JP2008021305A - Counseling system, counseling device and counseling control program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a counseling system by which a user inputs emotion by using more appropriate expression, and moreover, counseling for detecting even the emotions which the user himself is not aware of first is attained by using a computer. <P>SOLUTION: The counseling system is constituted of a data base server 2 which accumulates linguistic information input via a PC 4 extending for over a plurality of days for the plurality of days; the space between words leaving part 204 and a clustering part 205 which generate component clusters, based on the similarity between linguistic elements included in the accumulated linguistic information; a linguistic information unit generating part 207 which associates an input date, when the linguistic information is input with the component clusters, divides the linguistic information based on the discontinuity of the associated component clusters, to generate a linguistic information unit; and a linguistic information analysis part 203 which analyzes the linguistic information of the linguistic information unit as the unit. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a counseling system, a counseling device, and a counseling control program, and more particularly to a counseling system, a counseling device, and a counseling control program using a structured association method.

  Currently, a counseling system that collects information from users via a computer network and analyzes the collected information by a computer has been put into practical use. As a conventional example of such a counseling system, for example, Patent Document 1 is cited. The invention described in Patent Document 1 transmits a question message prompting the user to input his / her trouble and receives the input information.

Then, the information related to the received information is selected and synthesized from the information stored in advance, and a message as a reply is created and transmitted to the user. According to such a counseling system, the user can receive objective advice about his / her problems without going to a specialized counselor.
However, in the invention of Patent Document 1, a plurality of items are presented, and the user is made to input troubles by selecting the corresponding item. For this reason, there is a drawback that the degree of freedom of expression of input by the user is low and the subjective emotion of the user cannot be accurately grasped.

In general, humans often do not accurately grasp their own feelings and the reason why their feelings occurred. In such a case, in the invention of Patent Document 1, items are selected according to the superficial recognition of the user, information about emotions that the user is not aware of is not input, and an appropriate answer is given. There is a possibility that it cannot be provided.
Japanese Patent Application No. 2003-256550

By the way, a counseling method called a SAT method (structured associative method) is currently proposed. According to this counseling method, information such as text that freely expresses subjective emotions is input to the user, and such information is continuously collected to detect emotions that the user himself / herself is not aware of. it can.
However, the invention of Patent Document 1 in which the user selects information set in advance and inputs information cannot link text information described freely as in the SAT method. Further, the invention described in Patent Document 1 does not take into consideration any analysis of information that is continuously input, and detects emotions other than emotions that the user recognizes at the beginning of counseling. I can't.

For this reason, at the present stage, the computer can be used to collect information necessary for counseling by the SAT method, but the input information cannot be analyzed without a specialized counselor.
Also, even when specialized counselors analyze the collected information, extracting the data necessary for analysis from a large amount of text data that has been continuously input over a relatively long period of time is a burden on counseling. It becomes the cause which raises.

The present invention has been made in view of the above points, and the user can express his / her emotion more appropriately using a more appropriate expression, and the user can continuously express his / her subjective emotion. To provide a counseling system, a counseling device, and a counseling control program that can realize, using a computer, counseling that can detect emotions that the user himself / herself was not aware of at first. With the goal.
Another object of the present invention is to provide a counseling device that can automatically extract data necessary for analysis from a large amount of text data.

  In order to solve the above problems, the counseling system according to claim 1 includes an input receiving unit that receives input of language information that is information related to a language over a plurality of days, and a language that is input via the input receiving unit. Language information receiving means for receiving information through a network, storage means for storing the language information received by the language information receiving means for a plurality of days, and language elements included in the language information stored by the storage means, Grouping means for classifying based on the similarity between language elements and generating a group of a plurality of language elements, and corresponding to an input date when the language information is input and at least one of the groups generated by the grouping means The association means to be attached, and the groups arranged in the order of the input dates in association with the input dates by the association means. In the group, when the discontinuity of the group type occurs, the language information dividing means for generating the language information unit by dividing the language information stored in the storage means before and after the discontinuity, and Linguistic information analyzing means for analyzing linguistic information in units of the linguistic information units generated by the division by the linguistic information dividing means.

  According to such an invention, language information input over a plurality of days can be received and accumulated. Moreover, the language elements included in the accumulated language information can be classified based on the similarity, and a group of a plurality of language elements can be generated. The language information unit can be generated by dividing the language information accumulated before and after the discontinuity of the group that occurs when the created group is associated with the input date.

  The created linguistic information unit is regarded as a group of data (one unit) from the start of the user's thought to an interruption or end to some event (factor), so that the linguistic information analysis means uses the linguistic information unit as a unit. To provide a counseling system that can detect emotions that the user himself / herself is not initially aware of from the document in which the user inputs his / her emotions using a more appropriate expression by analyzing linguistic information it can.

  Further, the counseling device according to claim 2 is a storage information acquisition unit that acquires linguistic information that is input over a plurality of days and that relates to the stored language, and the language information acquired by the storage information acquisition unit. The language elements included in the language element are classified based on the similarity between the language elements, a grouping unit that generates a group of a plurality of language elements, an input date when the language information is input, and the grouping unit In a group associated with at least one of the groups, and in a group that is associated with the input date by the association unit and arranged in the order of the input date, when the discontinuity of the group type occurs, A language information unit is generated by dividing the language information acquired by the accumulated information acquisition means before and after the discontinuity. An information dividing unit, characterized in that it comprises a language information analyzing means for analyzing the language information and the language information unit in units derived by dividing by the language information dividing means.

According to such an invention, it is possible to acquire data in which language information input over a plurality of days is accumulated. Moreover, the language elements included in the accumulated language information can be classified based on the similarity, and a group of a plurality of language elements can be generated. The language information unit can be generated by dividing the language information accumulated before and after the discontinuity of the group that occurs when the created group is associated with the input date.
Since the created language information unit is regarded as one unit from the start to the end or end of the user's thought, the language information analysis means analyzes the language information in units of the language information unit so that the user himself It is possible to provide a counseling device that can detect emotions that the user himself / herself is not aware of from the document in which the emotions are input using a more appropriate expression.

Further, the counseling device according to claim 3 is characterized in that, prior to receiving input of language information by the input receiving means, theme information that gives the user a thought theme, an action to be taken for an episode recalled by the user by the theme information, or It further comprises message providing means for providing the user with a message including at least action / decision information input instruction information for instructing to write information relating to the decision.
According to such an invention, it is possible to give a user a theme and to provide information on an episode recalled by the user. In addition, it is possible to instruct the user to write information on an action or decision to be taken for an episode recalled, and to prompt the user to input information such as an episode in free notation.

