JP2006190235A - Document classifying method, document classifying program and document classifying device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a document classifying method for showing a relationship of similarity between a plurality of documents to be classified in a visually recognizable manner. <P>SOLUTION: A stable document-to-document distance between two documents out of the documents to be classified is calculated depending on a degree of similarity between both documents, and an initially arranged document is selected from the document to be classified and its position coordinate is initialized. In accordance with a difference between the length of a spacing vector to the other initially arranged document and the stable document-to-document distance and the direction of the spacing vector, a step of calculating a document-to-document force vector to be received from the other initially arranged document and a step of calculating the position coordinate at the next processing point depending on the document-to-document force vector are repeated until each initially arranged document is converged, to find a temporary position coordinate. Then, arranged documents are added several times and the temporary position coordinate is calculated, and the step of calculating the document-to-document force vector and a step of updating the position coordinate are repeated until all documents to be classified are finally converged. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a document classification method for classifying a plurality of documents to be classified according to their contents.

Examples of conventional document classification devices include those described in Patent Documents 1 to 3 and 2, for example. Patent Document 4 is a technique related to a graphics creation method in which nodes and arcs whose combinations are determined in advance are arranged in a display space with a visually suitable balance. In the document classification device described in Patent Document 1, each of a plurality of classification target documents is classified into one of a plurality of predetermined categories according to the distance between the documents. Further, in the document classification device described in Patent Document 2, each document is classified as described above according to the distance between the word vector of each document and the word vectors of cells arranged two-dimensionally for a plurality of documents to be classified. It is classified as one of the cells.
Japanese Patent Laid-Open No. 8-222447 Japanese Patent No. 3385297 JP 2003-288352 A JP 2002-312803 A

In the document classification apparatuses described in Patent Documents 1 and 2, each document is classified in units of categories or cells. According to this, it is possible to roughly know the positional relationship according to the content between documents in the entire plurality of classification target documents. However, these document classification devices cannot know the positional relationship between a plurality of documents classified into the same category or cell. If it is intended to classify documents in the same category or cell in more detail, it is necessary for the user to check the contents of those documents one by one, which increases the burden of manual work.
The spring model described in Patent Document 3 has a problem that the amount of calculation until the arrangement converges becomes enormous. Patent Document 4 discloses a method of arranging nodes while sequentially adding nodes to the display space. However, the graphics creation method of Patent Document 4 does not represent the interrelationship between nodes as a distance between nodes, but adds all the existing arrangement points (nodes, documents) as in the present invention. It is not necessary to reconstruct the positions of the arrangement points. The node addition method disclosed in Patent Document 4 is basically a method of adding a new node while fixing the existing node. At the time of addition, only the position of the existing node in the vicinity is re-executed. It is composed. When the graphics creation method of Patent Document 4 is applied to document classification, the position of all placement points must be reconstructed every time one placement point is added, which in turn increases the amount of calculation. there were.
The present invention has been made in view of the above problems, and makes it possible to know in detail the positional relationship between documents in a plurality of classification target documents, and in addition, even if the number of classification target documents increases. An object of the present invention is to provide a document classification method, a document classification program, and a document classification device that make it possible to suppress an increase in the amount.

  The document classification method of the present invention is a document classification method for classifying a plurality of classification target documents according to their contents, and the distance between stable documents between two documents among the classification target documents is determined by both documents. A first step of calculating according to the degree of similarity; a second step of selecting an initially arranged document from the classification target documents; and calculating position coordinates at which each of the initially arranged documents is initially arranged on a display coordinate system And the current processing point (repeating process of the fourth to sixth steps (or repeating process of the tenth and eleventh steps)) between each of the two documents among the arranged initial placement documents. A distance vector from one document to the other document on the display coordinate system at a certain time before execution of the sixth step (or eleventh step) at a certain time in Placement document A fourth step of calculating an inter-document force vector received from some other initially placed document based on the difference between the length of the spacing vector and the stable inter-document distance and the direction of the spacing vector; A fifth step of calculating a total document inter-force vector by summing up inter-document force vectors received from each of the other initial-arranged documents for the initial-arranged document; According to the inter-document force vector, the sixth step (or the next step after the certain time during the next processing time point (repeating process of the fourth to sixth steps (or repeating process of the tenth and eleventh steps)) (or An eleventh step) a sixth step of calculating position coordinates at a certain point in time) and the execution of the initial arrangement document during the repetition of the fourth to sixth steps. A seventh step of determining the convergence of the position coordinates and terminating the repetition process; an eighth step of selecting a next layout document to be newly incorporated into the display coordinate system from the classification target document; and each next layout A ninth step of calculating a position coordinate at which the document is initially arranged in the display coordinate system; and a sum of inter-document force vectors received from existing arranged documents for the newly arranged next arranged document A tenth step of calculating a force vector; an eleventh step of calculating a position coordinate at the next processing time according to the total inter-document force vector for the newly placed next-placed document; And a twelfth step of determining convergence of the position coordinates of the next arranged document during execution of the repeating process of the eleventh step and ending the repeating process. It is characterized by.

  By executing a series of steps, the classification target document is distributed so that the force to maintain the stable inter-document distance with other classification target documents in the display coordinate system is balanced. Since the stable inter-document distance is calculated according to the similarity between two documents to be classified, the distribution of the documents to be classified is classified objects with a high similarity between the documents to be classified close to each other. Documents are located far away.

If the transfer processing is simply performed for all the classification target documents at once, the amount of calculation becomes large when the number of classification target documents is large. In addition, there is a problem that when there are many classification target documents with low similarity to these classification target documents among classification target documents with high similarity, these classification target documents do not approach each other even if the moving process is repeated. Arise. However, the above-described problem can be avoided by first executing the movement process for a small number of classification target documents and then sequentially adding another classification target document and performing the movement process. Note that the ninth to twelfth steps may be both a method of performing all the documents in the time-arranged document at once and a method of sequentially performing each of the documents.
Another aspect of the document classification method of the present invention is a document classification method for classifying a plurality of classification target documents according to their contents, wherein a stable inter-document distance between each two documents of the classification target documents is determined. A first step of calculating according to the degree of similarity between the two documents, a second step of selecting an initially placed document from the classification target documents, and each of the initially placed documents is initially placed on a display coordinate system A third step of calculating position coordinates and a distance vector from one document to the other document on the display coordinate system at the time of the current processing is calculated between each two documents of the arranged initial arranged documents. Then, for each of the initially arranged documents arranged, the inter-document force vector received from some other initially arranged document based on the difference between the distance vector length and the stable inter-document distance and the direction of the separation vector. A fifth step of calculating a total inter-document force vector by summing the inter-document force vectors received from each of the other initial arranged documents for each of the arranged initial arranged documents; For each of the initially arranged documents arranged, the sixth step of calculating the position coordinates at the next processing time according to the total inter-document force vector and the execution of the repetition process of the fourth to sixth steps A seventh step of determining convergence of the position coordinates of the initially arranged document and terminating the repetition process; and an eighth step of selecting a plurality of next arranged documents to be newly incorporated in the display coordinate system from the classification target document. A ninth step of calculating a position coordinate that is initially arranged in the display coordinate system for one of the next arranged documents and arranging the position coordinate; A tenth step of calculating the total inter-document force vector by summing up the inter-document force vectors received from the existing arranged document, and the next arranged document arranged in the ninth step. For the eleventh step of calculating the position coordinates at the next processing time according to the total inter-document force vector, and the ninth step during the repetition of the tenth and eleventh steps. A twelfth step of determining the convergence of the position coordinates of the next arranged document and setting the position at this time as a provisional decision position of the next arranged document arranged in the ninth step; After the step is executed for all the next arranged documents selected in the eighth step, the repeating process in the fourth to seventh steps is performed for all the arranged documents. A thirteenth step to be executed and a fourteenth step to execute the eighth to thirteenth steps for the remaining classification target document.
According to another aspect of the document classification method of the present invention, each time a new document to be classified is added, provisional determination of the position of the additional document is performed, and the plurality of documents selected in the eighth step are performed. Every time the next arranged document is arranged, the reconstruction of the positions of all the arranged documents is executed, so that it is possible to prevent the calculation amount from increasing.
In the document classification method of the present invention, each of the classification target documents has a document number for identifying the document itself, and the documents of the classification target documents that the two documents cite the degree of similarity between the two documents in the first step. It is preferable to calculate using a number. According to this document classification method, classification target documents described in different languages can be targeted. Further, in this document classification method, it is preferable to regard the own document as one of the classification target documents cited by the own document. As a result, the fact that one of the two documents that are the evaluation target of the similarity quotes the other can be reflected in the calculation of the similarity.

