block diagram showing a hardware configuration of the document component analysis apparatus according to the present embodiment. As shown in FIG. 1, the computer 10 is connected to an external storage device 20 such as a hard disk drive (HDD). The external storage device 20 stores a program 21 executed by the computer 10. The computer 10 and the external storage device 20 constitute a document component analysis device 30.

  FIG. 2 is a block diagram mainly showing a functional configuration of the document component analyzing apparatus 30 shown in FIG.

  As shown in FIG. 2, the document component analysis apparatus 30 includes a document input unit 31, a viewpoint (large) acquisition unit 32, a component matrix generation unit 33, a project information input unit 34, a similar project specification unit 35, an evaluation acquisition unit 36, A presentation unit 37 and an evaluation input unit 38 are included. In the present embodiment, these units 31 to 38 are realized by the computer 10 illustrated in FIG. 1 executing the program 21 stored in the external storage device 20. This program 21 can be stored in advance in a computer-readable storage medium and distributed. Further, this program 21 may be downloaded to the computer 10 via, for example, a network.

  In addition, the document component analysis device 30 includes a viewpoint information storage unit 22 and a performance storage unit 23. In the present embodiment, the viewpoint information storage unit 22 and the result storage unit 23 are stored in, for example, the external storage device 20.

  In the viewpoint information storage unit 22, viewpoints (large), viewpoints (medium), and viewpoints (small) are stored in advance in association with each other.

  The viewpoint (large) (first viewpoint) includes a character string (first character string) representing an item to be described in the document as a predetermined standard or standard. Hereinafter, a character string included in the viewpoint (large) is referred to as a term (large) for convenience.

  The viewpoint (medium) (second viewpoint) includes a character string (second character string) representing a more detailed item than the term (large) term associated with the viewpoint. Hereinafter, a character string included in the viewpoint (medium) is referred to as a term (medium) for convenience.

  The viewpoint (small) (third viewpoint) includes a character string (third character string) representing a more detailed item than the term (middle) term associated with the viewpoint. Hereinafter, a character string included in the viewpoint (small) is referred to as a viewpoint (small) term for convenience.

  The document input unit 31 inputs a document. A document input by the document input unit 31 includes a plurality of components including a character string (for example, a cell in which the character string is described). Further, in the document input by the document input unit 31, the above-mentioned viewpoint (large) term is specified. The document input by the document input unit 31 is a document in which the content of a project such as system development is described. A document input by the document input unit 31 is created by a system developer or the like.

  The viewpoint (large) acquisition unit 32 acquires the viewpoint (large) term specified in the document input by the document input unit 31.

  The component matrix generation unit 33 uses the viewpoint (medium) based on the information stored in the viewpoint information storage unit 22, the document input by the document input unit 31, and the viewpoint (large) term acquired by the viewpoint identification unit 32. ) Component matrix (first component matrix), total number component matrix (second component matrix) and viewpoint (large) component matrix (third component matrix). Although details will be described later, the viewpoint (medium) component matrix and the viewpoint (large) component matrix determine the completeness of the document input by the document input unit 31 (whether all the standards or standards are described). It is a useful table for. On the other hand, the total number component matrix is a table useful for determining the description amount or the degree of detail (whether the reference or standard is described in detail) of the document input by the document input unit 31.

  The viewpoint (medium) component matrix, the total number component matrix, and the viewpoint (large) component matrix generated by the component matrix generation unit 33 are stored in the result storage unit 23.

  The project information input unit 34 inputs project information indicating the outline of the project described in the document input by the document input unit 31 (that is, related information related to the contents of the document). The project information input by the project information input unit 34 is created by a system developer or the like. The project information (project information indicating the outline of the project described in the document) input by the project information input unit 34 is generated by each component matrix (generated for the document) generated by the component matrix generation unit 33 described above. Are stored in the result storage unit 23 in association with each component matrix).

  For example, project information, each component matrix generated for the document, and evaluation information indicating the evaluation of the document are accumulated in the result storage unit 23 for each project described in the past document, for example. .

  The similar project specifying unit 35 includes each component matrix generated by the component matrix generating unit 33 and project information input by the project information input unit 34, each component matrix for past documents stored in the result storage unit 23, and Based on the project information, a project similar to the project described in the document input by the document input unit 31 (hereinafter simply referred to as a similar project) is specified.

  The evaluation acquisition unit 36 acquires the evaluation information of the similar project specified by the similar project specification unit 35 (evaluation information indicating the evaluation of the document describing the contents of the similar project) from the result storage unit 23.

  The presenting unit 37 gives each component matrix generated by the component matrix generating unit 33 and the evaluation information acquired by the evaluation acquiring unit 36 to an evaluator who evaluates a document input by the document input unit 31, for example. Present.

  The evaluation input unit 38 inputs evaluation information indicating the evaluation according to an operation of an evaluator who evaluates the document input by the document input unit 31.

  FIG. 3 shows an example of the data structure of the viewpoint information storage unit 22 shown in FIG. As shown in FIG. 2, the viewpoint information storage unit 22 stores viewpoints (large), viewpoints (medium), and viewpoints (small) in association with each other.

  As described above, the viewpoint (large) is a character string (term) representing an item to be described in the document as a predetermined standard or standard. The viewpoint (medium) is a character string (term) representing a more detailed item than the viewpoint (large). The viewpoint (small) is a character string (term) representing an item more detailed than the viewpoint (medium).

  That is, the viewpoint information storage unit 22 stores a set of terms (character strings) having a hierarchical structure including three stages of viewpoint (large), viewpoint (medium), and viewpoint (small).

  In the example illustrated in FIG. 3, the viewpoint information storage unit 22 stores the viewpoints (medium) terms “business processing amount” and “expansion target” in association with the viewpoint (large) term “extensibility”. . In addition, the viewpoint information storage unit 22 stores the viewpoints (small) terms “normal work” and “busy period work” in association with the viewpoint (medium) term “business processing amount”. Further, the viewpoint information storage unit 22 stores viewpoint (small) terms “CPU” and “memory” in association with the viewpoint (medium) term “expansion target”. According to this, it is shown that terms representing items in more detail than the term (large) term “extensibility” are the terms “business processing amount” and “expansion target”. In addition, terms that represent more detailed items than the term (medium) term “business processing volume” are the terms “normal business” and “busy business” in the perspective (small), and the term “medium extension” The terms representing more detailed items are “CPU” and “memory” in terms of viewpoints (small).