The counseling device according to claim 4 provides the map information for the message providing means to input information related to the place recalled by the theme information when the theme information is provided, and the theme information It is further characterized by further comprising a position input receiving means for inputting the recalled location position onto the map information.
According to such an invention, it is possible to provide the theme information and to input information related to the place recalled by the theme information. For this reason, the information of the place which a user recalls with an episode with theme information can also be collected.

Further, in the counseling device according to claim 5 of the present invention, the grouping means includes element decomposition means for decomposing language information into language elements included in the language information, and the element decomposition means decomposed by the element decomposition means. Similarity determination means for determining similarity of language elements based on a relative relationship between the appearance of language elements and other language elements, and language elements based on the similarity determined by the similarity determination means Are clustered to generate a plurality of groups.
According to such an invention, language information can be decomposed into language elements. It is also possible to cluster language elements based on the relative relationship between the appearance of one language element generated by decomposition and the appearance of other language elements, and to generate a plurality of groups that combine language elements that frequently appear at the same time. it can.

  The counseling device according to claim 6, wherein the association unit includes at least one of the groups generated by the grouping unit and a language element included in the language information in which the language element included in the group is input. Or an input date that occupies a predetermined ratio or more, or an input date and a group that includes the most language elements included in the language information input on the input date. .

Further, in the counseling device according to claim 7, the language information analysis unit determines a difference between the language information input earlier and the language information input later in the language information included in the language information unit. It is characterized by analyzing in association with changes in user emotions.
According to such an invention, it is possible to obtain a change in the emotion of the user in the process of information input over a plurality of days by analysis.

The counseling device according to claim 8, wherein the language information analysis unit analyzes the language information included later in the language information unit in association with information that is not recognized by the user at first. It is characterized by doing.
According to such an invention, in the process of inputting information over a plurality of days, it is possible to obtain an emotion that has not been recognized by the user at first and has become apparent later by analysis.

  Further, in the counseling device according to claim 9, the language information analyzing unit searches the language information unit using a keyword input receiving unit that receives a keyword input and a keyword received by the keyword input receiving unit. Linguistic information unit selecting means for selecting a linguistic information unit including linguistic information matching the keyword, and linguistic information unit output means for outputting the linguistic information unit selected by the linguistic information unit selecting means to the outside. It is characterized by that.

  According to such an invention, a language information unit including an arbitrary keyword can be extracted from the language information unit. Since the linguistic information unit is a set of data from the start to the end or end of the user's thought about an event, the extracted data is considered to be a set of data written about an event related to a keyword. It is done. For this reason, it is possible to automatically extract data in which the subjective emotions of the user are expressed in detail, accurately, and appropriately with respect to the event related to the keyword.

Further, the counseling device according to claim 10, wherein the language information analyzing means is self-evaluated by a user who has input language information from language information included in the language information unit selected by the language information unit selecting means. Subjective extraction means for extracting at least one of subjective evaluation of independence and dependence, and subjective evaluation of evaluating at least one change over time of the self-evaluation, independence and dependence subjective evaluation extracted by the subjective extraction means And an evaluation means.
According to such an invention, it is possible to evaluate a change in subjective emotion over time with respect to data in which a user's subjective emotion is expressed in detail, accurately, and appropriately for an event related to a keyword. it can.

  The program according to claim 11 is stored in a computer to obtain language information that is input to a computer over a plurality of days and stores language information, and language information acquired by the stored information acquisition function. The language elements included in the language element are classified based on the similarity between the language elements, a grouping function for generating a group of a plurality of language elements, an input date when the language information is input, and the grouping function When a discontinuity of the group type occurs in the association function that associates at least one of the groups and the group that is associated with the input date by the association function and arranged in the order of the input date, A language information unit is generated by dividing the language information acquired by the stored information acquisition function before and after the discontinuity. And language information division function, characterized in that to realize, and language information analysis function of analyzing the language information in units of the language information unit produced by dividing by the language information dividing function.

According to such an invention, it is possible to acquire data in which language information input over a plurality of days is accumulated. Moreover, the language elements included in the accumulated language information can be classified based on the similarity, and a group of a plurality of language elements can be generated. The language information unit can be generated by dividing the language information accumulated before and after the discontinuity of the group that occurs when the created group is associated with the input date.
Since the created language information unit is regarded as one unit from the start to the end or end of the user's thought, the language information analysis means analyzes the language information in units of the language information unit so that the user himself It is possible to provide a counseling control program that can detect an emotion that the user himself / herself is not aware of from the document in which the emotion is input using a more appropriate expression.

Embodiments 1 to 4 of a counseling system, a counseling device, and a counseling control program according to the present invention will be described below with reference to the drawings.
(Embodiment 1)
Hereinafter, Embodiment 1 of the present invention will be described. In the present embodiment, the counseling system, the counseling device, and the counseling control program of the present invention are described in the order of (1) the overall configuration of the counseling system, (2) the main part of the counseling function, and (3) the analysis operation example of the counseling function. It shall be.

(1) Overall Configuration of Counseling System FIG. 1 is a diagram for explaining the concept of the counseling system according to the first embodiment. In the illustrated system, a PC (Personal Computer) 4 used by a user accepts input of language-related information (language information) over a plurality of days. The counseling system has a WEB server 1 for receiving input language information through a network. Further, a database server 2 that accumulates the language information received via the WEB server 1 for a plurality of days of input, and an analysis program 101 that analyzes the language information accumulated by the database server 2 are provided.

In the counseling system of the first embodiment that executes counseling using the SAT method, the user freely describes his / her thoughts and feelings. The contents described by the user are sent to the WEB server 1 as language information. The WEB server 1 accepts the transmitted language information and stores it in the database server 2.
In the first embodiment, the WEB server 1 writes the theme information that gives the user a thinking theme and the information about the action or the decision to be made for the episode recalled by the user based on the theme information before receiving the input of language information. A message including at least action / decision information input instruction information to be instructed is provided to the user.