  The preferred form of the present invention is a form obtained by adding any of the constituent elements in the dependent claims (any combination of constituent elements in the dependent claims) to the form specified by the independent claims in the claims. Including.

  It is possible to know in detail the positional relationship between documents in a plurality of classification target documents.

  Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. FIG. 1 is a block diagram showing an embodiment of a document classification apparatus according to the present invention. The document classification device 1 classifies a plurality of classification target documents according to the contents of each classification target document. The document classification device 1 includes a database 10, a stable inter-document distance calculation unit 22, an arrangement document selection unit 23, a position coordinate initial value setting unit 24, an inter-document force vector calculation unit 26, and a position coordinate update unit 28. The database 10 includes a classification target document DB 12, a stable inter-document distance DB 14, a position coordinate DB 16, and an inter-document force vector DB 18. The classification target document DB 12 stores a plurality of classification target documents in association with document codes that specify each document. The classification target document is stored in the classification target document DB 12 in advance, but can be input as necessary by an appropriate input unit.

  The stable inter-document distance DB 14 stores the stable inter-document distance calculated by the stable inter-document distance calculation unit 22 in association with the document code. FIG. 2 is a configuration diagram illustrating an example of the database of the inter-document distance DB 14. As shown in this figure, the stable inter-document distance between two documents is stored in association with the document codes (P0001, P0002,...). For example, in this case, the stable inter-document distance between the document (P0001) and the document (P0002) is 0.005.

  The position coordinate DB 16 stores the initial value of the position coordinate of each document set by the position coordinate initial value setting unit 24 and the position coordinate updated by the position coordinate update unit 28 in association with the document code. FIG. 3 is a configuration diagram illustrating an example of the database of the position coordinate DB 16. As shown in this figure, the position coordinates (X coordinate, Y coordinate) of each document are stored in association with the document code. For example, in this case, the position coordinates of the document (P0003) are (0.5155, 0.3417).

  The inter-document force vector DB 18 stores the total inter-document force vector calculated by the inter-document force vector calculation unit 26 in association with the document code. FIG. 4 is a configuration diagram illustrating an example of the database of the total inter-document force vector DB 18. As shown in this figure, the total inter-document force vector (FX, FY) working on each document is stored in association with the document code. For example, in this case, the total inter-document force vector of the document (P0002) is (0.007, -0.003).

  The stable inter-document distance calculation unit 22 calculates a stable inter-document distance between two documents for a plurality of classification target documents stored in the classification target document DB 12 according to the degree of similarity between the two documents. The stable inter-document distance decreases as the degree of similarity between both documents increases and decreases as the degree of similarity decreases.

The position coordinate initial value setting unit 24 sets the initial value of the position coordinate of each document on the two-dimensional coordinate plane. An example of an initial value setting method in the position coordinate initial value setting unit 24 will be described. For convenience of explanation, the number of documents to be classified is N (N is an integer of 2 or more), and each document is represented as T _i (i = 1, 2,..., N). First, the document _{T i} and the document _T j reads (j = 1,2, ···, N , j ≠ i) stable document distance _L 0 (i, j) between the in table _{L a.} After reading the stable inter-document distance L ₀ (i, j) for all (i, j) pairs, the average value L _avg of L ₀ (i, j) is obtained. Then, the position coordinates (X _i , Y _i ) of each document T _i are expressed by the following equation:
X _i = L _avg × rnd
Y _i = L _avg × rnd
Ask from. Here, rnd represents a random number. Thereby, the initial value of the position coordinate of each document is set. The stable inter-document distance L ₀ (i, j) is normalized by dividing by the average value L _avg .

  The inter-document force vector calculation unit 26 calculates a total inter-document force vector that works on each document. The total inter-document force vector is a vector sum of inter-document forces that each document receives from other documents. The inter-document force is an attractive force between the two documents when the distance on the coordinate plane obtained from the position coordinates of the two documents is larger than the above-mentioned inter-document distance, and conversely, the distance on the coordinate plane is This is a concept introduced on the assumption that a repulsive force acts between both documents when the distance between the documents is smaller. The magnitude of these forces increases as the absolute value of the difference between the distance on the coordinate plane and the inter-document distance increases, and decreases as the absolute value decreases. When the distance on the coordinate plane matches the stable inter-document distance, the inter-document force acting between the two documents is zero.