  Similarly, the viewpoint information storage unit 22 stores the viewpoints (medium) terms “backup”, “business continuation”, and “recovery” in association with the viewpoint (large) term “availability”. Further, the viewpoint information storage unit 22 associates the terms “small” with the terms “data amount”, “time zone”, “target range”, “backup method”, and “backup method” in association with the term “medium”. "Recovery method" is stored. In addition, the viewpoint information storage unit 22 associates the viewpoint (medium) term “business continuity” with the viewpoint (small) terms “role”, “requirement”, “schedule”, “recovery level”, and “operation rate”. Is stored. In addition, the viewpoint information storage unit 22 stores the viewpoint (small) terms “recovery time” and “availability confirmation” in association with the term “medium” term “recovery”. According to this, it is shown that the terms representing the items in more detail than the term (large) term “availability” are the terms “backup”, “business continuation”, and “recovery”. In addition, terms that represent more detailed items than the term “middle” term “backup” are terms “data amount”, “time zone”, “target range”, “backup method”, and “recovery method”. It is shown that there is. In addition, the terms representing the items in more detail than the term “business continuity” in the perspective (medium) are the terms “role”, “requirement”, “schedule”, “recovery level” and “operation rate” in the perspective (small). It is shown. Further, it is indicated that terms representing items in more detail than the term “recovery” in the viewpoint (medium) are the terms “recovery time” and “availability confirmation” in the viewpoint (small).

  Next, information stored in the result storage unit 23 illustrated in FIG. 2 will be described with reference to FIGS. For each project described in the document as described above, project information, each component matrix (a viewpoint (medium) component matrix, a total number component matrix and a viewpoint (large) component matrix), and evaluation information are stored in the result storage unit 23. Stored in association.

  FIG. 4 shows an example of the data structure of project information stored in the result storage unit 23. The project information indicates, for example, an outline of a project described in a document. As shown in FIG. 4, the project information includes, for example, a project name, a business type, a product rank, a scale, and a period (information).

  Each component matrix stored in the result storage unit 23 is each component matrix generated for a document describing the contents of a project whose outline is indicated by the associated project information. Although details of the data structure of each component matrix will be described later, each component matrix may be stored in a storage area other than the record storage unit 23. In this case, as shown in FIG. 5, the record storage unit 23 only needs to store information indicating an area in which each component matrix is stored.

  FIG. 6 shows an example of the data structure of the evaluation information stored in the result storage unit 23. The evaluation information indicates an evaluation of the evaluator with respect to a document in which the content of the project (system development or the like) indicated by the associated project information is described. As shown in FIG. 6, the evaluation information includes, for example, evaluation related to document completeness and detail.

  Next, a processing procedure of the document component analysis apparatus 30 according to the present embodiment will be described with reference to the flowchart of FIG.

  First, the document input unit 31 inputs a document to be evaluated by the evaluator (step S1).

  Here, FIG. 8 shows an example of a data structure of a document input by the document input unit 31. It is assumed that the document input by the document input unit 31 is composed of a plurality of sections. A document (a section constituting the document) includes a plurality of components (cells) in which a part of the document is described. That is, the document (contents) is divided into a plurality of components.

  The file format of the document input by the document input unit 31 is not limited. However, in the case of a document that is not in the format shown in FIG. 8 (that is, a document that is not divided into a plurality of components), the text of the document Is converted into the format shown in FIG. Further, the document input by the document input unit 31 is preferably divided into, for example, chapters, sections, and terms because the component matrix generated from the document is easy to see.

  Although omitted in the document shown in FIG. 8, in the document input by the document input unit 31, for example, a viewpoint (large) term (included in the viewpoint (large) is included for each section constituting the document. Character string) is specified. Hereinafter, a document input by the document input unit 31 is referred to as a target document.

  Returning to FIG. 7 again, the following steps S2 to S5 are executed for each of the sections constituting the target document. Hereinafter, the node that is the target of the processing in steps S2 to S5 is referred to as a target node.

  The viewpoint acquisition unit 32 acquires a term (large) term specified in the target clause (step S2).

  Next, the component matrix generation unit 33 performs a viewpoint (medium) component matrix generation process on the target clause (step S3). According to this viewpoint (middle) component matrix generation process, each viewpoint (middle) associated with the viewpoint (large) term of the target clause acquired by the viewpoint (large) acquisition unit 32 in the viewpoint information storage unit 22. A viewpoint (medium) component matrix is generated that represents the number of cells (cells that constitute the target section) that have a description of the term. Details of the viewpoint (medium) component matrix generation process will be described later.

  In addition, the component matrix generation unit 33 executes a total number component matrix generation process on the target clause (step S4). According to this total number component matrix generation process, the terminology (medium) of each viewpoint associated with the term (large) term of the target clause acquired by the viewpoint (large) acquisition unit 32 in the viewpoint information storage unit 22 and A total number component matrix is generated that represents the amount of description relating to the term (small) term associated with the term (medium) term. The details of the total number component matrix generation process will be described later.

  Furthermore, the component matrix generation unit 33 performs viewpoint (large) component matrix generation processing on the target clause (step S5). According to this viewpoint (large) component matrix generation process, a viewpoint (first) component matrix representing the viewpoint (large) term of the target section and the number of cells constituting the target section is generated. Details of the viewpoint (large) component matrix generation process will be described later.

  Each component matrix generated by the processing in steps S3 to S5 (that is, each component matrix generated from the target document) is stored together with project information indicating an outline of the project described in the target document, as well as a result storage unit. 23. The project information is created by, for example, a system developer or the like, and is input by the project information input unit 34.

  Next, it is determined whether or not the processing in steps S2 to S5 has been executed for all sections constituting the target document (step S6).