A user input form 3 by the SAT method is shown in FIG. According to the input form 3, the user has an event (episode) that is recalled with respect to the theme information, a background emotion that causes the episode to be recalled, and a desire or expectation that the user has for himself or others from the background emotion. Entered. You can also input your own image (self image) that realizes your hopes and expectations, and your goals, actions, and decisions to realize your image. The language information input by the user will be described in detail later.
The analysis program 101 analyzes the language information input according to the input form 3. The result of the analysis is managed by the administrator of the WEB server 1 and used for a medical or health survey or a government survey. Furthermore, the analysis result can be transmitted to the user and used for the user's self-counseling.

(2) Main part of counseling function FIG. 2 is a block diagram for explaining the analysis program 101 in more detail. The analysis program 101 includes a similarity determination unit 201 that classifies language information accumulated in the database server 2 based on similarity of language elements included in the language information, and generates a plurality of groups.
The similarity determination unit 201 includes a segmentation unit 204 that decomposes language information into language elements included in the language information, and the similarity of language elements based on the appearance frequency of the language element decomposed by the segmentation unit 204 Determine gender. The similarity determination unit 201 includes a clustering unit 205 that clusters language elements based on the determined similarity, and generates a plurality of groups by clustering. In the first embodiment and the second embodiment, the generated group is hereinafter referred to as a component cluster.

The similarity determination unit 201 includes a clustering dictionary 206 that is used for clustering. The clustering dictionary 206 is a database of clustered language elements that should be treated as substantially the same language elements. A specific method of clustering will be described in detail later.
The analysis program 101 includes a language information unit generation unit 207. The language information unit generation unit 207 associates the input date when the language information is input with at least one of the component cluster. When a discontinuity of component clusters occurs in a series of component clusters associated with consecutive days of input dates, the language stored in the database server 2 before and after the generated discontinuity A language information unit is generated by dividing the information.

Note that the input date refers to the date on which the language information is actually input on the date on which the input of language information is received, and the simple date refers to the entire date on which the input of language information is received.
In addition, the analysis program 101 includes a language information analysis unit 203. The language information analysis unit 203 analyzes the language information in units of language information units generated by the language information unit generation unit 207. In the first embodiment, the linguistic information unitized by the linguistic information unit generation unit 207 is stored in the database server 2 again with information indicating each group. The analysis program 101 extracts and analyzes the language information unit stored in the database server 2 as necessary.

  Of the configurations described above, the WEB server 1 functions as language information receiving means, analysis result providing means, and message providing means. Further, the database server 2 functions as storage means. The similarity determination unit 201 of the analysis program 101 functions as a grouping unit, the language information unit generation unit 207 functions as an association unit and a language information division unit, and the language information analysis unit 203 functions as a language information analysis unit. The segmentation unit 204 of the similarity determination unit 201 is an element decomposition unit, and the clustering unit 205 is a similarity determination unit.

(3) Example of analysis operation of counseling function Here, the analysis of language information by the analysis program 101 is illustrated.
1. Generation of Component Cluster FIG. 3 is a diagram showing a specific example of the input form 3. 4A, 4B, and 4C illustrate language information input by the user according to the input form shown in FIG. 3, and FIGS. The language information input on another day is shown. According to the input form shown in FIG. 3, the system administrator side provides the user with “What do you feel in this area and your life now” as theme information? In the example of FIG. 4, the user inputs the language information 401 shown in FIG. 4A for such theme information.

  In the input form 3, the color floating from the episode is set as the question 302 next. The question 302 is a question unnecessary for counseling, and is a question for making the user think intuitively. In this embodiment, the question that the user needs to think based on the theory and the question that the user thinks intuitively are alternately arranged to keep the user's thought flexible, and the user's emotion is easily reflected in the language information. ing.

  In the present embodiment, as shown in FIG. 3, a message including information instructing the user sequentially and instructing to input goals, actions, and decisions for realizing a self-image by the questions 304 to 307 is provided. To do. In response to the question 306 out of these questions, the user inputs language information 402 of “Go anywhere, go anywhere, look for work in the country. Go to an unknown land”.

In the counseling system of this embodiment that accepts language information over a plurality of days, after the language information shown in FIG. 4A is input, the language information shown in FIGS. 4B and 4C on another day. Is entered. The period for receiving the language information input is arbitrary, but the first embodiment assumes about one month to one year.
The language information input during the reception period is accumulated in the database server 2. After completing the input acceptance, the system administrator analyzes the accumulated language information using the analysis program 101. In the first embodiment, it is assumed that the analysis is executed only on the language information indicating the goal, action, and decision among the input language information.

That is, in the example shown in FIG. 4, among the language information shown in (a) to (c), the language information 402 in (a), the language information 403 in (b), and the language information in (b). 404 is language information used for analysis. Alternatively, in addition to the language information 402, 403, and 404, language information such as the language information 405, 406, and 407 at the end that summarizes their emotions may be considered for analysis.
The division writing unit 204 reads out language information to be analyzed from the database server 2. Then, a so-called segmentation process is performed to decompose the language information into language elements. Separation is a process of decomposing language information into language information elements that are meaningful character string elements.

Taking the language information 405 shown in FIG. 4 (a) as an example, the text information “where to go, wherever you go, look for work in the country, go to an unknown land” is broken down into “where”, The language elements of “good”, “somewhere”, “go”, “region”, “work”, “search” are obtained.
After completion of the segmentation by the segmentation unit 204, the clustering unit 205 excludes language elements whose appearance frequency is so low that the appearance frequency is negligible, particles that do not make sense, and the like, which are subject to clustering. Set.

In the clustering, if the clustering dictionary 206 is used, different words can be handled as the same word depending on the part of speech or the next following word, while indicating the same meaning. Specifically, for words that mean “clean”, in addition to “clean”, words such as “looks pretty”, “clean”, and “clean” are extracted as separate language elements. It can be handled in the subsequent processing as the same “clean” language element.
In addition, when it is not desirable to handle the phrase “anywhere” as the language element “anywhere” and the language element “good”, the language element “anywhere” and the language element “good” continuously appear in the clustering dictionary 206. If it appears, it can be set to handle it as a language element “anywhere”.

  The clustering unit 205 obtains the “distance” between the language elements based on the co-occurrence relationship of the language elements, and groups the language elements having a short distance as one component cluster. The distance between the language elements is determined by the combination of one language element and another language element that appear at the same time, and the appearance frequency of the combination. In the first embodiment, the phrase “appears at the same time” indicates that one language element and another language element appear in the language information indicating the goal, action, or decision input on the same day. Shall.