An example of a method for calculating the inter-document force vector in the inter-document force vector calculation unit 26 will be described. First, the distance L (i, j) between the document T _i and the document T _j is referred to as a processing time point (current processing time point) (in particular, in the present embodiment, the update of position coordinates is referred to as “current processing time point” and “next processing time point”). The “current processing time point” refers to the movement process (the process of calculating the total inter-document force vector and updating the position coordinates based on the total or part of each of the arranged documents is determined as the convergence of the position coordinates. In the repetitive processing of (repeating until a certain time), the time point at which a certain time starts is referred to, and the “next processing time point” indicates the time point at which the next time after the certain time starts). Based on the coordinates,
L (i, j) = {(X _i −Y _i ) ² + (X _j −Y _j ) ² } ^0.5
Ask from. Incidentally, the term "based on the position coordinates of the two in the processing time," as will be described later, the position coordinates are updated as required in each document T _i, always take the same value Because there is no. Next, the inter-document force f (i, j) between the document T _i and the document T _j is expressed by the following equation:
f (i, j) = (L ₀ (i, j) −L (i, j)) / (L ₀ (i, j) + ε1) ^α
Ask from. Here, ε1 is a constant to cope with when L ₀ (i, j) is 0, and is set to 1 × 10 ⁻¹² , for example. α is set so that the inter-document force f (i, j) increases exponentially as the stable inter-document distance L ₀ (i, j) decreases. By doing so, a greater inter-document force works when the similarity between documents is high. As a result, it becomes easy to form a group of similar documents, the position where the group is arranged is close to the human sense, and it can be easily converged even if the number of classified documents N increases. it can. When the number of classification target documents is relatively small (when N is less than 50), α is set to any value between 0.8 and 2.3. When N exceeds 100, it can be easily converged by setting α to any value of 1.8 to 2.2. In particular, when N = 101 to 3000, α = 2 is preferable. In particular, when mapping a document to be classified into a two-dimensional space, if α is smaller than the above range, there are many cases where the coordinates of some documents do not converge and diverge in the course of repeated movement processing. If it is larger, it becomes easier to form a uniform document group that does not reflect the contents of individual documents. α is set to any value between 0.8 and 2.3, for example, and is preferably 2. Next, the X component fX (i, j) and the Y component fY (i, j) of the inter-document force that the document T _i receives from the document T _j are expressed by the following equations:
fX (i, j) = f (i, j) × (X i -X j) / (L (i, j) + ε2) β
fY (i, j) = f (i, j) × (Y i -Y j) / (L (i, j) + ε2) β
Ask from. Here, ε2 is a constant to cope with L (i, j) being 0, for example, 1 × 10 ⁻¹² . Β is set to 0.5, for example. Finally, the X component FX _i and the Y component FY _i of the sum of the inter-document forces acting on each document T _i are expressed by the following equations:
FX _i = Σ _j fX (i, j)
FY _i = Σ _j fY (i, j)
Ask from. Here, Σ _j means taking the sum of all placed documents. The vector having FX _i and FY _i calculated in this way as components is the above-described total inter-document force vector.

The position coordinate update unit 28 updates the position coordinates of each document so that the absolute value of the total inter-document force vector calculated by the inter-document force vector calculation unit 26 becomes small. An example of the position coordinate update method in the position coordinate update unit 28 will be described. That is, the position coordinates (X _i , Y _i ) of each document T _i are expressed by the following equation based on the inter-document force vector (FX _i , FY _i ) calculated by the inter-document force vector calculation unit 26:
X _i ′ = X _i −k × FX _i
Y _i ′ = Y _i −k × FY _i
Updated by Here, (X _i ′, Y _i ′) represents the updated position coordinates. Further, k is a movement coefficient, for example, a constant not less than 1 × 10 ^{−23 and not} more than 1 × 10 ⁻²² . The above formula, each document T _i, in the direction of the document between the force vector, which means that is moved by a distance proportional to the magnitude of the absolute value of the vector. The updated position coordinates are stored in the position coordinate DB 16 and are overwritten on the position coordinates stored so far. Position coordinate update section 28 in the present embodiment, in conjunction with the updated coordinates, an average value ML of the movement distance of each document T _i the following formula,
ML = Σ {(k × FX _i ) ² + (k × FY _i ) ² } ^0.5
Ask from. This average value ML is used when determining the convergence condition by the convergence condition determination unit 30 described later.

  The document classification device 1 further includes a convergence condition determination unit 30, a display unit 32 (output unit), and an input unit 34. The convergence condition determination unit 30 determines the convergence condition after the position coordinates are updated by the position coordinate update unit 28. For example, it can be set as a convergence condition that the average value ML obtained by the position coordinate update unit 28 is equal to or less than a specified value. When the convergence condition is not satisfied, the convergence condition determination unit 30 causes the inter-document force vector calculation unit 26 to calculate the total inter-document force vector again using the updated position coordinates, and causes the position coordinate update unit 28 to The position coordinates are updated again using the total inter-document force vector. Therefore, the update of the position coordinates by the position coordinate update unit 28 is executed until the above convergence condition is satisfied.

Display unit 32, the convergence condition described above is satisfied, after the updating of the position coordinates by the position coordinate update section 28 has been completed, based on the determined position coordinates, relative position on the coordinate plane between the document T _i Visualize and display relationships. An example of a display method on the display unit 32 will be described. FIG. 5 is a diagram illustrating an example of a result display screen by the display unit 32. In this example, first, the display area 50 is divided into m × n cells (here, m = n = 4). Further, the maximum value (X _max , Y _max ) and the minimum value (X _min , Y _min ) of the X coordinate and Y coordinate that define the display area are input by the input unit 34 described later. In addition, without inputting these values, the maximum and minimum values of the X coordinate and the Y coordinate can be used as default values from the position coordinates of all documents that have already been determined. Next, the display part 32 calculates | requires the coordinate range corresponded to each cell from these input values. Then, the number of documents included in each cell is displayed as shown in FIG. For example, in this case, the number of documents included in the upper right cell is one. Further, in this example, an image of a document included in each cell is created, and the image is hyperlinked to each cell. As shown in FIG. 5, when the mouse pointer 52 is moved to a cell of interest, the documents included in the cell can be displayed as a corresponding document list. Here, a patent document such as a published patent publication is assumed as a classification target document, and the type of patent document and the publication number are displayed in the corresponding document list. In addition, since hyperlinks are pasted on these displays, for example, if a portion displayed as “JP-A-8-XXXXX” is clicked on the screen, the published patent gazette You can access the image and see its contents.

The input unit 34 is for inputting a display area or the like on a coordinate plane to be displayed by the display unit 32, and for example, a keyboard or a mouse is used. For example, in the example of FIG. 5, values of X _max , Y _max , X _min , and Y _min that define the display area 50 can be input from the input unit 34. The input information is passed to the display unit 32.

Next, the operation of the document classification apparatus 1 will be described, and an embodiment of the document classification method according to the present invention will be described. FIG. 6 is a flowchart showing the initial process and the process of arranging and moving the initially arranged document in the two-dimensional display coordinate system. First, the stable inter-document distance calculation unit 22 reads the classification target document stored in the classification target document DB 12, calculates the stable inter-document distance between the two documents, and calculates the calculated stable inter-document distance as the stable inter-document distance. The data is stored in the DB 14 (S61). Subsequently, the stable inter-document distance calculation unit 22 reads the stable inter-document distance stored in the inter-document distance DB 14 to calculate an average value (S62), and divides each stable inter-document distance by this average value. Is normalized and the data in the stable inter-document distance DB 14 is updated (S63). The arrangement document selection unit 23 selects int√N (a value obtained by rounding down the decimal point of the square root of the total number N of the classification target documents) as the initial arrangement document T _k that is the classification target document to be first arranged in the display coordinate system ( S64). The position coordinate initial value setting unit 24 sets the initial value of the position coordinate of each document using the average value, and stores the initial value of the set position coordinate in the position coordinate DB 16 (S65). Then, the inter-document force vector calculation unit 26 reads the stable inter-document distance stored in the inter-document distance DB 14 and the position coordinates stored in the position coordinate DB 16, and uses these values to calculate the total sum applied to each document. The inter-document force vector is calculated, and the calculated total inter-document force vector is stored in the inter-document force vector DB 18 (S66). Thereafter, the position coordinate update unit 28 reads the total document inter-force vector stored in the inter-document force vector DB 18, updates the position coordinates of each document based on the vector, and stores the updated position coordinates in the position coordinate DB 16. Store (S67). When the position coordinates are updated, the convergence condition determination unit 30 determines the convergence condition. If the convergence condition is not satisfied, the above steps (S66 to S67) are repeatedly executed. If the convergence condition is satisfied, the process proceeds to a process of adding a new classification target document.

