JPH1115835A - Sorting information presenting device and medium recording sorting information presenting program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To grasp how to change or transit the distribution and overall tendency of an information group in accordance with a different period to be sorted. SOLUTION: A document storing means 1 stores plural documents la to 1c,... to which information generation time is applied. A specification storing means 3 stores a sorting specification including a retrieving expression and a period to be sorted which are inputted from an input device 2. A retrieving means 4 retrieves a document suited to the retrieving expression stored in the means 3 among the documents to which information generation time within the period to be sorted stored in the means 3 is applied. The detected document is transferred to a sorting means 5. The means 5 sorts the document detected by the means 4 in accordance with similarity. A sorting history storing means 6 stores the sorting result of the means 5 together with sorting specification. A sort presenting means 7 displays plural sorting history 8a to 8c stored in the means 6 on the screen of a display device 8.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a classification information presenting apparatus and a medium storing a classification information presenting program, and more particularly to a classification information presenting apparatus for presenting an outline of the distribution of information groups and the like and presenting such information to a computer. The present invention relates to a medium recording a classification information presentation program to be executed.

[0002]

2. Description of the Related Art There is a demand for knowing the tendency of a huge amount of information. For example, by collecting research papers and classifying their contents, it is possible to determine what research issues are receiving attention. To make such a decision accurately, a large amount of information must be analyzed. It would take too much time if the work was done manually by humans. Therefore, a technique for classifying a large amount of information and presenting the distribution state of the information to a user has been developed. Examples include the following:

[0003] First, there are some which are classified into fixed classifications given in advance. This is good when the information is surely well within the prescribed classification frame by limiting the field, but it is not suitable for the case where the distribution of topics always changes, such as newspaper articles.

To solve this problem, there is a classification search method based on vector similarity. This categorizes, presents, and selects documents by word vectors contained in the content,
By narrowing down the selected ones, narrowing down is sequentially performed. As a result, it is not necessary to set the classification in advance, and the classification can be performed with the appropriate classification item at that time according to the transition of the topic. However, the classification result is displayed only in a list, and it is difficult to grasp the tendency of information at a certain point in time. Also, it is difficult to grasp the transition of the trend.

[0005] Therefore, in the classification, there is an object which aims to grasp the tendency of the information group by arranging information in a two-dimensional space and arranging information having high similarity close to each other. . This makes it easy to grasp the whole image of the distribution.

[0006] Further, a device that performs classification based on viewpoints (for example, Japanese Patent Application No. 7-178778, "Information search device")
There is. Unlike other methods that classify based on a single classification criterion (the same words are used), this method considers differences in the relationship between words Provide a way. Also, using a thesaurus, even if different words are used in different documents, they can be classified into the same classification.

[0007]

However, according to the prior art, it is possible to grasp the tendency of the information group whose contents are fixed. However, when the contents of the information group change every moment, the tendency becomes longer. There is a problem that it is difficult to grasp the transition status of how it changes according to.

The present invention has been made in view of such a point, and a classification information presenting apparatus capable of grasping how the distribution and overall tendency of an information group changes and changes according to different classification target periods. The purpose is to provide.

[0009]

According to the present invention, in order to solve the above-mentioned problems, in a classification information presentation device for presenting a distribution state of an information group, a document holding means for holding a document given an information generation time; A specification holding unit that holds a classification specification including a search expression and a classification search target period; and an information generation time within the classification target period that matches the search expression held by the specification holding unit and is held by the specification holding unit. Search means for searching the given document from the document holding means, a classification means for classifying the documents detected by the search means into a plurality of document sets according to similarity, and holding a classification result by the classification means Classification history holding means, and, when a plurality of classification results in the classification history holding means are specified, a classification presentation means for displaying the specified classification result on a display device, Classification information presentation device is provided that.