The distance is closer as the frequency of occurrence of one language element and another language element increases. For example, when the language element a and the language element b appear 12 times simultaneously and the language element a and the language element c appear 8 times simultaneously during the input reception period, the distance between the language element a and the language element b is This is closer than the distance between the language element a and the language element c.
The clustering unit 205 determines the distance between the language elements as described above, and sets the ones having a distance equal to or smaller than a predetermined threshold as one component cluster (cluster analysis). In the first embodiment, the following processing will be described on the assumption that four component clusters of component cluster I to component cluster IV have been created.

  In the configuration described above, language elements are grouped by using cluster analysis. However, the first embodiment is not limited to grouping language elements by clustering. As a method of grouping language elements, any method may be used as long as it is a method of grouping language elements by factor analysis or other similarities based on the frequency of appearance in combination.

1. Clustering by factor analysis Here, an example of clustering by factor analysis will be described.
5A, 5B, and 5C are diagrams for explaining clustering by factor analysis, and FIG. 5A shows “somewhere”, “go” written vertically and horizontally, respectively. It is the figure which described distance dnm between language elements, such as "local". (B) shows the factor loading of language elements having the distances shown in (a). (C) is a diagram showing that some factor is indicated by the distance between language elements.
The factor loading is a correlation coefficient of each language element with respect to some factor such as I and II. The larger the absolute value of this value, the stronger the correlation between the language element and the factor. The maximum factor loading is 1.

According to (a), the distance between “somewhere” and “go” is d12, and the distance between “go” and “region” is d23. Also, according to (b), it is shown that the factor loading for the factor “I somewhere” is 0.916, and that the language element “somewhere” has a relatively large correlation with the factor I. Yes. (C) is the figure which displayed the axis | shaft I showing the factor I by the orthogonal rotation, and the axis | shaft II showing the factor II according to the plot showing each language element. In addition, each axis | shaft showing each of factor I, II, and III is mutually orthogonally crossed.
In clustering using factor analysis, a language element in which a factor load for a certain factor (for example, factor I) is larger than a predetermined value is defined as one cluster. When the predetermined value is set to 0.4, in the example shown in FIG. 5B, the language elements “somewhere”, “go”, “region”, “search”, and “work” all have factor I. It is classified into the component cluster to represent.

-2 Correlation between component element clusters and input dates The language information unit generation unit 207 associates any one of the component element clusters I to IV with a plurality of dates on which language information is input. As a method of association, the language elements included in the language information input on a predetermined input date are compared with the language elements constituting any of the component cluster clusters I to IV, and at least the component cluster clusters I to IV are compared. There is one in which one language element is associated with an input date in which a language element included in the component cluster occupies a predetermined ratio or more of language elements included in input language information.

FIG. 6 is a diagram for explaining the association between the component cluster and the input date. As shown in FIG. 6 (a), the input acceptance dates from June 6 to June 19 are the input dates, and the component clusters I to IV are set as shown in FIG. 6 (b). Shall. Further, the predetermined ratio is 70% or more.
In such a case, when the language element input on June 6 is compared with the component cluster I, among the eight input language elements a, s, m, h, r, n, o, i , Six language elements a, m, r, i, and o are included in the component cluster I. Therefore, the language elements included in the component cluster I account for 70% of the language elements input on June 6. Accordingly, the component cluster I is associated with the language information input on June 6.

In addition, the five language elements a, s, u, d, and z input on June 9 have a component cluster including any four of the language elements a, s, u, d, and z. No corresponding component cluster exists.
Further, when the language element input on June 14 is compared with the component cluster II, six of the eight language elements s, h, i, n, j, o, u, and t that are input. The language elements s, h, n, j, u, and t are included in the component cluster II, and 70% of the language elements input on June 14 are occupied by the language elements included in the component cluster II. Yes. Accordingly, the component cluster II is associated with the language information input on June 14th.

The language information unit generation unit 207 associates the component clusters with consecutive input dates as described above. As a result, as shown in the figure, among the consecutive input dates, the component cluster corresponds only to June 6 and June 14, and the component clusters I and II are arranged in the order of the input date. It becomes.
Further, the association between the language information input on the input date and the component cluster is not limited to the example described above. For example, it is possible to associate one input date with a component cluster that includes the largest number of language elements included in the language information input on the input date. In this case, the component cluster is associated with more input days than described above. For this reason, the change of the input language information can be detected in more detail.

3. Detection of discontinuity Next, when a discontinuity of component clusters occurs in a series of component clusters associated with consecutive input dates, which is performed by the language information unit generation unit 207, and before the discontinuity The process of dividing the language information stored in the database server 2 will be described later.
FIG. 7 is a diagram showing a series of component clusters associated with consecutive input dates. As shown in the figure, the component cluster I is associated with the input dates June 1 and June 7, and is associated with June 4 between June 1 and June 7. There are no component clusters. In addition, the component cluster III is associated with the input date June 8 following the input date June 7.
In such a case, in the first embodiment, it is considered that there is a discontinuity of the component cluster between the input date June 7 and the input date June 8. The position where there was a discontinuity is indicated in the figure by a discontinuity point 601.

  Further, according to the example shown in FIG. 7, the component cluster III is associated with the input date June 8 and June 9, and the component cluster II is associated with June 14. However, the component cluster III is associated with the next input date, June 15th. When there is a change in the component cluster but the component cluster before the change is again associated with the input date immediately after the change, in this embodiment, the input dates June 9 and June 14, and the input date It is possible not to set a discontinuous point between June 14 and June 15. At this time, how many days of the input date are considered immediately after the change can be appropriately determined according to the amount of accumulated language information, the purpose of counseling, and the like.

Further, according to the example shown in FIG. 7, after the component cluster III is associated on June 15, the component cluster IV is input on the input date June 16, June 17, and June 18. Are associated. Therefore, a discontinuous point 602 is set between June 15 and June 16.
Further, Embodiment 1 is not limited to such a configuration, and when there are component clusters having different types in a series of component clusters, all boundaries between individual element clusters are regarded as discontinuous points. May be. In this case, a discontinuous point 603 and a discontinuous point 604 are set in addition to the discontinuous points 601 and 602.