  If it is determined that the process has not been executed for all the nodes (NO in step S6), the process returns to the above-described step S2 and is repeated. In this case, the process is repeated with a section in which the process of steps S2 to S5 is not executed among the sections constituting the target document.

  On the other hand, when it is determined that the processing has been executed for all the sections (YES in step S7), the similar project specifying unit 35 and the evaluation acquiring unit 36 each component matrix and actual result storage unit generated by the component matrix generation unit 33 Based on the information stored in 23, an automatic evaluation process is executed (step S7). According to this automatic evaluation process, a project similar to the project described in the target document (similar project) is specified, and evaluation information indicating evaluation for the document in which the similar project is described is acquired. Details of the automatic evaluation process will be described later.

  The presentation unit 37 uses each component matrix (a viewpoint (medium) component matrix, a total number component matrix and a viewpoint (large) component matrix) generated by the component matrix generation unit 33 and evaluation information acquired in the automatic evaluation process, for example, as a target The document is presented to the evaluator who evaluates the document (step S8).

  Thereby, the evaluator can refer to each presented component matrix and evaluation information when evaluating the target document.

  Next, a processing procedure of the above-described viewpoint (medium) component matrix generation process (the process of step S3 shown in FIG. 7) will be described with reference to the flowchart of FIG. This viewpoint (medium) component matrix generation process is a process for generating a table (viewpoint (medium) component matrix) useful for the evaluator to determine the completeness of the target document.

  Note that a document input by the document input unit 31 is referred to as a target document, and a clause that is subject to the viewpoint (medium) component matrix generation process among the clauses that constitute the target document is referred to as a target clause.

  In the viewpoint (medium) component matrix generation process, the following steps S11 to S18 are executed for each cell (component) constituting the target clause.

  First, the component matrix generation unit 33 acquires one of the cells constituting the target clause based on the target document (step S11). Hereinafter, the cell acquired in step S11 is referred to as a target cell.

  Next, for each of the viewpoint (medium) terms stored in the viewpoint information storage unit 22 in association with the viewpoint (large) term of the target clause specified by the viewpoint (large) acquisition unit 32 described below, Steps S12 to S16 are executed.

  In this case, the component matrix generation unit 33 acquires one viewpoint (medium) term stored in the viewpoint information storage unit 22 in association with the viewpoint (large) term of the target clause (step S12).

  The component matrix generation unit 33 specifies the number of viewpoint (medium) terms (number of viewpoint (medium) appearances) acquired in step S12 appearing in the target cell (step S13). In addition, the term appearance number of the viewpoint (medium) specified by the component matrix generation unit 33 is held in the component matrix generation unit 33, for example.

  Further, the following steps S14 and S15 are executed for each viewpoint (small) term stored in the viewpoint information storage unit 22 in association with the viewpoint (middle) term acquired in step S12.

  In this case, the component matrix generation unit 33 acquires one viewpoint (small) term stored in the viewpoint information storage unit 22 in association with the viewpoint (middle) term acquired in step S12 (step S14). ).

  The component matrix generation unit 33 identifies the number of viewpoint (small) terms (number of viewpoint (small) terms appearing) acquired in step S14 appearing in the target cell (step S15). In addition, the term appearance number of the viewpoint (small) specified by the component matrix generation unit 33 is held in the component matrix generation unit 33, for example.

  When the process of step S15 is executed, the component matrix generation unit 33 associates the viewpoint (small) term stored in the viewpoint information storage unit 22 with the viewpoint (middle) term acquired in step S12. It is determined whether or not the processing of steps S14 and S15 has been executed for all (step S16).

  When it is determined that the processing has not been executed for all the terms (small) (NO in step S16), the process returns to the above-described step S14 and is repeated. In this case, in step S14, terms (small) that are not executed in steps S14 and S15 are acquired.

  On the other hand, when it is determined that the processing has been executed for all the terms (small) (YES in step S16), the component matrix generation unit 33 determines the viewpoints of the target clause acquired by the viewpoint (large) acquisition unit 32 ( It is determined whether or not the processing of steps S12 to S16 has been executed for all of the viewpoint (medium) terms stored in the viewpoint information storage unit 22 in association with the large term (step S17).

  When it is determined that the processing has not been executed for all the terms in the viewpoint (medium) (NO in step S17), the processing returns to the above-described step S12 and is repeated. In this case, in step S12, a term (middle) term in which the processes in steps S12 to S16 are not executed is acquired.

  On the other hand, when it is determined that the processing has been executed for all the terms in the viewpoint (medium) (YES in step S17), the component matrix generation unit 33 associates the terms with the viewpoint (large) in the target clause. The number of appearances of each viewpoint (medium) term in the target cell and the number of occurrences of each viewpoint (small) term associated with the term (medium) term in the target cell are retained.

  The component matrix generation unit 33, based on the number of occurrences of each viewpoint (medium) term in the target cell and the number of occurrences of the term (small) term in the target cell held in the component matrix generation unit 33, A viewpoint (medium) representing the viewpoint of the target cell is determined (step S18).

  In the process of step S18, the viewpoint (medium) term having the largest number of appearances is determined as the viewpoint (medium) of the target cell. In addition, if there are multiple terms with the highest number of applications (medium), the terms with the highest number of occurrences in the target cell of the terms with the corresponding viewpoint (small) are targeted. Determined as cell perspective (middle). Furthermore, when there are a plurality of terms of the viewpoint (medium) with the largest number of applications, and the number of occurrences of the associated viewpoint (small) terms in the target cell is also the same, the viewpoint information The term described at the upper level in the storage unit 22 is determined as the viewpoint (medium) of the target cell. In addition, when no term (middle) term appears in the target cell, the viewpoint (middle) of the target cell is set as other.

  Here, with reference to FIG. 3 mentioned above, the process of step S18 is demonstrated concretely. Here, the description will be made assuming that the viewpoint (large) term specified in the target section is “availability”.

  For example, it is assumed that one “backup” term (medium) appears in the target cell. In this case, since the term of the viewpoint (middle) having the highest number of appearances in the target cell is “backup”, the viewpoint (middle) of the target cell is determined as “backup”.