[0010] According to this classification information presentation device, the document search means searches the document storage means for a document that matches the search formula stored in the specification storage means and the classification target period. The detected documents are classified by the classification unit into a plurality of document sets according to similarity. The classification result is stored in the classification history storage unit. Then, when a plurality of classification results in the classification history holding means are specified, the specified classification results are displayed on the display device by the classification presenting means.

[0011] Further, in a medium recording a classification information presentation program for causing a computer to present the distribution state of an information group, a document holding means for holding a document given an information occurrence time, a search formula and a classification target period are stored. A specification holding unit that holds a classification specification including the document, and a document that matches a search expression held by the specification holding unit and is given a time of information occurrence within a classification target period held by the specification holding unit; Search means for searching from means, classification means for classifying documents detected by the search means into a plurality of document sets according to similarity, classification history holding means for holding the classification result by the classification means, and classification history holding means When a plurality of classification results are designated, a classification presentation unit for displaying the designated classification results on a display device, a function for causing a computer to function as Medium recording information presentation program is provided.

By causing the computer to execute the classification information presentation program recorded on the medium, the computer retains the classification specification, and when a plurality of classification results are designated, the plurality of classification results are displayed on the display device of the computer. You.

[0013]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram illustrating the principle of the present invention. The document holding means 1 holds a plurality of documents 1a, 1b, 1c,... Given information generation times. The specification holding unit 3 holds the classification specification including the search formula and the classification target period input from the input device 2. Search means 4
Searches for a document that matches the search expression held in the specification holding unit 3 from among the documents provided with the information occurrence times within the classification target period held in the specification holding unit 3.
The detected document is passed to the classifying means 5. Classification means 5
Classifies documents detected by the search means 4 according to similarity. The classification history storage unit 6 stores the classification result by the classification unit 5 together with the classification specification. Classification presentation means 7
A plurality of classification results 8 a to 8 held in the classification history holding unit 6
8c is displayed on the screen of the display device 8.

Thus, each time the specification holding unit 3 holds a classification specification having a different classification target period, the classification result of the document generated within the classification target period is stored in the classification history storage unit 6. Then, if a plurality of classification results having different classification target periods are designated and displayed on the display device, it is possible to grasp a temporal transition state of the content of the information group.

FIG. 2 is a diagram showing a schematic configuration of the first embodiment of the present invention. This embodiment includes a large document set 11 for holding document information, a thesaurus holding unit 12 for holding a thesaurus, an input device 13 for inputting specifications such as a search formula, a specification holding unit 14 for holding the input specifications, Search mechanism unit 15 for performing search, initial document set storage unit 16 for storing search results, classification mechanism unit 17 for classifying search results, classification history storage unit 18 for storing classification results, classification presentation mechanism for presenting classification results Part 19 and CRT (Cathode-Ray Tub
e) and the like. The details of the function of each component will be described below.

The large document set 11 stores a large amount of document information to which information generation time is added. In the large-scale document set 11, new documents are stored every moment. The thesaurus holding unit 12 holds a thesaurus (synonym dictionary) that clarifies the relation between words (synonym relation and hierarchical relation).

FIG. 3 is a diagram showing an example of a thesaurus.
In the thesaurus 12a, the similarity relationship between words is represented by a tree structure, the root is set to "level 0", and the level value increases by one each time the hierarchy goes down from the root.

The input device 13 is a keyboard, a mouse, or the like. By operating the input device 13 by the user, it is possible to set search and classification specifications. Specifically, a search formula, the number of divisions, a viewpoint specification, and a classification target period are input. In this case, one keyword is input on the premise that a full-text search is performed (this search expression may be one or more keywords, or a logic based on a Boolean operation including designation of a bibliographic clause of a document). Expression). The number of divisions is a value that specifies how many clusters (document sets with similar concepts) are to be divided when classifying information. The viewpoint is a specification of how words are classified based on a central concept (here, a phrase input as a search formula is the central concept). ". For example, when “car” is the central concept and classification is performed from the viewpoint of “object”, expressions such as “develop car” and “sell car” are extracted, and “development” is an operation targeting car. The information is categorized based on phrases such as “sales” and “sales”. In this figure, the input device 13 is connected only to the specification holding unit 14. However, it is also possible to input various commands (such as designation of a classification result to be displayed on the display device 20) to other components.