  Then, the effect of this embodiment is demonstrated. In the document classification device 1, when determining the position coordinates of a plurality of classification target documents on the coordinate plane, the distance between the two documents on the coordinate plane is calculated by the stable inter-document distance calculation unit 22. If the distance is larger, the attractive force proportional to the difference acts between the two documents as the inter-document force. Conversely, if the distance on the coordinate plane is smaller than the stable inter-document distance, the repulsive force proportional to the difference is the inter-document force. When it is assumed that the document works between both documents, the vector sum of inter-document forces received by each document from other documents is calculated by the inter-document force vector calculation unit 26. Here, the inter-document force between the two documents increases as the distance between the two documents on the coordinate plane increases away from the inter-document distance calculated by the stable inter-document distance calculation unit 22. It is desirable to determine the position coordinates of each document so as to be small. Therefore, the position coordinate of each document is updated by the position coordinate update unit 28 so that the absolute value of the inter-document force vector becomes smaller. The update of the position coordinates is executed once or a plurality of times until a predetermined convergence condition is satisfied. When the update of the position coordinates is executed a plurality of times, before each update after the second time, based on the position coordinates of each document at that time, that is, the position coordinates after the previous update, the inter-document force vector calculation unit The calculation of the inter-document force vector by 26 is executed. Thus, the distance between the two documents on the coordinate plane can be brought close to the inter-document distance calculated by the stable inter-document distance calculation unit 22 while matching all the classification target documents. Therefore, according to the document classification apparatus 1 and the document classification method according to the present embodiment, the position coordinates of each document can be determined based on the inter-document distance calculated between the two documents. It becomes possible to know in detail the positional relationship between documents in the document.

  The document classification device 1 also includes a display unit 32. Thereby, the user can easily know the relative positional relationship between documents by viewing the display on the display unit 32. The document classification device 1 may be configured not to include the display unit 32. In this case, for example, an output unit that outputs the classification result may be provided instead of the display unit 32, and the output content may be displayed on an external display or printed by an external printer.

  In addition, the document classification device 1 includes an input unit 34 that can input the maximum value and the minimum value of the X coordinate and the Y coordinate that define the range displayed in the display area 50 (see FIG. 5). As a result, the user can display a desired range on the coordinate plane and know in detail the positional relationship between documents in the range.

  Note that the position coordinate update unit 28 preferably executes the update of the position coordinates until the absolute value of the inter-document force vector acting on each document becomes the minimum value obtained by summing all the documents to be classified. . In this case, the position coordinates of each document can be determined while maintaining particularly high consistency among all the classification target documents.

  FIG. 7 is a block diagram showing an example of the configuration of the stable inter-document distance calculation unit 22 in FIG. The stable inter-document distance calculation unit 22 includes a word extraction unit 70 that extracts words from various documents, and various databases 80 that store the words extracted by the word extraction unit 70.

  The word extraction unit 70 includes a keyword extraction unit 71 that extracts words from the key document as keywords, a reference word extraction unit 72 that extracts words from the reference document as reference words, and a search word that extracts words from the search document as search words. And an extraction unit 73. Here, the classification of “key document” and “search document” is convenient, and in the stable inter-document distance calculation unit 22, one of the two documents whose inter-document distance is desired to be obtained is the key document, and the other is Search document. The reference document is a document that is referred to when setting a keyword evaluation value, that is, a value representing the degree to which each keyword is uniquely included in the key document. As the reference document, for example, all the documents in the classification target document DB 12 (see FIG. 1) or a part of the documents in the classification target document DB 12 extracted in advance at random can be used. The reference document can be input to the stable inter-document distance calculation unit 22 as necessary by an appropriate input unit. Further, the stable inter-document distance calculation unit 22 includes storage means (not shown) for storing a reference document.

  Each of the extraction units 71 to 73 has a function of extracting words in a document using hiragana, punctuation marks, special symbols, and spaces as delimiters or using a morphological analysis tool or the like in Japanese. In addition, the extraction units 71 to 73 collate words cut out from the document with words already cut out from the same document so that words are not extracted redundantly from one document, and only the words that do not match are extracted. Has a function to extract. In addition, the extraction units 71 to 73 extract words in a document by using special symbols and / or spaces as delimiters or using a morphological analysis tool or the like in a language in which alphabets such as English are used. It has the function to do.

  The database (DB) 80 includes a keyword DB 81, an all word DB 82, an evaluation value DB 83, a search word DB 84, and a similarity DB 85. The keyword DB 81 stores keywords extracted from the key document. The keyword is stored in association with the key document code that identifies the key document that is the extraction source. The all word DB 82 stores a keyword extracted from the key document and a reference word extracted from the reference document. The keyword and the reference word are stored in association with the key document code that specifies the key document that is the extraction source and the reference document code that specifies the reference document. The evaluation value DB 83 stores an evaluation value calculated by a keyword evaluation value calculation unit 91 described later. The search word DB 84 stores search words extracted from the search document. The search word is stored in association with a search document code that specifies a search document as an extraction source. The similarity DB 85 stores the similarity calculated by the similarity calculation unit 92 described later.

  Note that the keyword, reference word, and search word may be extracted from the entire document to be extracted, or may be extracted from a part thereof. For example, if the document to be extracted is a patent document, the extraction range may be limited to bibliographic items, summaries, claims, or examples. In particular, when the data amount is limited, it is effective to narrow the extraction range to a part of the document. In addition, the reference word is extracted from a part of the reference document, the keyword and the search word are extracted from the entire key document and the search document, respectively. Can be adjusted.

  The stable inter-document distance calculation unit 22 includes a keyword evaluation value calculation unit 91, a similarity calculation unit 92, and an inter-document distance calculation unit 93. The keyword evaluation value calculation unit 91 has a function of calculating an appearance rate at which a common keyword appears in all documents including the key document and the reference document. When there are N reference documents and a common keyword exists in B of them, the keyword appearance rate in all documents is calculated as B / (1 + N). The keyword evaluation value calculation unit 91 searches the keywords and reference words stored in the all-word DB 82, and calculates how many reference words are the same as the same keyword and keyword. Here, since the “reference word” is a name given to the word extracted from the reference document for convenience, the “reference word identical to the keyword” means a keyword included in the reference document. The keyword appearance rate in all documents is calculated by dividing the calculated number of keywords by the number of all documents. Further, the keyword evaluation value calculation unit 91 has a function of calculating a keyword evaluation value by taking the reciprocal of the keyword appearance rate in all documents. That is, the keyword evaluation value is calculated by (1 + N) / B and indicates the degree to which each keyword is uniquely included in the key document.

  The similarity calculation unit 92 adds the evaluation values of all keywords included in the search document, and divides the added value by the number of keywords included in the search document, whereby the key document and the search document are similar. It has a function of calculating the degree of similarity representing the degree. Further, the similarity calculation unit 92 stores the calculated similarity in the similarity DB 85.