  Further, for example, a case is assumed in which one term “middle” term “backup” and two “business continuation” appear in the target cell. In this case, since the term of the viewpoint (medium) having the highest number of appearances in the target cell is “business continuation”, the viewpoint (medium) of the target cell is determined as “business continuation”.

  In addition, for example, the terms “backup” and “business continuity” in the viewpoint (medium) appear one by one in the target cell, and the term “operating rate” in the viewpoint (small) appears one in the target cell. Is assumed. In this case, the terms (medium) with the highest number of occurrences in the target cell are the two terms “backup” and “business continuation”, but the term “operating rate” is the term “medium”. Since the term is associated with “business continuation”, the viewpoint (medium) of the target cell is determined as “business continuation”.

  Further, for example, a case is assumed where the terms “backup” and “business continuity” in the viewpoint (medium) appear one by one in the target cell. In this case, the terms (medium) that have the highest number of appearances in the target cell are two, “backup” and “business continuation”. In FIG. 3, “backup” is described above “business continuation”. Therefore, the viewpoint (medium) of the target cell is determined as “backup”.

  Further, for example, a case is assumed where only terms (small) terms (for example, “data amount”, “role”, “recovery time”, etc.) appear in the target cell. In this case, since the term (medium) term does not appear in the target cell, the viewpoint (middle) of the target cell is determined as “other”.

  For example, when the viewpoint (medium) term and the viewpoint (small) term do not appear in the target cell, the viewpoint (middle) of the target cell is not determined.

  When the process of step S18 is executed as described above, the component matrix generation unit 33 determines whether or not the processes of steps S11 to S18 described above have been executed for all the cells constituting the target clause (step S19). ).

  When it is determined that the process has not been executed for all the cells (NO in step S19), the process returns to the above-described step S11 and is repeated. In this case, in step S11, a cell in which the processes in steps S11 to S18 are not executed is acquired.

  On the other hand, when it is determined that the process has been executed for all the cells (YES in step S19), the viewpoint (medium) is determined for each of the cells constituting the target clause.

  The component matrix generation unit 33 uses the viewpoint (medium) terminology for each viewpoint (medium) term stored in the viewpoint information storage unit 22 in association with the viewpoint (large) term of the target clause. A viewpoint (medium) component matrix including the number of cells (cells constituting the target clause) determined as) is generated (step S20).

  Here, FIG. 10 shows an example of the data structure of the viewpoint (medium) component matrix generated by the component matrix generation unit 33. Here, an example of the viewpoint (medium) component matrix generated by executing the viewpoint (medium) component matrix generation process for the target clause “10.2 backup policy” is shown. It is assumed that the number of cells constituting the target clause is 39.

  The example illustrated in FIG. 10 indicates that “backup” is determined from the viewpoint (medium) of 10 cells among 39 cells constituting the target clause. In addition, it is shown that “others” is determined from the viewpoint (medium) of 9 cells among 39 cells constituting the target clause.

  That is, according to the viewpoint (medium) component matrix as shown in FIG. 10, it is shown that 10 out of 39 cells of the target section “10.2 backup policy” are descriptions regarding the viewpoint (medium) “backup”. Has been.

  Next, with reference to the flowchart of FIG. 11, the processing procedure of the total number component matrix generation process (the process of step S4 shown in FIG. 7) will be described. This total number component matrix generation process is a process for generating a table (total number component matrix) useful for the evaluator to determine the level of detail of the target document.

  As in the case of the above-described viewpoint (medium) component matrix generation process, the document input by the document input unit 31 is the target document, and the sections that are the target of the total number component matrix generation process among the sections constituting the target document. Is called the target section.

  In the total number component matrix generation process, the following steps S21 to S28 are executed for each cell (component) constituting the target clause.

  First, the component matrix generation unit 33 acquires one of the cells constituting the target clause based on the target document (step S21). Hereinafter, the cell acquired in step S11 is referred to as a target cell.

  Next, for each of the viewpoint (medium) terms stored in the viewpoint information storage unit 22 in association with the viewpoint (large) term of the target clause acquired by the viewpoint (large) acquisition unit 32 described above, the following Steps S22 to S26 are executed.

  In this case, the component matrix generation unit 33 acquires one viewpoint (medium) term stored in the viewpoint information storage unit 22 in association with the viewpoint (large) term of the target clause (step S22).

  The component matrix generation unit 33 specifies the number of viewpoint (medium) terms (number of viewpoint (medium) appearances) acquired in step S22 appearing in the target cell (step S23). In addition, the term appearance number of the viewpoint (medium) specified by the component matrix generation unit 33 is held in the component matrix generation unit 33, for example.

  Further, the following steps S24 and S25 are executed for each of the viewpoint (small) terms stored in the viewpoint information storage unit 22 in association with the viewpoint (medium) term acquired in step S22.

  In this case, the component matrix generation unit 33 acquires one viewpoint (small) term stored in the viewpoint information storage unit 22 in association with the viewpoint (middle) term acquired in step S22 (step S24). ).

  The component matrix generation unit 33 specifies the number of viewpoint (small) terms (number of viewpoints (small) term appearance) acquired in step S24 that appears in the target cell (step S25). In addition, the term appearance number of the viewpoint (small) specified by the component matrix generation unit 33 is held in the component matrix generation unit 33, for example.

  When the process of step S25 is executed, the component matrix generation unit 33 associates the viewpoint (middle) term acquired in step S12 with the viewpoint (small) term stored in the viewpoint information storage unit 22. It is determined whether or not the processing of steps S24 and S25 has been executed for all (step S26).

  When it is determined that the processing has not been performed for all the terms (small) (NO in step S26), the process returns to the above-described step S24 and is repeated. In this case, in step S24, terms (small) that are not executed in steps S24 and S25 are acquired.

  On the other hand, when it is determined that the processing has been executed for all the terms (small) (YES in step S26), the component matrix generation unit 33 determines the viewpoint of the target clause acquired by the viewpoint (large) acquisition unit 32 ( It is determined whether or not the processing of steps S22 to S26 has been executed for all of the viewpoint (medium) terms stored in the viewpoint information storage unit 22 in association with the large term (step S27).