The specification holding unit 14 holds the specification input by the input device 13. Each specification is held in a separate storage area. The search formula is held in the search formula holding unit 14a. The division number is held in the division number register 14b. The viewpoint is held in the viewpoint specification holding unit 14c. The classification target period is held in the classification target period register 14d.

The search mechanism 15 includes a search formula stored in the search formula storage 14a and a classification target period register 14d.
Is searched from the large-scale document set 11 for documents that match the search formula among the documents generated within the classification target period. This search result is stored in the initial document set holding unit 16. At this time, it is not necessary to actually copy the entire document, and only the pointers (document ID or address) necessary for accessing the document are collected. Also, here, the information of the generation date and time given to the document is passed at the same time. In addition to this, when various attributes, extracted keywords, or the like or a text analysis result are given to the document in advance, a document pointer may be passed along with them (or a pointer to them).

The classification mechanism section 17 includes the thesaurus holding section 12
The documents included in the initial document set are grouped into clusters formed by similar documents using the thesaurus stored in. This processing ends when the number of clusters becomes equal to or less than the value specified in the division number register 14b.

The calculation of the degree of similarity is performed by using the “Vector Spa
ce Model "(Salton, G." Autom
atic Text Processing ”Addi
son-Wesley 1989) can be used. In this similarity calculation method, each document is represented by a vector having the weight of a word as an element, and the similarity (for example, inner product) of the vector is set to be similar to the document. As a classification method, a method disclosed in JP-A-5-225256 (Scatte
r / Gather) and Kohonen's "Self-
There is a method using “Organizing Map”.

In this embodiment, classification is performed based on viewpoints. In order to perform the classification based on the viewpoint, first, the text information portion of the document set in the initial document set holding unit 16 is analyzed, and a predetermined relationship between the central concept (words in the search formula) input from the input device 13 and And the relations between them are extracted.
Then, with respect to the central concept, a word having a relation corresponding to the viewpoint stored in the viewpoint specification holding unit 14c is extracted. Register the extracted words in the category count table.

FIG. 4 is a diagram showing an example of the category count table. The category count table 30 includes a “category” and the number of documents (count) belonging to the category. In the initial state, the extracted words are registered in the “category” as they are. Then, the number of occurrences of the word is set to “count”.

If the number of categories in this category count table is larger than the value of the division number register 14b,
Combines categories based on the word merge algorithm. Hereinafter, the word merging algorithm will be described. [S1] The category with the least number of appearances in the category count table is selected. [S2] The upper level concept including the selected category is specified with reference to the thesaurus. This concept is referred to as “W0”. [S3] Among words registered in the category field of the category count table, "W
All words corresponding to the lower concept of “0” are replaced with “W0”. [S4] In the category count table, the total count of the records registered as "W0" in the category field is calculated. The value is set to “C0”. [S5] All existing records registered as "W0" in the category field in the category count table are deleted, and a new category "W" whose count is "C0" is deleted.
The record of "0" is registered.

For example, in the category count table 30 shown in FIG. 4, "W / S (workstation)" is the least frequent word. Referring to the thesaurus of FIG. 3, the superordinate concept of “workstation” is “computer”. Under the “computer”, there are “PC”, “PDA” and the like. In addition, there is a “desktop” under the “PC”. These are all integrated under the concept of "computer".

FIG. 5 is a diagram showing a count table after the category integration processing. In the count table 30a after the category integration processing, the “PC”, “W /
The category of "S" has disappeared, and their count has been added to "Calculator".