The inter-document distance calculation unit 93 has a function of calculating a stable inter-document distance L ₀ (i, j) between the document T _i and the document T _j using the similarity stored in the similarity DB 85. Here, the stable inter-document distance L ₀ (i, j) is expressed by the following equation:
L ₀ (i, j) = 2 / (S _ij + S _ji )
It is requested from. Here, S _ij represents the similarity when the document T _i is the key document and the document T _j is the search document. S _ji is the document T _j is the key document and the document T _i is the search document. Represents the degree of similarity. That is, the above expression means that the average value of the similarity calculated by switching the relationship between the key document and the search document is taken between the document T _i and the document T _j, and further, the inverse of the average value is taken. is doing. The _{reason why} the average value of similarity calculated by switching the relationship between the key document and the search document is used is that S _ij and S _ji do not necessarily match. The stable inter-document distance L ₀ (i, j) calculated in this way decreases as the similarity between the two documents increases, and increases as the similarity decreases.

  FIG. 8 is a flowchart showing a process for calculating a stable inter-document distance (a subroutine of the stable inter-document distance calculating step (S61) in FIG. 6). First, the keyword extraction unit 71 extracts keywords from the key document, and stores the extracted keywords in the keyword DB 81 (S81). Further, the reference word extraction unit 72 extracts the reference word from the reference document, and stores the extracted reference word in the all word DB 82 (S82). Note that the all words DB 82 also stores the keywords extracted by the keyword extraction unit 71. Next, the keyword evaluation value calculation unit 91 reads the keywords and reference words stored in the all-word DB 82, calculates the evaluation value of each keyword, and stores the evaluation value in the evaluation value DB 83 (S83). Further, the inter-document distance calculation unit 93 extracts a search word from the search document, and stores the extracted search word in the search word DB 84 (S84). Next, the similarity calculation unit 92 reads the evaluation value stored in the evaluation value DB 83 and the search word stored in the search word DB 84, calculates the similarity between the key document and the search document, The similarity is stored in the similarity DB 85 (S85). Finally, the inter-document distance calculation unit 93 reads the similarity stored in the similarity DB 85 and calculates the stable inter-document distance between each document (S86).

According to the stable inter-document distance calculation unit 22 of the present exemplary embodiment, the stable inter-document distance between two documents is calculated using an evaluation value indicating the degree to which each keyword is inherently included in the key document. A stable inter-document distance that reflects the degree of similarity with high accuracy can be obtained. Note that the stable inter-document distance is not limited to the one calculated by the calculation method shown in this embodiment, and is calculated as a distance between vectors such as word vectors as described in Patent Documents 1 and 2, for example. It may be a thing. However, in order to accurately reflect the degree of similarity between the two documents, it is preferable to use the calculation method shown in this embodiment.
As another embodiment of the process for calculating the stable inter-document distance when the present invention is applied to the classification display of patent documents, a method using duplicate citations can be considered. FIG. 19 is a diagram for assisting the description of the embodiment using the duplicate citations. FIG. 20 is a flowchart showing the processing in this embodiment. First, a document cited by duplicating the document T _i and the document T _j is detected (S201). For example, as shown in FIG. 19, the US6713520B2 the document _{T i,} the document _{T j} of US6433090B1. The document T _i, 3 single documents are cited (but is also self-document treated as references.). 23 documents are cited in the document T _j (however, the document itself is also treated as a cited document). Of these, only US6433090 (document T _j ) is detected as a duplicate citation. Next, the evaluation value of the double cited document US6433090 is calculated (S202). More specifically, the reciprocal of the number of documents classified as other classification target documents is used as the evaluation value. For example, the classification target document cites duplicate references US6433090 is assuming there is only one addition to document _{T i,} the evaluation value of the duplicate references US6433090 becomes 1/2 = 0.5. Next, the similarity between the document T _i and the document T _j is calculated on the basis of the evaluation value of the duplicate cited document calculated in this way (S203). Specifically, the value obtained by adding the evaluation values of the overlapping cited documents is divided by the sum of the number of cited documents of the document T _{i and} the number of cited documents of the document T _j is set as the similarity. In this example, the only cited reference is US6433090, and its evaluation value is 0.5. Therefore, the value obtained by adding the evaluation values of the cited references is 0.5. The sum of the number of documents cited in the document T _{i and} the number of documents cited in the document T _j is 3 + 23 = 26. Therefore, the similarity between the document T _i and the document T _j is 0.5 / 26≈0.019. Finally, a stable inter-document distance between the document T _i and the document T _j is calculated based on the similarity (S204). Specifically, the reciprocal of the similarity (26 / 0.5 = 52) is set as the stable inter-document distance. In this embodiment, the reciprocal of the number of other classification target documents that cite the duplicate citation is used as the evaluation value. However, in this method, the number of classification target documents is less than 100 (preferably less than 50). It is particularly useful in the case of. Instead, when the number of classification target documents is less than 2,000, the reciprocal of the square root of the number of other classification target documents quoting duplicate citations can be used as the evaluation value. Moreover, when the number exceeds 100, it is desirable to fix the evaluation value to 1. In order to shorten the processing time in S201, it is conceivable to prepare a table indicating the document number of its own document and the document number of another classification target document that cites it in advance for each classification target document.

  FIG. 9 is a flowchart showing a subroutine of the total inter-document force vector calculation step (S66) of FIG. First, the inter-document force vector calculation unit 26 reads the position coordinates of each document stored in the position coordinate DB 16, and calculates the distance on the coordinate plane between the two documents (the length of the separation vector) from the position coordinates. (S91). The inter-document force vector calculation unit 26 reads the stable inter-document distance stored in the inter-document distance DB 14 and calculates the inter-document force using the stable inter-document distance and the distance calculated in the previous step S91. (S92). Further, the inter-document force vector calculation unit 26 calculates the X component and the Y component of the inter-document force based on the separation vector (S93), and calculates the sum of the inter-document forces working from other arranged documents for a certain document. By calculating as a vector sum, a total inter-document force vector is calculated (S94). Then, when the total document inter-force vector is calculated for all the arranged documents, the flow ends. When there is a document for which the total inter-document force vector is not calculated, the above steps (S91 to S94) are performed. Repeated (S95).

  FIG. 10 is a flowchart showing a subroutine of the position coordinate update step (S67) of FIG. First, the position coordinate update unit 28 reads an inter-document force vector stored in the inter-document force vector DB 18, and moves each document, that is, changes the position coordinate according to the vector (S101). Thereafter, the position coordinate update unit 28 calculates an average value of the moving distances of the respective documents used for determining the convergence condition (S102). In S <b> 68, the convergence condition can be that the average value of the movement distance is less than the threshold value. Alternatively, the convergence condition may be that the position coordinate update step is repeated int√N times.

  FIG. 11 is a flowchart showing processing for adding an additional arrangement document to the display coordinate system. Referring to FIG. 11, after the arrangement / movement process of the initial arrangement document shown in FIG. 6 is completed, additional arrangement documents are sequentially added to complete the arrangement / movement of all the classification target documents. Will be explained.

  The arrangement document selection unit 23 randomly selects the next arrangement document to be added to the display coordinate system int (mm / 10) (where mm is the number of classification target documents already arranged in the display coordinate system). (S111). However, when the remaining number of classification target documents is less than int (mm / 10), all the remaining classification target documents become time-arranged documents. The number of time-arranged documents added immediately after the arrangement / movement process of the initial arrangement document is int {(int√N) / 10}.