  When it is determined that the processing has not been executed for all the terms in the viewpoint (medium) (NO in step S27), the process returns to the above-described step S22 and is repeated. In this case, in step S22, a term (middle) term in which the processes in steps S22 to S26 are not executed is acquired.

  On the other hand, when it is determined that the processing has been executed for all the terms in the viewpoint (medium) (YES in step S27), the component matrix generation unit 33 associates the terms with the viewpoint (large) in the target clause. The number of appearances of each viewpoint (medium) term in the target cell and the number of occurrences of each viewpoint (small) term associated with the term (medium) term in the target cell are retained.

  The component matrix generation unit 33, based on the number of occurrences of each viewpoint (medium) term in the target cell and the number of occurrences of the term (small) term in the target cell held in the component matrix generation unit 33, The total number of viewpoints (medium) appearing in the target cell is determined (step S28). Note that the total number of each viewpoint (medium) determined by the component matrix generation unit 33 is held in the component matrix generation unit 33.

  In the process of step S28, the number of occurrences of the term (middle) term in the target cell is set as the total number of terms of the term (middle). In addition to the viewpoint (medium) term, when the viewpoint (small) term stored in the viewpoint information storage unit 22 in association with the viewpoint (middle) term appears in the target cell, The number of appearances of the term (small) term in the target cell is added as the total number of terms of the term (medium). Further, the viewpoint (medium) term does not appear in the target cell, and the viewpoint (small) term stored in the viewpoint information storage unit 22 in association with the viewpoint (medium) term appears in the target cell. If this is the case, the number of occurrences of the term (small) term in the target cell is added as the total number of other (point of view (medium)).

  Here, with reference to FIG. 3 mentioned above, the process of step S28 is demonstrated concretely. Here, the description will be made assuming that the viewpoint (large) term specified in the target section is “availability”.

  For example, it is assumed that one “backup” term (medium) appears in the target cell. In this case, since the number of occurrences of the term “backup” in the viewpoint (medium) in the target cell is 1, the total number of the term “backup” in the viewpoint (middle) is determined to be 1.

  Further, for example, a case is assumed where the terms “backup” and “business continuity” in the viewpoint (medium) appear one by one in the target cell. In this case, since the number of occurrences of the term “backup” in the viewpoint (medium) in the target cell is 1, the total number of the term “backup” in the viewpoint (middle) is determined to be 1. In addition, since the number of appearances of the term “business continuation” in the viewpoint (medium) in the target cell is 1, the number of statements of the term “business continuation” in the viewpoint (middle) is determined to be 1.

  For example, when the term “backup” in the viewpoint (medium) appears in the target cell, and the terms “data amount” and “time zone” in the viewpoint (small) appear one by one in the target cell. Is assumed. In this case, the terms “data amount” and “time zone” in the viewpoint (small) are terms associated with the term “backup” in the viewpoint (medium), and therefore the terms “data amount” and The number of occurrences of the “time zone” in the target cell is added to the total number of terms “backup” in the viewpoint (medium). Therefore, the total number of terms “backup” in the viewpoint (medium) is determined to be 3.

  In addition, the viewpoint (medium) term “backup” appears in the target cell, and the viewpoint (small) term “data amount” appears in the target cell. Assume that one term “role” appears in the target cell. In this case, since the term “data amount” of the viewpoint (small) is a term associated with the term “backup” of the viewpoint (medium), the appearance of the term “data amount” of the viewpoint (small) in the target cell. The number is added to the total number of terms “backup” in the perspective (medium). Accordingly, the total number of terms “backup” in the viewpoint (medium) is determined to be two. Further, the viewpoint (medium) term “business continuation” stored in the viewpoint information storage unit 22 in association with the viewpoint (small) term “role” does not appear in the target cell. The number of occurrences of the term “role” in the target cell is added to the total number of “others”. Therefore, the total number of “others” is determined to be 1.

  Further, for example, it is assumed that the viewpoint (small) term “data amount” and the viewpoint (small) term “role” appear one by one in the target cell. In this case, corresponding to the term “backup” of the viewpoint (middle) and the term “role” of the viewpoint (small) stored in the viewpoint information storage unit 22 in association with the term “data amount” of the viewpoint (small) Since the term “business continuation” of the viewpoint (medium) stored in the viewpoint information storage unit 22 does not appear in the target cell, the terms “data amount” and “role” of the viewpoint (small) The number of occurrences in the cell is added to the total number of viewpoints (medium) “others”. Therefore, the total number of viewpoints (medium) “others” is determined to be two.

  When the process of step S28 is executed as described above, the component matrix generation unit 33 determines whether or not the processes of steps S21 to S28 described above have been executed for all the cells constituting the target clause (step S29). ).

  When it is determined that the process has not been executed for all the cells (NO in step S29), the process returns to the above-described step S21 and is repeated. In this case, in step S21, a cell in which the processes in steps S21 to S28 are not executed is acquired.

  On the other hand, when it is determined that the processing has been executed for all the cells (YES in step S29), the component matrix generation unit 33 holds the total number of terms in each viewpoint (medium) for each cell constituting the target clause. Has been.

  The component matrix generation unit 33 generates a total number component matrix including a value obtained by summing up the total number of terms in each viewpoint (medium) for each cell constituting the target clause (step S30).

  Here, FIG. 12 shows an example of the data structure of the total number component matrix generated by the component matrix generation unit 33. Here, an example of the total number component matrix generated by executing the total number component matrix generation process for the target clause “10.2 backup policy” is shown.

  The example shown in FIG. 12 shows that the total number of terms “backup” in the viewpoint (medium) is 22 and the total number of “others” is 11 in the target clause (all cells constituting the target section). Yes.

  That is, according to the total number component matrix as shown in FIG. 12, it is expressed that the viewpoint (medium) “backup” is mainly described in detail in the target section “10.2 backup policy”.