Until the number of categories becomes equal to or less than the value stored in the division number register 14b, the above category integration processing is repeatedly executed. Further, the classification mechanism unit 1
7 indicates that each set is 2 based on the similarity between the classified sets.
Place in dimensional space. For this, we use the method of Kruskull of "PC multidimensional scale construction method" (Okata / Imaizumi, Kyoritsu Shuppan). Then, according to the number of elements in the set, the area indicating the classification is widened. Alternatively, by changing the color density of the area, the magnitude relation of the number of elements can be visually easily understood.

Next, the classification mechanism 17 performs labeling. A character string indicating the cluster is given in the cluster label field. Here, the label of the thesaurus is used as it is. In addition, as another method, there is a method in which the top few keywords frequently used in the cluster are used as labels.

The classification history holding section 18 holds the classification result by the classification mechanism section 17. FIG. 6 shows the classification history holding unit 18.
It is a figure which shows the holding content. Information is three tables 3
1, 32, and 33 are held separately.

In the table 31, items of "classification ID", "date", "period", "center concept", "viewpoint", "cluster" and "classification screen" are registered. "Category I
"D" is an identification number for specifying the classification history.
“Date” is the date of the first day of the period to be classified (classification target period). The “period” indicates how many days from the date indicated in the “date” were classified. The “center concept” indicates the center concept at the time of classification. The “viewpoint” indicates what kind of viewpoint is used for classification. In the “cluster”, the identification number (classification ID) of the cluster obtained by the classification is registered. The "classification screen" stores classification screens 31a and 31b in which the classification results are represented by two-dimensional image images. In the table 32, items of "classification ID", "classification label", "number", and "member" are registered. “Classification ID” is an identification number for specifying a classified cluster. “Classification label” is a label added to the cluster. “Number” is the number of documents included in the cluster. “Member” is the identification number “Document ID” of each document included in the cluster.

In the table 33, "document ID" and "title" are registered. “Document ID” is an identification number of each document. "Title" is the title of the document.

The classification presentation mechanism 19 receives designation of a classification history to be displayed on the screen from the input device 13, takes out the classification screen of the classification history from the classification history holding unit 18, and displays it on the screen of the display device 20.

FIG. 7 is a diagram showing a display example of the classification screen. A plurality of history icons 41 are displayed on the classification screen 40. Each history icon 41 corresponds to a classification history, and by selecting an arbitrary history icon 41,
The corresponding classification history can be displayed.

The selected classification history is displayed on the first classification screen 42.
And the second classification screen 43. By displaying the two classification histories side by side in this way, the difference can be easily determined.

When a document is specified, the information content display window 44 displays the content of the document. To specify a document, for example, an arbitrary cluster is selected from the first classification screen 42 and the second classification screen 43, and a list of titles of documents included in the cluster is displayed. Then, by selecting a document with reference to the title, the content of the document is displayed in the information display window 44.

FIG. 8 is a diagram showing an example of a classification screen. The viewpoint display section 45a at the upper left of the classification screen 45 indicates that the central concept is “car” and the viewpoint is “target”. That is, the classification is made from the viewpoint of "what to do with the automobile". Then, an elliptical figure 45 indicating the classified cluster is displayed in the classification screen 45.
b to 45j are displayed together with the label.

In this way, a plurality of classification histories can be simultaneously presented to the user. Therefore, the user displays two classification histories with different periods of the document to be classified on the first classification screen 42 and the second classification screen 43, and how the distribution of topics changes during that period. You can know what.

Next, a second embodiment will be described. In this embodiment, a plurality of display screens between two types of display screens are created and sequentially displayed, thereby visualizing a state in which clusters are continuously enlarged, reduced, and integrated.

FIG. 9 is a diagram showing a schematic configuration of the second embodiment. In this embodiment, a large document set 51, a thesaurus storage unit 52, an input device 53, a specification storage unit 54 (a search expression storage unit 54a, a division number register 5
4b, a viewpoint specification storage unit 54c and a classification target period register 54d), a search mechanism unit 55, an initial document set storage unit 56, a classification mechanism unit 57, and a classification history storage unit 58 are described in the first embodiment (FIG. 2) have the same functions as the components of the same name in FIG.