The position coordinate initial value setting unit 24 calculates the position coordinates on the display coordinate system where the time placement document is first installed (S112). In the present embodiment, the time-arranged document is initially set so as to be positioned in the vicinity of the arranged classification target document having the shortest stable inter-document distance. Specifically, the position coordinate initial value setting unit 24 refers to the stable inter-document distance DB 14 to obtain c where L ₀ (c, mm + k) is the minimum value (where c = 1 to mm). The initial value of the position coordinates of the arrangement document T _k is (X _k , Y _k ) = (X _c + ε, Y _c + ε) (ε: constant). Instead of the above, the initial value of the time-arranged document may be determined by a random number as in the case of the initial-arranged document.

  After the position coordinates of a certain time-arranged document are set to initial values, the inter-document force vector calculation unit 26 calculates the current total inter-document force vector received by the time-arranged document from other arranged classification target documents ( S113). The position coordinate update unit 28 updates the position coordinates of the time-arranged document based on the total inter-document force vector (S114). The convergence condition determination unit 30 determines the convergence of the position coordinates of the time-arranged document when the current movement amount of the time-arranged document is equal to or smaller than the threshold value or when the processes of S113 to S115 are executed a predetermined number of times ( S115). If convergence is not determined, the processing of S113 to S115 is repeated again for the time-arranged document.

  The processes of S112 to S115 are sequentially performed for other documents among the time-arranged documents. When the arrangement / movement processing is completed for all the documents in the time-arranged document, the position calculation (processing in S66 to S68) is performed for all the arranged documents including the time-arranged document added to the display coordinate system this time. This is performed N times (S117). In this way, all the time-arranged documents are arranged at a time and moved (the process of calculating the total inter-document force vector and updating the position coordinates based on the total or part of the arranged documents is performed using the position coordinates. Instead of repeating the process until the convergence is determined, the position coordinates of all the time-arranged documents are processed one by one by sequentially placing and moving the time-arranged documents one by one while fixing the position coordinates of the other arranged documents. , And the placement / movement process for all the arranged documents including the current time-arranged document is performed, whereby the number of repetitions of the movement process can be reduced. The processing of S111 to S117 is performed on the unallocated classification target document. However, when there is no unallocated classification target document, the arrangement / movement process ends at this point.

  FIG. 12 is a flowchart showing a subroutine of the result display step (output step) in FIG. First, the display unit 32 divides the display area into m × n cells (S121). Here, the maximum value and the minimum value of the X coordinate and the Y coordinate defining the display area are input by the input unit 34 (S122). This input is performed by the user. Next, the display unit 32 calculates a coordinate range corresponding to each cell based on the above-described value input from the input unit 34 (S123). Then, the display unit 32 displays the number of documents having position coordinates within the coordinate range of each cell in the display area (S124). The display unit 32 creates an image of the document included in each cell (S125) and hyperlinks the image of the document to each cell (S126).

  FIGS. 13A and 13B are diagrams for explaining a modification of the result display by the display unit 32 of FIG. The display area 50 shown in the figure corresponds to FIG. In this example, by designating a part of the display area 50 as a new display area, the part can be displayed again on the entire display area 50. For example, if four cells in the center (the outer frame is indicated by a thick line) are designated in FIG. 13A, the designated portion is re-displayed in the entire display area 50 as shown in FIG. 13B. Is displayed. At this time, since the number of cells in the display area 50 is unchanged, the designated portion is divided into finer cells. For example, the cell in which the number of documents is displayed as “5” in FIG. 13A corresponds to the upper right four cells in FIG. Therefore, the sum of the number of documents in the four cells is 5. The designation of the display area can be performed, for example, by inputting coordinate values to the input unit 34 in FIG. 1 or by selecting with a mouse on the screen.

  FIG. 14 is a diagram for explaining a modified example of the result display by the display unit 32 of FIG. In this example, the display unit 32 plots and displays the position coordinates of each document in the display coordinate system (two-dimensional display coordinate system) in the plot area 54p in the display area 54d. Each plot 56 has a text box 53 (“text box” having a certain shape and size for displaying the attributes of the plotted document so that the corresponding document can be identified. This is a small area, but it is also possible to set text boxes of several different shapes or sizes depending on the display amount of attribute information. In order to prevent the text box 53 from protruding from the display area 54d, the plot area 54p corresponds to the size of the text box 53 from the display area 54a (when a text box having a plurality of shapes or sizes is set, It is reduced inward by the length of the long vertical or horizontal diameter. That is, the area surrounded by the dotted line located at each corner of the display area 54 a and the frame of the display area 54 a has the same size and shape as the text box 53. Here, an open patent publication is assumed as a document to be classified, and an application number is displayed as the document number. Further, a hyperlink is pasted on the displayed text box 53 or the document number, and the document image can be accessed by clicking the document number on the screen. In addition to the document number, the text box 53 can display the name of the invention, the applicant, and a keyword cut out from the summary, which makes it easier to grasp the classification contents.

  FIG. 15 shows a flowchart according to a modification of FIG. First, the user inputs the maximum value and the minimum value of the X coordinate and the Y coordinate that define the display area 54a (S151). This input can be performed from the input unit 34 of FIG. The display unit 32 sets the plot area 54p (S152). The display unit 32 plots the position coordinates of each document in the plot area 54p, and displays the text box 53 in association with the plot 56 (S153). Further, the display unit 32 hyperlinks the document image to each plot (S154). In the display example of FIG. 14, a partial area of the display is specified, and this is enlarged and displayed as a new display area, or one point of the display area, for example, a text box at the center of the area is specified with the mouse pointer. It is possible to display an enlarged / reduced display around this. Also, by copying the contents of one or more designated text boxes onto a worksheet such as spreadsheet software, the work following the classification can be made easier.

  FIG. 16 is a diagram for explaining a modification of the result display by the display unit 32 of FIG. In this example, the display unit 32 displays a document having a position coordinate within a display radius on the coordinate plane as a corresponding document with the position coordinate of the reference document designated by the user as a base point. Designation of the reference document and the display radius can be performed from the input unit 34 in FIG. The reference document is selected from the classification target documents stored in the classification target document DB 12. In FIG. 16, the corresponding document list is displayed on the right side in the display screen 57. Hyperlinks are pasted on these displays. Here, there are four documents within the display radius from the reference document. In addition, this list is sorted and displayed in order from the shortest distance from the reference document. Further, in this example, a display area 58 is provided on the left side in the display screen 57. In the display area 58, the position coordinates of each document are plotted with the reference document as the center, and a circle 59 having the display radius as the center with the reference document as the center is displayed. This circle 59 can be used as a guide when redesignating the display radius. The numbers attached to each plot correspond to the numbers in the corresponding document list. According to this example, a document similar to the reference document can be searched. Further, in this case, by displaying the reference document in a so-called highlight display in which the color or font is changed, it becomes easy to grasp the positional relationship between the target reference document and a similar document.