  As described above, the viewpoint (medium) component matrix generation processing (steps S11 to S17 shown in FIG. 9) and the total number component matrix generation processing (steps S21 to S27 shown in FIG. 11) are common. For this reason, by using the processing result of the viewpoint (medium) component matrix generation process (steps S11 to S17 shown in FIG. 9), it is possible to omit the same process in the total number component matrix generation process.

  Next, the processing procedure of the viewpoint (large) component matrix generation process (the process of step S5 shown in FIG. 7) will be described with reference to the flowchart of FIG. This viewpoint (large) component matrix generation process is a useful table for the evaluator to judge the contents of the target document, for example, and is expressed from a higher viewpoint than the viewpoint (medium) component matrix described above. This is a process for generating a table (viewpoint (large) component matrix).

  As in the case of the viewpoint (medium) component matrix generation process and the total number component matrix generation process described above, the document input by the document input unit 31 is the target document, and the viewpoint (large) among the sections constituting the target document. A clause that is a target of component matrix generation processing is referred to as a target clause.

  First, the component matrix generation unit 33 refers to the target document and counts the number of cells constituting the target clause (step S31).

  Next, the component matrix production | generation part 33 pinpoints the term of view (large) of an object clause (step S32). In this case, the component matrix generation unit 33 refers to, for example, the viewpoint (medium) component matrix generated in the above-described viewpoint (medium) component matrix generation processing (for example, the viewpoint (medium) component matrix shown in FIG. 10), The viewpoint (large) term associated with the viewpoint (middle) in which the value (number of cells) is described is specified as the viewpoint (large) term of the target section.

  In the process of step S32, as described above, the viewpoint (large) term of the target section may be specified based on the viewpoint (large) term specified in the target section with reference to the target document. In addition, the viewpoint (large) term of the target clause acquired by the viewpoint (large) acquisition unit 32 may be used.

  The component matrix generation unit 33 generates a viewpoint (large) component matrix that includes the number of cells counted in step S31 in association with the viewpoint (large) term specified in step S32 (step S33).

  Here, FIG. 14 shows an example of the data structure of the viewpoint (large) component matrix generated by the component matrix generation unit 33. Here, an example of the viewpoint (large) component matrix generated by executing the viewpoint (large) component matrix generation process for the target clause “10.2 backup policy” is shown.

  The example shown in FIG. 14 shows that the number of cells constituting the target clause is 39, and that the target clause is described as “availability” as an upper viewpoint.

  In FIG. 7 described above, the processing is executed in the order of the viewpoint (medium) component matrix generation processing shown in FIG. 9, the total number component matrix generation processing shown in FIG. 11, and the viewpoint (large) component matrix generation processing shown in FIG. Although described as an example, the order of these processes may be changed as appropriate.

  Next, with reference to the flowchart of FIG. 15, the processing procedure of the automatic evaluation process described above (the process of step S7 shown in FIG. 7) will be described.

  In this automatic evaluation process, evaluation information that is used as a reference when evaluating a document input by the document input unit 31 is acquired from the result storage unit 23. The automatic evaluation process is executed by the similar project identification unit 35 and the evaluation acquisition unit 36 included in the document component analysis apparatus.

  Here, in the result storage unit 23, for each project described in the past document, project information indicating the outline of the project, each component matrix (perspective (medium) component matrix) generated for the document, Assume that the total number component matrix and the viewpoint (large) component matrix) and evaluation information indicating the evaluation of the document are accumulated (stored) in association with each other. Note that the evaluation information stored in the result storage unit 23 is created by an evaluator who evaluates a document and is input by the evaluation input unit 38.

  Further, in the result storage unit 23, as described above, the project information indicating the outline of the project described in the document (document to be evaluated) input by the document input unit 31 and the generated document are generated. Each component matrix (a viewpoint (medium) component matrix, a total number component matrix, and a viewpoint (large) component matrix) is stored in association with each other.

  Hereinafter, a project described in a document input by the document input unit 31 is referred to as a target project, and project information indicating an outline of the target project is referred to as target project information.

  First, the similar project specifying unit 35 acquires target project information (step S41).

  Further, the similar project specifying unit 35 acquires the viewpoint (medium) component matrix, the total number component matrix, and the viewpoint (large) component matrix stored in the result storage unit 23 in association with the target project information (step S42).

  Next, the similar project specifying unit 35 refers to the project information and each component matrix stored in the result storage unit 23, and the project (target project) described in the document input by the document input unit 31. Search for (identify) similar projects.

  In this case, the similar project specifying unit 35 executes the following steps S43 to S45 for each of the projects other than the target project (that is, project information other than the target project information stored in the result storage unit 23). Hereinafter, the project (project information) to be processed in steps S43 to S45 is referred to as a similar candidate project (similar candidate project information).

  First, the similar project specifying unit 35 acquires similar candidate project information from the result storage unit 23 (step S43).

  Next, the similar project specifying unit 35 associates the similar candidate project information acquired in step S43 with the viewpoint (medium) component matrix, the total number component matrix, and the viewpoint (large) component matrix stored in the result storage unit 23. Is acquired (step S44).

  The similar project specifying unit 35 compares the target project information acquired in step S41 with the similar candidate project information acquired in step S43, and each component matrix of the target project information acquired in step S42 is acquired in step S44. The degree of similarity between the target project and the similar candidate project is calculated by comparing with each component matrix of the similar candidate project information (step S45).

  Here, the calculation process of the similarity between the target project and the similar candidate project will be specifically described. The similarity between the target project and the similar candidate project calculated by the similar project specifying unit 35 includes the similarity of the project information and the similarity of the component matrix.

  First, the similarity of project information will be described. Here, it is assumed that the project information (target project information and similar candidate project information) has a data structure as shown in FIG. In this case, if the business types included in the target project information and the similar candidate project information are the same, 10 is added to the similarity of the project information. If the product ranks included in the target project information and the similar candidate project information are the same, 5 is added to the similarity of the project information. If the scales included in the target project information and the similar candidate project information are the same, 8 is added to the similarity of the project information. Further, if the error of the period included in the target project information and the similar candidate project information is less than one month, 5 is added to the similarity of the project information, and if the error is less than 2 months, 4 is added to the similarity of the project information. Is added. As described above, the similarity of the project information is calculated by adding the similarities to the items of the target project information and the similar candidate project information.