The document cluster identification device 59 is provided by the input device 5
Regarding the two classification results specified by the input from 3,
Determine the inclusion relationship of the cluster. In this embodiment,
The inclusion relation is determined using the thesaurus held in the thesaurus holding unit 52. That is, if there is a superordinate concept cluster and a subordinate concept cluster, the subordinate concept cluster is included in the superordinate concept cluster. For example, "computer" and "workstation (W / S)"
If there is a cluster of “W / S”, “W / S” is included in “computer”.

As a result, comparing the two classification histories,
Each cluster is divided into three types: a "same cluster", a "cluster in an inclusive relationship", and a "cluster that exists in only one".

The classification interpolator 60 generates a plurality of screens for interpolating the display screens of the two classification histories based on the inclusion relation determined by the document cluster identification device 59. In addition,
As a premise, an ellipse indicating a cluster has center coordinates (x,
The y-axis direction of a circle represented by y) and a radius r is reduced and represented at a fixed ratio. Here, it is set to 60%.

When the document cluster identifying device 59 determines that the clusters are the same, an interpolation process is performed as follows. First, an ellipse indicating a cluster of one classification history (first classification) is IB (0), and an ellipse indicating a cluster of the other classification history (second classification) is IB (9). Here, the center coordinates of IB (0) are (x0, y0), and the radius is r
0, the center coordinate of IB (9) is (x9, y9), and the radius is r9. At this time, IB (i) (i = 1, 2, 3,
..., 8) the center and radius are

[0045]

(Equation 1)

[0046]

(Equation 2)

[0047]

(Equation 3) Becomes

If the document cluster identifying device 59 determines that the cluster is in an inclusive relation, an interpolation process is performed as follows. Here, cluster A in the first classification
However, in the second classification, consider a case where the cluster is divided into two clusters B and C. At this time, the cluster A sequentially disappears, and the clusters B and C must be sequentially generated. Here, a method of sequentially extinguishing them will be described.

The virtual position of cluster A is set in IB (9). This calculates the area that cluster A will occupy when clusters B and C are integrated. The center is (x9, y9) and the radius is (r9). This allows
According to the above equations (1) to (3), IB (i) (i = 1,
An elliptical shape of 2, 3, ..., 8) is obtained.

Further, assuming that the inside of the ellipse is colored flat, and that color is represented by three colors of RGB (red, green, blue), the color of cluster A is (R0, G0, B0)
It is represented by Since the cluster A of IB (9) is not displayed, its RGB values (R9, G9, B9) are set to the same color as the background (or the color of the cluster if it is part of a larger cluster). Therefore,

[0051]

(Equation 4)

[0052]

(Equation 5)

[0053]

(Equation 6) With this, the color of the ellipse IB (i) is obtained.

As a result, a figure can be defined for interpolation when the cluster A disappears. As the interpolated figures when the clusters B and C occur, the figures obtained by the above processing may be arranged in reverse order.

When the document cluster identification device 59 determines that the cluster is a cluster that exists only on one side, the interpolation process is performed as follows. When the cluster A in the first class does not exist in the second class, the cluster A is erased in the same manner as when the cluster A is erased by division. In this case, the same values as IB (0) are used for the center coordinates and the radius of IB (9).

The cluster that does not exist in the first classification is the second cluster.
Are generated sequentially in the same manner as the clusters B and C generated by the above division. Similar interpolation is performed for labels. That is, the label is sequentially moved from the initial position to the final position. When it disappears, it is sequentially changed to the background color. Note that labels may be displayed only on the initial screen and the final screen without performing interpolation.

By performing all of the above interpolation processing,
Eight display screens that interpolate between the first classification and the second classification can be obtained. The display screen interpolated by the classification interpolation mechanism unit 60 in this way is sent to the display buffer 61 together with the classification screens of the first classification and the second classification.