After setting the discontinuous points, the language information unit generation unit 207 generates a language information unit by dividing the language information before and after the discontinuous points. According to the example shown in FIG. 6, the language information unit U1 is created on the input date June 1, June 4, and June 7. Also, the language information unit U3 is created on the input dates June 16, June 17, and June 18.
If the discontinuous points 603 and 604 are not set, the input date June 8, June 9, June 14 and June 15 creates the language information unit U2, and the discontinuous points 603 and 604 are set. In the case of setting, the input date June 8 and June 9 create the language information unit U4, and the input date June 14 and the input date June 15 are the language information unit U5 and the language information, respectively. Unit U6 is created.

In the example illustrated in FIG. 7, only the case where the input date and the component cluster are associated with each other one by one is illustrated. However, the first embodiment associates the input date with at least one of the component clusters. A language element input on one input date may be associated with a plurality of component clusters. In such a case, for example, it is considered to be continuous when adjacent component clusters are associated with consecutive input dates, and discontinuous when there is no common component cluster. It is done.

In such a case, when one component cluster I is associated with the input date a, and when the component cluster I and the component cluster IV are associated with the input date a + 1 that is continuous with the input date a, Since the attached component cluster includes the common component cluster I, it is determined to be continuous. On the other hand, when one component cluster I is associated with the input date a and component cluster III and component cluster IV are associated with the input date a + 1 continuous with the input date a, the associated component Since the cluster does not include something in common, it is determined to be discontinuous.
Alternatively, it may be considered that it is continuous only when all adjacent component clusters coincide with each other, and it is determined that the adjacent component clusters are discontinuous when they include mismatched component clusters.

4. Analysis The language information analysis unit 203 analyzes the language information included in each language information unit by associating the difference between the previously input language information and the later input language information with a change in the user's emotion. To do.
In other words, in the first embodiment, for example, in the language information unit U2, the language information input on the input date June 8 is interpreted as indicating an emotion that has been grasped as an action or a decision to be initially made for the user. Then, the language information input on the input date June 15 is interpreted as indicating the final feeling that the user was not aware of at the beginning.
In the first embodiment, based on the above interpretation, the emotion of the user changes from the emotion input on the input date June 8 to the emotion input on the input date June 15 from June 8 to 15. It is determined that

Such Embodiment 1 can give the user an opportunity to organize his / her thoughts over a plurality of days by the SAT method, and can appropriately grasp the change of the user's emotion at this opportunity.
In the first embodiment, the language information analysis unit 203 can analyze the language information included later in the language information unit in association with information that is not recognized by the user at first. In other words, in the first embodiment, only the language information input on the input date June 7 out of the language information included in the language information unit U1 is the final action to be taken on the image recalled by the user by the theme information. It is adopted as information indicating.
In such a case, whether only the language information on the input date June 7 or the language information on the input date June 4 is adopted depends on the scale of the accumulated language information and the discontinuity point. Needless to say, it is appropriately determined depending on the setting interval, the purpose of counseling, and the like.

The first embodiment described above is performed based on the following grounds.
That is, in the counseling system of the first embodiment, the user freely inputs a language based on the given theme information. In this process, it is thought that the user's feelings are organized and changed by making their thoughts into letters. However, in a database that accumulates linguistic information input by users over multiple days, the user started thinking about one event, and at what timing emotions about other events influenced and the previous thought changed I don't know if the thinking about one event has settled down and the thinking about the next event has started.

In the first embodiment of the present invention, the user himself / herself is aware at the beginning of the counseling by objectively determining the change or switching of the user's thinking target and performing analysis by dividing the thinking from the start to the interruption or termination into one break. It aims to detect the final emotions and emotional changes of some event that is not.
In order to realize such an object, in the first embodiment, as a specific technique for determining a break from the start to the stop or end of thinking, the component cluster is compared with the language information stored in the database. We observed changes in information content. Then, from the observation result, a break from the start to the end of thinking or the end or stop was detected, and a language information unit was created by dividing the database into the language information by this break.

Furthermore, in the first embodiment, the language information is analyzed in units of language information units. With such a process, it becomes possible to extract only emotions such as changes in emotions from the start to the end of thinking about one event, and final actions and decisions on a given theme.
That is, in the conventional data search using a plurality of keywords, keywords are set according to the content that the user desires to acquire. However, the first embodiment not only acquires data of specific content but also the time of the keyword in the entire data. Change can be observed.

FIG. 8 is a flowchart illustrating a counseling control program executed in the counseling system of the first embodiment described above, and shows a program executed by the similarity determination unit 201 and the language information unit generation unit 207.
As illustrated in FIG. 8, in the similarity determination unit 201, the segmentation unit 204 generates language elements by segmenting the language information stored in the database server 2 (S 1). For example, the clustering unit 205 determines the similarity between the language elements using the distance between the language elements represented by the Euclidean distance or the like (S2), and configures one language element whose distance is closer than the threshold. Element clusters are set (S3).

  The language information unit generation unit 207 takes in the component cluster data generated by the clustering unit 205 and associates it with the input date. For this reason, first, the count value n of the input date is set to 1 (S4). Then, it is determined whether the first day is an input date, and if it is an input date, it is determined whether there is a component cluster corresponding to the input language element (S5).

As a result of the determination, when there is no component cluster corresponding to the first day (S4: No), one count value n is added (S7).
If it is determined in step S5 that there is a component cluster corresponding to the language element input on the nth day (S5: Yes), the nth component cluster is associated (S6). Then, the language information unit generation unit 207 determines whether the count value of n + 1 obtained as a result of the addition is equal to or greater than the number of input reception days (S8). ), Step S5 is executed again, and it is determined whether there is a component cluster corresponding to the language element input for the nth day after the addition.

  In step S8, when n after addition exceeds the number of input reception days (S8: Yes), it is assumed that the processing has been completed for all input reception days. And in order to produce | generate a language information unit, it transfers to the process concerning the division | segmentation of language information. In order to divide the linguistic information, the linguistic information unit generation unit 207 determines a location where discontinuity occurs in the component cluster associated with the input date (S9).

  As a result of the determination, if there is a discontinuous point at which the component cluster is discontinuous (S10: Yes), the language information is divided before and after the discontinuous point to generate a language information unit (S11). The linguistic information analysis unit 203 analyzes linguistic information for each linguistic information unit, and extracts information related to changes in the user's emotions and final behavior and purpose based on before and after the input of the linguistic information included in the linguistic information unit. .