  Next, the similarity of the component matrix will be described. The similarity of the component matrix is, for example, for each corresponding component matrix: “total value described in the component matrix (all clauses) / the value described in the component matrix (of the cell)” The difference between the values of “number” is calculated, and a value obtained by rounding off the difference is subtracted from 10.

  That is, for each of the viewpoint (middle) component matrix of the target project information acquired in step S42 and the viewpoint (middle) component matrix of the similar candidate project information acquired in step S44, "all of the corresponding viewpoint (middle) component matrix" The total value of the values described in the section) / the number in which the value is described in the viewpoint (medium) component matrix is calculated, and the value obtained by rounding the difference between the calculated values is subtracted from 10 Calculate the value. This calculation process is also executed for the total number component matrix and the viewpoint (large) component matrix, and the total value of the values calculated for each component matrix is set as the similarity of the component matrix. Note that the degree of similarity of component matrices may be calculated by other processes as long as each component matrix is used.

  The similarity between the target project and the similar candidate project is the total value of the similarity of the project information and the similarity of the component matrix calculated as described above.

  Note that the degree of similarity between the target project and the similar candidate project may be calculated by a method other than those described above. Also, the similarity between the target project and the similar candidate project may not be calculated using all of the project information and each component matrix, for example, may be calculated using only the project information, or only each component matrix It may be calculated using

  As described above, when the similarity between the target project and the similar candidate project is calculated in step S45, the similar project specifying unit 35 selects a project other than the target project (other than the target project information stored in the result storage unit 23). It is determined whether or not the processing of steps S43 to S45 described above has been executed for all of the project information) (step S46).

  When it is determined that the processing has not been executed for all the projects (NO in step S46), the process returns to the above-described step S43 and is repeated. In this case, a process that is not executed in steps S43 to S45 is executed as a similar candidate project.

  On the other hand, when it is determined that the processing is executed for all the projects (YES in step S46), the similar project specifying unit 35 selects a project (similar candidate project) having the highest similarity with the calculated target project. A project similar to the target project (similar project) is specified (step S47).

  Next, the evaluation acquisition unit 36 evaluates the similar project identified by the similar project identifying unit 35 (that is, the evaluation information stored in the result storage unit 23 in association with the project information indicating the outline of the similar project). ) Is acquired (step S48). Note that the evaluation information acquired by the evaluation acquisition unit 36 in this way is information indicating an evaluation of a past document in which a similar project is described.

  The evaluation information acquired by the evaluation acquisition unit 36 includes the viewpoint (medium) component matrix, the total number component matrix, and the total number component matrix generated for the document (document to be evaluated) input by the document input unit 31 as described above. Along with the viewpoint (large) component matrix, it is presented to the evaluator of the document via the presentation unit 37. When the evaluation information is presented, the similarity between the target project and the similar project may be presented together.

  As described above, in this embodiment, a document composed of a plurality of cells (components) including a character string, in which a viewpoint (large) term (first character string) is designated, is input. Then, the viewpoint (middle) term (second character string) stored in the viewpoint information storage unit 22 in association with the designated viewpoint (large) term is acquired, and the input document is configured. For each cell, identify the number of terms (middle) terms included in the cell, and for each cell, based on the number of terms (middle) terms identified for the cell, Determining the term (medium) term representing the medium), generating a point (middle) component matrix (first component matrix) including the number of cells in which the term (middle) term is determined, Evaluator who evaluates the document with a configuration that presents the middle (main) component matrix Since then viewpoint Medium ingredient matrix reference can easily grasp the completeness of the contents of the document, it is possible to support the evaluation of the document by the evaluator.

  Further, in the present embodiment, the viewpoint (small) term (stored in the viewpoint information storage unit 22 in association with the viewpoint (medium) term associated with the designated viewpoint (large) term ( (Third character string) is acquired, the number of viewpoint (small) terms included in the cell is specified for each cell constituting the input document, and the viewpoint (medium) specified for the cell is specified. Based on the number of terms and the number of terms in terms (small), for each cell, determine the terms in terms of perspective (medium) that represent the perspective of the cell, and more detailed considering the terms in terms of perspective (small) A (mid) component matrix can be generated.

  Further, in the present embodiment, a total number component matrix (second component matrix) including the number of viewpoint (medium) terms specified for each cell and the number of viewpoint (small) terms is generated and generated. In addition, the configuration that presents the total number component matrix allows the evaluator who evaluates the document to easily understand the level of detail of the document with reference to the total number component matrix. It becomes possible to do.

  Furthermore, in the present embodiment, a viewpoint (large) component matrix (third component matrix) including the term of the designated viewpoint (large) and the number of cells constituting the input document is generated, and the viewpoint (third component matrix) is generated. Large) By presenting the component matrix, even evaluators who are not engaged in system development, for example, can grasp the content of the document from a higher viewpoint than the above viewpoint (medium) component matrix It becomes possible.

  In the present embodiment, the similarity is calculated by comparing the component matrix generated from the input document and the component matrix stored in the result storage unit 23, and based on the calculated similarity. Thus, a document similar to the document to be evaluated (a project described in the document to be evaluated) is configured by presenting the evaluation information stored in the result storage unit 23 in association with the component matrix. It is possible to evaluate the document to be evaluated with reference to the evaluation information for the document in which the content of the project similar to is described.

  Furthermore, in the present embodiment, information (second related information) indicating the outline of the project described in the input document, project information (first related information) stored in the result storage unit 23, and It is also possible to calculate the similarity by comparing the two, and present the evaluation information stored in the record storage unit 23 in association with the project information based on the calculated similarity.

  In the present embodiment, the viewpoint (medium) component matrix, the total number component matrix, the viewpoint (large) component matrix, and the evaluation information are presented. However, for example, only the viewpoint (medium) component matrix is presented. Such a configuration may be used.