  FIG. 17 shows a flowchart according to a modification of FIG. First, the user inputs a reference document and display deformation from the input unit 34 in FIG. 1 (S171, S172). Then, the display unit 32 reads the position coordinates of each document stored in the position coordinate DB 16, and displays the documents located within the display radius from the reference document as a corresponding document list (S173). Further, the display unit 32 hyperlinks the image of the document displayed in the corresponding document list (S174). Here, the user accesses the image of the document displayed by following the hyperlink as necessary, and confirms the content (S175). When the search radius is specified again and the search is performed again, the above steps (S172 to S175) are repeated, and when the search is not performed again, the flow is terminated (S176).

  Finally, the hardware configuration of the document classification device 1 will be described with reference to FIG. FIG. 18 is a block diagram showing a hardware configuration of the document classification device 1 of FIG. As shown in FIG. 18, the document classification device 1 physically includes a control device 1a, a memory 1b, a storage device 1c, an input device 1d, and a display device 1e. These devices are electrically connected to each other via a bus 1f so that various signals can be input and output.

  Specifically, the control device 1a is, for example, a CPU (Central Processing Unit), and the memory 1b is a volatile semiconductor memory such as a RAM (Random Access Memory). The storage device 1c is a non-volatile magnetic disk such as an HDD (Hard Disc Drive). The input device 1d is, for example, a keyboard or a mouse, and the display device 1e is an LCD (Liquid Crystal Display) or a CRT (Cathode Ray Tube) display.

  The correspondence between the hardware configuration and the functional configuration is shown below. Regarding the document classification device 1, the functions of the database 10 are realized by the storage device 1c as a physical component. Each function of the stable inter-document distance calculation unit 22, the position coordinate initial value setting unit 24, the inter-document force vector calculation unit 26, the position coordinate update unit 28, and the convergence condition determination unit 30 is executed by the control device 1a. It is realized by doing. Each function of the input unit 34 is realized by the input device 1d. In addition, each function which the display part 32 has is implement | achieved by the control apparatus 1a and the display apparatus 1e. That is, the control device 1a performs a predetermined calculation to determine the display content of the classification result, and the display device 1e displays the classification result according to the content.

  The document classification apparatus and the document classification method according to the present invention are not limited to the above-described embodiments, and various modifications can be made. For example, although the configuration in which the position coordinates of each document are determined on a two-dimensional coordinate plane is shown, the coordinate plane may be one-dimensional. At this time, each document has position coordinates on one straight line. In this case, too, it is referred to as a one-dimensional “coordinate plane” for convenience. Alternatively, the position coordinates of each document may be determined by extending to three or more dimensions.

  Further, although the convergence condition is that the average value of the moving distance of each document is equal to or less than a specified value, the convergence condition is not limited to this. For example, the convergence condition may be that the maximum value of the moving distance of each document is not more than a specified value.

  Further, the movement coefficient k used for updating the position coordinates does not always need to be a constant value. After the convergence has progressed to some extent, the movement coefficient k may be adjusted depending on whether the average value of the movement distance of each document is increased or decreased in order to increase the convergence speed. For example, if the average value of the movement distance is larger than that after the previous update, k ′ = k × 0.01 (k ′: movement coefficient after addition / subtraction), and if it is smaller, k ′ = k × 1.03.

  It can show so that the relationship of the similarity between several patent documents can be recognized visually.

It is a block diagram which shows one Embodiment of the document classification device by this invention. It is a block diagram which shows an example of the database of inter-document distance DB14. It is a block diagram which shows an example of the database of position coordinate DB16. It is a block diagram which shows an example of the database of document force vector DB18. It is a figure which shows an example of the result display screen by the display part. It is a flowchart which shows the process which arrange | positions and moves an initial arrangement document in an initial process and a two-dimensional display coordinate system. FIG. 2 is a block diagram illustrating an example of a configuration of a stable inter-document distance calculation unit 22 in FIG. 1. It is a flowchart which shows operation | movement of the stable document distance calculation part 22 of FIG. It is a flowchart which shows the subroutine of the total document inter-force vector calculation step (S66) of FIG. It is a flowchart which shows the subroutine of the update step (S67) of the position coordinate of FIG. It is a flowchart which shows the process which adds an additional arrangement | positioning document to a display coordinate system. It is a flowchart which shows the subroutine of the result display step of FIG. (A) And (b) is a figure for demonstrating the modification of the result display by the display part 32 of FIG. It is a figure for demonstrating the modification of the result display by the display part of FIG. 15 shows a flowchart according to a modification of FIG. It is a figure for demonstrating the modification of the result display by the display part of FIG. FIG. 17 shows a flowchart according to a modification of FIG. It is a block diagram which shows the hardware constitutions of the document classification device 1 of FIG. It is a figure for assisting description of embodiment which calculates the distance between stable documents using a duplication reference document. It is a flowchart which shows the process in embodiment which calculates the distance between stable documents using a duplication reference document.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Document classification apparatus, 10 ... Database, 12 ... Classification object DB, 14 ... Inter-document distance DB, 16 ... Position coordinate DB, 18 ... Inter-document force vector DB, 22 ... Stable inter-document distance calculation part, 23 ... Arrangement Document selection unit, 24 ... Position coordinate initial value setting unit, 26 ... Inter-document force vector calculation unit, 28 ... Position coordinate update unit, 30 ... Convergence condition determination unit, 32 ... Display unit, 34 ... Input unit, 53 ... Text box 54a ... display area, 54p ... plot area, 56 ... plot.

Claims (20)