The display buffer 61 can store 10 display screens. Then, the display screens sent from the classification interpolation mechanism unit 60 are sequentially stored. Classification presentation mechanism 62
Displays the display screen stored in the display buffer 61 on the display device 63.

Thus, the growth, decay, division, and integration of the cluster can be displayed by animation. FIG. 10 is a diagram showing a change in the classification displayed as an animation. This is a case where the cluster 71 splits into two clusters and the cluster 71 itself disappears. In the figure, the left end is the first classification, and the right end is the second classification. Only two screens for interpolating between them are shown.

The cluster 71 becomes lighter in color and disappears as it approaches the second screen. On the other hand, clusters 72 and 73
Are gradually darker in light color and are clearly displayed in the second classification.

Next, a third embodiment will be described. This is because, when a cluster for which details are to be specified is specified and a place where a plurality of intermediate classifications are to be viewed between two classifications is specified, the information extraction device sequentially classifies certain sections based on partial calculation results stored in the history. Is what you do.

The components necessary for this embodiment are the second
Since the third embodiment is the same as the third embodiment, the processing contents of the third embodiment will be described using the configuration shown in FIG. For a plurality of intermediate classifications, the user gives the following parameters using the input device 53. "Length of classification target period" (for example, 2 months) "Date of initial classification" (for example, March 1, 1996) "Date and time of final classification" (for example, present) "Step of movement" (for example, 15) Day) The classification interpolation mechanism unit 60 interpolates between the initial classification, the final classification, and the intermediate classification according to such parameters. According to the above parameters: Classification of the information group whose initial classification occurred on "January 1, 1996-March 1, 1996". Classification of the information group in which the first intermediate classification occurred on "January 15, 1996-March 15, 1996".

Thereafter, the classification history whose target period is shifted by 15 days is similarly acquired from the classification history holding unit 58. If there is no appropriate time interval, the unit section classification stored in the classification history holding unit 58 is used as a partial calculation result, and these are combined to generate a classification history of a necessary period. To generate a unit section classification, a unit period is given to the search mechanism unit 55 in advance, and the search is periodically performed for each unit period. If the search mechanism unit 55 performs the search periodically, the classification mechanism unit 57 generates a unit section classification accordingly, and the generated unit section classification is stored in the classification history storage unit 58.

FIG. 11 is a diagram showing classification target periods according to the third embodiment. The horizontal axis in this figure is time.
The initial classification target period 81 is a two-month period up to “March 1, 1996” which is the date of the initial classification. The target period 82 of the first intermediate classification is a period shifted by 15 days from the target period 81 of the initial classification. Thereafter, similarly, the target period 83 of the second intermediate classification and the target period 8 of the third intermediate classification
4. The target period 85 for the final classification is determined.

The unit section classifications 91 to 98 are classifications every 15 days. By merging necessary ones of these unit section classifications 91 to 98, a classification history in a necessary classification target period can be generated. To merge the unit section classifications, those category count tables are simply merged and the counts of the same category are summed. Then, cluster merging is repeated by the above-described word merging algorithm until the number of categories reaches the designated number of divisions. Thereby, a classification history of a required period can be obtained from the unit section classification.

Then, the classification interpolator 60 interpolates between these classification histories. That is, between the initial classification and the first intermediate classification, between the first intermediate classification and the second intermediate classification, between the second intermediate classification and the third intermediate classification, and
Is interpolated between the intermediate classification and the final classification. The result is stored in the display buffer 61 (in this case, a display buffer having a larger capacity than in the second embodiment is required).
Then, the classification and presentation mechanism unit 62 sequentially displays the contents of the display buffer on the display device 63.

As described above, by obtaining a plurality of intermediate classifications and interpolating between them to display an animation,
For example, if the amount of information increases once and then disappears,
Information that cannot be known from the initial classification and the final classification alone can be displayed in an animation.