  The method described in each of the above-described embodiments is a program that can be executed by a computer, such as a magnetic disk (floppy (registered trademark) disk, hard disk, etc.), an optical disk (CD-ROM, DVD, etc.), a magneto-optical disk ( MO), and can be stored and distributed in a storage medium such as a semiconductor memory.

  In addition, as long as the storage medium can store a program and can be read by a computer, the storage format may be any form.

  In addition, an OS (operating system) operating on the computer based on an instruction of a program installed in the computer from the storage medium, MW (middleware) such as database management software, network software, and the like implement the present embodiment. A part of each process may be executed.

  Furthermore, the storage medium in the present invention is not limited to a medium independent of a computer, but also includes a storage medium in which a program transmitted via a LAN or the Internet is downloaded and stored or temporarily stored.

  Further, the number of storage media is not limited to one, and the case where the processing in the present embodiment is executed from a plurality of media is also included in the storage media in the present invention, and the media configuration may be any configuration.

  The computer according to the present invention executes each process according to the present embodiment based on a program stored in a storage medium, and includes a single device such as a personal computer or a system in which a plurality of devices are connected to a network. Any configuration may be used.

  In addition, the computer in the present invention is not limited to a personal computer, but includes an arithmetic processing device, a microcomputer, and the like included in an information processing device, and is a generic term for devices and devices that can realize the functions of the present invention by a program. .

  Note that the present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. Moreover, various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, constituent elements over different embodiments may be appropriately combined.

  DESCRIPTION OF SYMBOLS 10 ... Computer, 20 ... External storage device, 22 ... Perspective information storage part, 23 ... Performance storage part, 30 ... Document component analyzer, 31 ... Document input part, 32 ... Perspective identification part, 33 ... Component matrix production | generation part, 34 ... project information input part, 35 ... similar project specifying part, 36 ... evaluation acquisition part, 37 ... presentation part, 38 ... evaluation input part.

Claims (7)

Perspective information storage means for associating and storing a first character string representing an item to be described in a document as a predetermined reference or standard and a second character string representing an item more detailed than the first character string When,
A document composed of a plurality of partial documents composed of a plurality of components including character strings, wherein the first character string stored in the viewpoint information storage means is designated for each partial document A document input means for inputting
For each component constituting the input document, the number of second character strings stored in the viewpoint information storage means in association with the designated first character string included in the component is calculated. Identification means to identify;
Determining means for determining, for each component, a second character string representing a viewpoint of the component based on the number of second character strings specified for each component;
The partial document name indicating the partial document and the stored second character string are arranged on each axis, and the partial document name is the data corresponding to the intersection of the partial document name and the second character string. Generating means for generating a first component matrix in which data indicating the number of components for which the second character string is determined among a plurality of components constituting the partial document to be displayed ;
A document component analyzing apparatus comprising: presenting means for presenting the generated first component matrix. The viewpoint information storage means further stores a third character string representing an item more detailed than the second character string in association with the second character string;
The specifying means associates, for each component constituting the input document, the second character string associated with the designated first character string included in the component. Further specifying the number of third character strings stored in the viewpoint information storage means,
The determining means is configured to determine, based on the number of second character strings and the number of third character strings specified for each component, a second character string that represents the viewpoint of the component for each component. The document component analysis apparatus according to claim 1, wherein: Based on the number of second character strings and the number of third character strings specified for each constituent element, the determining means determines, for each constituent element, the second character string that appears in the constituent element. Further determine the total number,
The generating unit arranges the partial document name and the stored second character string on each axis, and uses the partial document name as data corresponding to an intersection of the partial document name and the second character string. Further generating a second component matrix in which data indicating the total value of the total number of second character strings determined for each of the constituent elements constituting the partial document indicated by is arranged ,
The document component analysis apparatus according to claim 2, wherein the presenting unit further presents the generated second component matrix. The generation unit includes the partial document name and the stored first character string arranged on each axis, and the partial document name as data corresponding to the intersection of the partial document name and the first character string. And further generating a third component matrix in which data indicating the number of components constituting the partial document in which the first character string is designated is arranged .
4. The document component analyzing apparatus according to claim 3, wherein the presenting unit further presents the generated third component matrix. A record storage means for storing the first component matrix generated for a document different from the input document and the evaluation information indicating the evaluation of the document in association with each other;
Calculating means for calculating a similarity by comparing the generated first component matrix and the first component matrix stored in the result storing means;
Evaluation acquisition means for acquiring evaluation information stored in the result storage means in association with the first component matrix compared with the generated first component matrix based on the calculated similarity; Further comprising
The document component analysis apparatus according to claim 1, wherein the presenting unit further presents the acquired evaluation information. Record storage means for storing first related information related to the content of a document different from the input document and evaluation information indicating evaluation of the document;
Second related information input means for inputting related information related to the contents of the input document;
Calculating means for calculating the similarity by comparing the first related information stored in the record storing means and the second related information input by the related information input means;
Evaluation acquisition means for acquiring evaluation information stored in the result storage means in association with the first related information based on the calculated similarity; and
The document component analysis apparatus according to claim 1, wherein the presenting unit further presents the acquired evaluation information. Perspective information storage means for associating and storing a first character string representing an item to be described in a document as a predetermined reference or standard and a second character string representing an item more detailed than the first character string In a document component analysis apparatus composed of an external storage device having a computer and a computer using the external storage device, a program executed by the computer,
In the computer,
A document composed of a plurality of partial documents composed of a plurality of components including character strings, wherein the first character string stored in the viewpoint information storage means is designated for each partial document A step of entering
For each component constituting the input document, the number of second character strings stored in the viewpoint information storage means in association with the designated first character string included in the component is calculated. Identifying steps;
Determining, for each constituent element, a second character string representing the viewpoint of the constituent element based on the number of second character strings specified for each constituent element;
The partial document name indicating the partial document and the stored second character string are arranged on each axis, and the partial document name is the data corresponding to the intersection of the partial document name and the second character string. Generating a first component matrix in which data indicating the number of components for which the second character string is determined among a plurality of components constituting the partial document to be shown ;
A program for executing the step of presenting the generated first component matrix.

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