A document classification method for classifying a plurality of documents to be classified according to their contents,
A first step of calculating a stable inter-document distance between each two documents of the classification target document according to the degree of similarity between both documents;
A second step of selecting an initially arranged document from the classification target documents;
A third step of calculating position coordinates where each of the initial placement documents is initially placed on a display coordinate system;
A distance vector from one document on the display coordinate system to the other document at the time of the current processing is calculated between each two documents of the arranged initial arranged documents, and the arranged initial arranged documents are calculated. A fourth step of calculating an inter-document force vector received from a certain other initial arrangement document based on a difference between a length of the separation vector and the stable inter-document distance and a direction of the separation vector;
A fifth step of calculating a total inter-document force vector by summing up inter-document force vectors received from each other initial-arranged document for each of the initially arranged documents;
A sixth step of calculating the position coordinates at the next processing time according to the total inter-document force vector for each of the arranged initial arranged documents;
A seventh step of determining convergence of the position coordinates of the initially arranged document during execution of the repetition process of the fourth to sixth steps and terminating the repetition process;
An eighth step of selecting a next layout document to be newly incorporated into the display coordinate system from the classification target document;
A ninth step of calculating a position coordinate at which each next placement document is initially placed in the display coordinate system;
A tenth step of calculating a total document inter-force vector by summing up inter-document force vectors received from existing arranged documents for the newly arranged next-arranged document;
An eleventh step of calculating the position coordinates at the next processing time in accordance with the total inter-document force vector for the newly placed next-placed document;
A document classification method comprising: a twelfth step of determining convergence of position coordinates of the next arranged document during execution of the repetition processing of the tenth and eleventh steps and ending the repetition processing. . In the fourth step,
The length of the inter-document force vector depends on the absolute value of the difference between the distance vector length and the stable inter-document distance.
The direction of the inter-document force vector is the same direction as the separation vector or the opposite direction, and the direction of the separation vector is drawn toward the other initial arrangement document when the length of the separation vector is larger than the stable inter-document distance. 2. The document classification method according to claim 1, wherein when the length of the separation vector is smaller than the stable inter-document distance, the document classification method is repelled by the other initial arranged document. In the seventh step,
When the number of classification target documents is N,
2. The document classification method according to claim 1, wherein convergence is determined when the fourth to sixth steps are repeated N times. The document classification method according to claim 1, wherein the eighth to twelfth steps are repeated for the next arranged document. When the number of classification target documents is N, the number of the initially arranged documents is not less than √N and not more than (√N + 100).
When the number of the classifying target document disposed in the display coordinate system previously with N _k, claims, characterized in that the number of next placement document than 1 times 0.01 times the N _k 4. The document classification method according to 4. Steps 10 to 12 are sequentially performed on the next arranged document one by one.
In the twelfth step,
2. The document classification method according to claim 1, wherein convergence is determined when the total inter-document force vector calculated in the eleventh step is less than or equal to a threshold value for the time-arranged document being processed. In the ninth step,
The document classification method according to claim 6, wherein the position coordinates at which each of the next arranged documents is initially arranged in the display coordinate system are determined by random numbers. In the ninth step,
7. The document classification method according to claim 6, wherein a position coordinate at which each next arranged document is initially arranged in the display coordinate system is set to a neighborhood of a previously arranged document having the smallest stable inter-document distance. . The tenth to twelfth steps are sequentially performed on the next arranged document one by one, and then the repetition process in the fourth to seventh steps is executed a predetermined number of times for all the arranged documents including the next arranged document. The document classification method according to claim 1. The document classification method according to claim 1, wherein the initial arrangement document is randomly selected from the classification target documents. A mark of the converged position coordinates of the classification target document on the display coordinate system is plotted in a plot area in the display area of the display means, and a text box including a label of each of the plotted classification target documents is associated with the mark Step to display in the display area,
The document classification method according to claim 1, wherein the plot area is reduced inward by a size of the text box from a frame of the display area. A document classification method for classifying a plurality of documents to be classified according to their contents,
A first step of calculating a stable inter-document distance between each two documents of the classification target document according to the degree of similarity between both documents;
A second step of selecting an initially arranged document from the classification target documents;
A third step of calculating position coordinates where each of the initial placement documents is initially placed on a display coordinate system;
A distance vector from one document on the display coordinate system to the other document at the time of the current processing is calculated between each two documents of the arranged initial arranged documents, and the arranged initial arranged documents are calculated. A fourth step of calculating an inter-document force vector received from a certain other initial arrangement document based on a difference between a length of the separation vector and the stable inter-document distance and a direction of the separation vector;
A fifth step of calculating a total inter-document force vector by summing up inter-document force vectors received from each other initial-arranged document for each of the initially arranged documents;
A sixth step of calculating the position coordinates at the next processing time according to the total inter-document force vector for each of the arranged initial arranged documents;
A seventh step of determining convergence of the position coordinates of the initially arranged document during execution of the repetition process of the fourth to sixth steps and terminating the repetition process;
An eighth step of selecting a plurality of next arranged documents to be newly incorporated into the display coordinate system from the classification target documents;
A ninth step of calculating and arranging position coordinates initially arranged in the display coordinate system for one of the next arranged documents;
A tenth step of calculating a total inter-document force vector by summing up inter-document force vectors received from existing arranged documents for the next-arranged document newly arranged in the ninth step;
An eleventh step of calculating position coordinates at the next processing time in accordance with the total inter-document force vector for the next arranged document newly arranged in the ninth step;
During the execution of the repeating process of the tenth and eleventh steps, the convergence of the position coordinates of the next arranged document arranged in the ninth step is determined, and the repeating process is terminated at this time. A twelfth step in which the position at is a provisionally determined position of the next arranged document arranged in the ninth step;
After executing the ninth to twelfth steps for all the next arranged documents selected in the eighth step, the thirteenth step for executing the repeating process in the fourth to seventh steps for all the arranged documents. When,
A document classification method comprising: a fourteenth step of executing the eighth to thirteenth steps for the remaining classification target document. Each classification target document has a document number for identifying its own document,
The document according to any one of claims 1 to 12, wherein a degree of similarity between both documents in the first step is calculated using a document number of the classification target document cited by both documents. Classification method. A value obtained by dividing the number of documents to be classified cited in both documents in the first step by the sum of the number of citations in each of the two documents is set as a value representing the degree of similarity between the two documents. The document classification method according to claim 13, wherein: The reciprocal of the number of classification target documents that cite a certain classification target document is used as the evaluation value of the classification target document,
A value representing a degree of similarity between the two documents obtained by dividing the sum of the evaluation values of the classification target documents cited by both documents in the first step by the sum of the number of citations in each of the documents; The document classification method according to claim 13, wherein: 16. The document classification method according to claim 13, wherein the document is regarded as one of the classification target documents cited by the document. The classification target document is a patent document,
The classification object document cited in a foreign patent document related to a foreign patent application for which priority is claimed based on the own document is regarded as one of the classification object documents cited by the own document. The document classification method according to any one of 13 to 15. 18. The display unit displays only the classification target document located within a range of a threshold distance on the display coordinate system from the specified classification target document. 18. Document classification method. 181. A document classification program for causing a computer system to execute the steps according to any one of claims 1 to 181. A document classification device for classifying a plurality of classification target documents according to their contents,
Means for executing a first step of calculating a stable inter-document distance between each two documents of the classification target documents according to the degree of similarity between the two documents;
Means for executing a second step of selecting an initially arranged document from the classification target documents;
Means for performing a third step of calculating position coordinates at which each of the initial placement documents is initially placed on a display coordinate system;
A distance vector from one document on the display coordinate system to the other document at the time of the current processing is calculated between each two documents of the arranged initial arranged documents, and the arranged initial arranged documents are calculated. Means for performing a fourth step of calculating an inter-document force vector received from some other initial placed document based on a difference between a length of the separation vector and the stable inter-document distance and a direction of the separation vector;
Means for performing a fifth step of calculating a total inter-document force vector by summing up inter-document force vectors received from each other initial-arranged document for each of the initially arranged documents;
Means for executing a sixth step for calculating the position coordinates at the next processing time in accordance with the total inter-document force vector for each placed initial placed document;
Means for determining a convergence of the position coordinates of the initially arranged document during execution of the repetition process of the fourth to sixth steps, and executing a seventh step of ending the repetition process;
Means for executing an eighth step of selecting a next layout document to be newly incorporated into the display coordinate system from the classification target document;
Means for performing a ninth step of calculating a position coordinate at which each next placement document is initially placed in the display coordinate system;
Means for executing a tenth step of calculating a total inter-document force vector by summing up inter-document force vectors received from existing arranged documents for the newly arranged next-arranged document;
Means for executing an eleventh step of calculating position coordinates at the next processing time in accordance with the total inter-document force vector for the newly arranged next arranged document;
Means for executing a twelfth step of determining the convergence of the position coordinates of the next arranged document during the execution of the repeating process of the tenth and eleventh steps and ending the repeating process. Document classification device.

Images