The above processing functions can be realized by a computer. In that case, the processing contents of the functions that the classification information presentation device should have are described in a program recorded on a computer-readable recording medium, and the above processing is executed by executing this program on a computer. Implemented by computer.
Examples of the computer-readable recording medium include a magnetic recording device and a semiconductor memory. When distributing in the market, the program is stored and distributed on a portable recording medium such as a CD-ROM or a floppy diskette, or stored in a storage device of a computer connected via a network. Can also be transferred to a computer. When the program is executed by the computer, the program is stored in a hard disk device or the like in the computer, and is loaded into the main memory and executed.

[0069]

As described above, in the classification information presentation apparatus of the present invention, the generation time of a target document is limited in time, classification results having different time divisions are held, and a plurality of classification results are stored. When specified, they are displayed on the display device, so that it is easy to grasp how the distribution state of the information has changed over time.

Further, in the medium on which the classification information presentation program of the present invention is recorded, the recorded classification information presentation program is executed by a computer, whereby the classification results having different time divisions are stored in the computer, and a plurality of classification results are stored. It can be displayed on a computer. as a result,
It is possible to cause a computer to present classification information so that it is easy to grasp how the distribution state of information has changed over time.

[Brief description of the drawings]

FIG. 1 is a principle configuration diagram of the present invention.

FIG. 2 is a diagram showing a schematic configuration of a first embodiment of the present invention.

FIG. 3 is a diagram illustrating an example of a thesaurus.

FIG. 4 is a diagram showing an example of a category count table.

FIG. 5 is a diagram showing a count table after category integration processing.

FIG. 6 is a diagram showing contents held by a classification history holding unit.

FIG. 7 is a diagram showing a display example of a classification screen.

FIG. 8 is a diagram showing an example of a classification screen.

FIG. 9 is a diagram illustrating a schematic configuration of a second embodiment.

FIG. 10 is a diagram illustrating a change in classification displayed as an animation.

FIG. 11 is a diagram illustrating classification target periods according to the third embodiment.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Document holding means 2 Input device 3 Specification holding means 4 Search means 5 Classification means 6 Classification history holding means 7 Classification presentation means 8 Display device

Claims (5)

[Claims] 1. A classification information presentation device for presenting a distribution state of an information group, comprising: a document holding unit for holding a document given an information generation time; and a specification for holding a classification specification including a search formula and a classification target period. Holding means, and a search means for searching, from the document holding means, a document which matches the search expression held in the specification holding means and which is given the information occurrence time within the classification target period held in the specification holding means. A classification unit that classifies the documents detected by the search unit into a plurality of document sets according to similarity; a classification history storage unit that stores the classification result by the classification unit; And a classifying means for displaying the specified classification result on a display device when the classification result is specified. 2. The classification information presentation device according to claim 1, wherein the classification unit generates, as a classification result, image information in which the classified individual document sets are represented by one graphic. 3. When two classification results in the classification history holding means are designated, an interpolation showing a state in which a document set gradually changes from one of the designated classification results to the other classification result. A classification interpolating unit that generates a screen, wherein the classification presenting unit continuously displays the interpolation screen generated by the classification interpolating unit between two designated classification results. The classification information presentation device according to claim 1, wherein 4. The classification information presenting apparatus according to claim 1, wherein said search means executes a search process every predetermined period. 5. A medium storing a classification information presentation program for causing a computer to present the distribution status of an information group, a document holding means for holding a document given an information generation time, a search formula and a classification target period. A specification holding unit that holds a classification specification including the document, and a document that matches the search expression held by the specification holding unit and is given the information occurrence time within the classification target period held by the specification holding unit. Search means for searching from means, classification means for classifying the documents detected by the search means into a plurality of document sets according to similarity, classification history holding means for holding the classification result by the classification means, classification history holding means When a plurality of classification results are designated, the classification presentation means for displaying the designated classification results on a display device, Medium recording information presentation program.