  The counseling system and the counseling device according to the first embodiment described above can generate a language information unit based on a change in emotion and thought of language information in which a user freely expresses his / her emotion. The linguistic information unit generated in this way can generate a linguistic information unit that can be regarded as one unit from the start to the end of the user's thought. Therefore, the linguistic information analysis unit 203 analyzes the linguistic information in units of the created linguistic information unit, so that the user can input a predetermined feeling from a document input by using a more appropriate expression. It is also possible to detect conclusions and feelings obtained over a period of days. Such feelings and the like are obtained for the first time during a free description of some event of interest to the user himself, and it is likely that the user himself is not initially aware of it.

  Moreover, in Embodiment 1 described above, only the case where the text information which the user input was applied to language information was demonstrated. However, the counseling system and the counseling device of Embodiment 1 are not limited to those that apply text information to language information. For example, when language information is input as speech, the language information input by speech can be handled in the same manner as in the first embodiment by extracting language information and language elements from speech.

(Embodiment 2)
Next, Embodiment 2 of the present invention will be described. The second embodiment will be described by taking a counseling system as an example as in the first embodiment. Since the overall configuration of the counseling system according to the second embodiment is the same as that shown in FIGS. 1 and 2 described in the first embodiment, illustration and description thereof are omitted here.
9A and 9B are diagrams for explaining the counseling system according to the second embodiment. In the counseling system of the second embodiment, when the WEB server 1 provides theme information, it provides a screen 803 for allowing an episode recalled by the theme information to be input in a free expression (FIG. 9A). At the same time, map information for inputting information related to the location related to the episode is provided (FIG. 9B).

  More specifically, as shown in the figure, a “record this episode location” button 801 is provided together with a screen 803 for providing theme information, and whether or not to input information on the location related to the episode to the user is determined. Let them choose. When the user selects to record the location of the episode by clicking the button 801 or the like, the map information 802 of (b) is provided instead of FIG. 9 (a).

Further, in the second embodiment, a position input receiving unit for inputting the position of the place recalled by the theme information onto the map information 802 is provided. In the second embodiment, the position input means is realized by icons 804 and 805 with explanatory texts such as “where the episode occurred” and “the direction of viewing the scenery related to the episode” and an input device such as a mouse. Yes.
That is, in the second embodiment, the icon 804 is highlighted together with the display of the map information 802 shown in (b). The user clicks an arbitrary point on the map information 802 while the icon 804 is highlighted. By clicking, information (location information) related to the location corresponding to the clicked coordinate on the map information 802 is sent to the database server and stored in association with the theme information or episode.

The location information stored in the database server in this way can be used for city planning and development by public organizations and companies. In other words, if the theme information is “What do you feel in this area or your life now?” And the user writes a pessimistic episode and records the location, this location is pessimistic to the user It is presumed to be recalled with various emotions.
On the other hand, when the same theme information is given, when the user writes a nostalgic episode and records a place, it is presumed that this place is recalled with feelings nostalgic for the user.

In the second embodiment, the emotion related to the place is provided together with the screen for prompting the input of the episode described in the first embodiment, so that the user's emotion related to the place can be accumulated in a time series over a plurality of days. For this reason, Embodiment 2 can also observe the change of the user's emotion regarding a place, and its history.
Considering such information, it is possible to proceed with development and urban planning in line with the feelings of local residents. For example, a place where a negative image for residents can be converted into a plus image can be used, or a place where a strong image can be used for local residents can be used while saving past images. In this case, it is possible to suppress the emotional trap between the local residents and the development side accompanying development and city planning, and it is possible to proceed with development smoothly.
In addition, the image regarding the location for local residents does not necessarily match the obvious information such as famous places and historic sites. According to the second embodiment, it is possible to grasp emotions related to the location of local residents that are difficult to estimate from the outside. Such feelings are useful information that could not be obtained by the prior art.

(Embodiment 3)
Next, a third embodiment of the present invention will be described.
FIG. 10 is a diagram for explaining the counseling device according to the third embodiment. The illustrated configuration shows the language information analysis unit 1000 of the third embodiment. The language information analysis unit 1000 searches for a language information unit using a keyword received by the keyboard 1003 and the display 1001 that accepts keyword input, and the keyword received by the keyboard 1003 and the display 1001, and finds a language information unit that includes language information that matches the keyword. A language unit selection unit 1002 for selection is provided. The language information unit selected by the language unit selection unit 1002 is output to the outside by the display 1001.

In the above configuration, the keyboard 1003 and the display 1001 function as a keyword input receiving unit, the language unit selection unit 1002 functions as a language information unit selection unit, and the display 1001 functions as a language information unit output unit.
That is, in the third embodiment, an administrator of the WEB server 1 or a person who has requested the administrator to collect data for counseling (hereinafter referred to as a requester) extracts data necessary for counseling. Enter keywords that you think are relevant.

When the client is, for example, a health company and data is extracted for the purpose of investigating the user's future design awareness, it is conceivable that words such as “future”, “life”, and “fund” are input as keywords. For the input of keywords, an input field is displayed along with a message such as “Please enter keywords” on the display 1001, and the client inputs a keyword such as “future” using the keyboard 1003.
The language unit selection unit 1002 performs keyword search for the language information unit generated by the language information unit generation unit 207 and stored in the database server 2, and detects the language information unit including the keyword. The detected language information unit is output to the display 1001 in units of language information units.

  Since the output language information unit includes keywords such as “future”, “life”, and “fund”, it can be considered that the user describes data about a theme related to his / her future plan. In addition, since the language information unit is considered to be a group of data that is thought about some factor, it is considered that this factor may be a future plan of the user. Alternatively, it is likely that the factor is related to the future plan, even though the factor itself is not the user's future plan.

Therefore, according to the third embodiment, the language information unit in which the episode related to the purpose of the investigation is written can be automatically extracted and provided to the client. For this reason, it is possible to reduce the processing load for the client to detect data necessary for the investigation from a large amount of data.
The language information unit is a set of data describing some factor. For this reason, Embodiment 3 can specify and extract the whole episode described in relation to a keyword, not simply extracting a document including the keyword by keyword search.

That is, Embodiment 3 can easily acquire data representing a user's subjective feelings until a thought is made for a factor related to an investigation target, a conclusion is made, and the thought is terminated. It can be said that the data acquired by the third embodiment accurately and appropriately reflects the user's feelings compared to the answer to the conventional questionnaire that answers a preset question.
According to such data, depending on the purpose of the survey, it is considered that there are many cases where the client can accurately know the psychology of the user even if the client is not a counselor with special expertise.

(Embodiment 4)
In the fourth embodiment of the present invention, the degree of self-affirmation, self-denial, self-request, and other-party request that the user is subjectively aware of is determined for the language information unit extracted by the third embodiment. The balance of self-affirmation, self-denial, self-request and demand for others is an indicator of whether or not the user's psychological state is healthy. Should the user be encouraged to use more advanced counseling such as face-to-face counseling? It is a criterion for judging whether or not.

In the fourth embodiment, it is assumed that the determination of self-affirmation, self-denial, self-request, and other-party request is executed by the language information analysis unit 203 illustrated in FIG.
In addition, self-affirmation means having a positive image intuitively when it sees itself as others. Self-denial means that the user has an intuitive negative image of himself / herself. Further, the other person request is a request that the user recognizes that the user should execute in order to realize the request. The other person request is a request that the third party other than itself desires to execute.

  The language information analysis unit 203 extracts at least one of self evaluation, self-reliance, and subjective evaluation by the user who has input the language information from the language information included in the language information unit selected by the language unit selection unit 1002 To do. Then, at least one change over time of the extracted self-evaluation, self-reliance, and subjective evaluation of dependence is evaluated. Such a language information analysis unit 203 functions as a subjective extraction unit and a subjective evaluation unit of the fourth embodiment.

  Here, a method of determining self-affirmation and self-denial, self-request and other-party request will be briefly described. In the case of determining the user's subjective self-affirmation, in the fourth embodiment, for example, the question 304 to the question 307 in the input form shown in FIG. Please add the question. When the user inputs a plus to such a question, the language information analysis unit 203 determines that the user's emotion tends to be self-affirming. When the user inputs a minus to the question, the language information analysis unit 203 determines that the user's emotion tends to be negative.

  In the case of determining a user's subjective self-request, in the fourth embodiment, for example, the questions 308 to 311 in the input form shown in FIG. "What should I do, (b) or who do I want to do?" When the user inputs an answer only to the question (a) with respect to the questions (a) and (b), the language information analysis unit 203 determines that the user's self-request is high. In addition, when the user inputs an answer only to the question (b), the language information analysis unit 203 determines that the request for others from the user is high.

Furthermore, when the user does not answer any of the questions (a) and (b) or answers the questions (a) and (b), the user is balanced between the self-request and the other-person request. In particular, it is determined that one of them is not in a high state.
Prior to such determination, in the fourth embodiment, first, a language information unit is selected by a keyword search in the third embodiment. The language information unit selected by the same keyword is used as data of one language information. This data is language information obtained by collecting a plurality of days of language information input by the user for one day.

  Next, the linguistic information analysis unit 203 displays by plotting on a graph that is input on each input date and has the coordinates of the plus or minus of the self-evaluation and the input of the answer to the questions (a) and (b). The plot is sequentially displayed before and after the input date, and shows changes over time such as user self-affirmation. Such a graph may also be displayed on the display 1001 shown in FIG.

  FIGS. 11A, 11 </ b> B, and 11 </ b> C are diagrams illustrating the analysis results of the fourth embodiment. (A) is the analysis result of the data of the language information unit selected by the keyword regarding "music, hobby". In the graph of the analysis result, the vertical axis (y-axis) shows the tendency of self-request and other-person demand, and the horizontal axis (x-axis) shows the positive and negative degrees of the self-image. In the fourth embodiment, a point where the vertical axis and the horizontal axis intersect is set as the origin (0, 0).

  Then, in the answer input on December 25, which is the first input date, if the self image is positive, 1 is added to the x coordinate of the origin (0, 0), and if it is negative, 1 is subtracted. If only the answer to question (a) is input, 1 is added to the y coordinate of the origin (0, 0), and if only the answer to question (b) is input, 1 is subtracted. Further, when there is no answer in any of the questions (a) and (b), or when an answer is input in any of them, the y coordinate is not changed. The plot P of December 29 is displayed at the coordinates (1, 1) determined in this way.

  Next, the linguistic information analysis unit 203 adds the coordinates (1) based on the positive or negative of the self-evaluation of the linguistic information input on December 19 and whether or not the answer to the questions (a) and (b) is input. , 1) is changed as necessary. In the illustrated example, since the coordinates have changed from (1,1) to (2,0), on December 29, the user answers his / her image as a plus and asks for the other person's request (b) ) Only.

  The language information analysis unit 203 sequentially determines plots based on the language information input on one day according to the order of the input dates by the method described above. Then, the plot P is displayed at the determined coordinates, and the vector b is displayed between the plots P adjacent to the input date. Further, a combined vector B of all vectors b is obtained and displayed in the graph. Vector B shows the change over time of self-evaluation regarding the user's music and hobbies.

In the example shown in FIG. 11A, the user's self-evaluation regarding music and hobbies from December 25 to April 24 tends to increase the tendency of independence and self-affirmation, and the problem is introspection It turns out that it is easy to make and internalize.
FIG. 11B shows the result of analyzing the data of the language information unit selected by the keyword relating to “shopping, eating, traveling” in the same procedure as described above. According to the results shown in FIG. 11 (b), it can be seen that the self-evaluation regarding the user's shopping, eating, and traveling tends to increase self-affirmation, although the independence is lower than that of music and hobbies.

Further, FIG. 11C shows the result of analyzing the data of the language information unit selected by the keyword related to “husband, mother” in the same procedure as described above. According to the result shown in FIG. 11C, it can be seen that the self-evaluation regarding the husband and mother of the user tends to decrease self-affirmation and increase dependency, and the problem is likely to be externalized.
Embodiment 4 described above can extract and evaluate a user's self-evaluation, self-reliance, and changes over time. Such information serves as an index for determining whether the user's psychological state is in a healthy direction and whether more advanced counseling is required. Furthermore, Embodiment 4 can make such a determination for each theme such as music and hobbies.

  Therefore, the fourth embodiment can specify, for example, a cause that the user cannot be independent or a cause that the user is not confident. Conversely, it is also possible to identify the cause that the user can maintain a high self-evaluation. Furthermore, when such a self-evaluation changes, the cause can be specified.

  The counseling system, counseling device, and counseling control program of the present invention described above can construct a psychosocial information system by applying it to a consciousness survey targeting many users. When configured in this way, it becomes possible to detect changes in collective psychology that occur within a short period of time, and human psychological status that has been obtained only indirectly as a socioeconomic index or the like has been converted into a social index. can do.

The counseling system, counseling device, and counseling control program of the present invention include the subjectivity of each user in the collected information. Collective information on how it was received can be extracted.
In particular, the fourth embodiment can construct a system (stress management) that cares about psychology and cognition. By using stress management, psychological care (population approach) in daily life can be realized. For this reason, it can be applied to the construction of a system that cares the user from both the whole society and the individual, such as introducing a specialized institution or the like capable of more advanced counseling (high risk approach) depending on the psychological state of the user.

It is a figure for demonstrating the concept of the counseling system of Embodiment 1 of this invention. It is a block diagram for demonstrating in detail the analysis program shown in FIG. It is the figure which showed the specific example of the input form shown in FIG. It is the figure which illustrated the language information which the user input according to the input form shown in FIG. It is a figure for demonstrating the clustering by the factor analysis of Embodiment 1 of this invention. It is a figure for demonstrating matching with the component cluster of Embodiment 1 of this invention, and an input date. It is the figure which showed a series of component cluster matched with the continuous input date of Embodiment 1 of this invention. It is the flowchart which illustrated the counseling control program performed with the counseling system of Embodiment 1 of this invention. It is a figure for demonstrating the counseling system of Embodiment 2 of this invention. It is a figure for demonstrating the counseling system of Embodiment 3 of this invention. It is a figure for demonstrating the counseling apparatus of Embodiment 4 of this invention.

Explanation of symbols

1 server 2 database server 3 input form 4 PC
DESCRIPTION OF SYMBOLS 101 Analysis program 201 Similarity determination part 203,1000 Language information analysis part 204 Segmentation part 205 Clustering part 206 Clustering dictionary 207 Language information unit generation part 601, 602, 603, 604 Discontinuous point 801 Button 802 Map information 803 Screen 804 Icon 1001 Display 1002 Language unit selection unit 1003 Keyboard

Claims (11)

Input accepting means for accepting input of language information, which is information related to a language, over a plurality of days;
Language information receiving means for receiving the language information input via the input receiving means via a network;
Storage means for storing the language information received by the language information receiving means for a plurality of days;
Grouping means for classifying linguistic elements included in the linguistic information accumulated by the accumulating means based on similarity between the language elements, and generating a group of a plurality of language elements;
Associating means for associating an input date when the language information is input with at least one of the groups generated by the grouping means;
In a group that is associated with the input date by the association unit and arranged in the order of the input date, when a discontinuity of the group type occurs, accumulation is performed in the accumulation unit before and after the discontinuity. Language information dividing means for generating a language information unit by dividing the linguistic information,
Linguistic information analyzing means for analyzing linguistic information in units of the linguistic information unit generated by the division by the linguistic information dividing means;
A counseling system characterized by comprising: Stored information acquisition means for acquiring linguistic information that is input over a plurality of days and related to the stored language;
Grouping means for classifying the language elements included in the language information acquired by the accumulated information acquisition means based on the similarity between the language elements, and generating a group of a plurality of language elements;
Associating means for associating an input date when the language information is input with at least one of the groups generated by the grouping means;
In the group that is associated with the input date by the association unit and arranged in the order of the input date, when the discontinuity of the group type occurs, the accumulated information acquisition unit before and after the discontinuity Language information dividing means for generating a language information unit by dividing the language information acquired by
Linguistic information analyzing means for analyzing linguistic information in units of the linguistic information unit generated by the division by the linguistic information dividing means;
A counseling device comprising:   Providing a message that provides the user with message information including at least action / decision information input instruction information for instructing the user to write theme information that gives a thinking theme, and to write information on an action or decision to be taken for an episode recalled by the user based on the theme information The counseling device according to claim 2, further comprising means. The message providing means provides map information for allowing the user to input information about a place recalled by the theme information when providing the theme information;
The counseling device according to claim 3, further comprising a position input receiving unit for inputting a position of a place recalled by the theme information onto the map information. The grouping means includes
Element decomposition means for decomposing language information into language elements included in the language information;
Similarity determination means for determining the similarity of language elements based on a relative relationship relating to the appearance of one language element generated by decomposition by the element decomposition means and other language elements,
The counseling device according to any one of claims 2 to 4, wherein language elements are clustered based on the similarity determined by the similarity determination unit to generate a plurality of groups. The association means includes
Associating at least one of the groups generated by the grouping means with an input date that occupies a predetermined percentage or more of the language elements included in the language information in which the language elements included in the group are input, or The counseling device according to any one of claims 2 to 5, wherein an input date is associated with a group including the most language elements included in the language information input on the input date. The language information analysis means includes
The linguistic information included in the linguistic information unit analyzes the difference between the linguistic information input earlier and the linguistic information input later in association with a change in the user's emotion. The counseling device according to claim 6. The language information analysis means includes
The linguistic information included in the linguistic information unit analyzes the linguistic information input later in association with information that the user is not aware of at the beginning. The counseling device described. The language information analysis means includes
Keyword input accepting means for accepting keyword input;
Language information unit selecting means for searching the language information unit using a keyword received by the keyword input receiving means and selecting a language information unit including language information matching the keyword;
Language information unit output means for outputting the language information unit selected by the language information unit selection means to the outside;
The counseling device according to any one of claims 2 to 8, wherein the counseling device is provided. The language information analysis means includes
Subjective extraction means for extracting at least one of self-evaluation, independence, and subjective evaluation by a user who has input language information from language information included in the language information unit selected by the language information unit selection means;
Subjective evaluation means for evaluating at least one change over time of the subjective evaluation of self-assessment, self-reliance, and dependence extracted by the subjective extraction means;
The counseling device according to claim 9, comprising: On the computer,
A stored information acquisition function for acquiring language information that is input over a plurality of days and is related to the stored language;
A grouping function for classifying the language elements included in the language information acquired by the accumulated information acquisition function based on the similarity between the language elements, and generating a group of a plurality of language elements;
An association function that associates an input date when language information is input with at least one of the groups generated by the grouping function;
In the group that is associated with the input date by the association function and arranged in the order of the input date, when the group type discontinuity occurs, the accumulated information acquisition function before and after the discontinuity A language information dividing function for generating a language information unit by dividing the language information acquired by
A language information analysis function for analyzing language information in units of the language information units generated by the division by the language information division function;
A counseling control program characterized by realizing

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