WO2017104571A1

WO2017104571A1 - Information processing device, information processing method, and recording medium

Info

Publication number: WO2017104571A1
Application number: PCT/JP2016/086728
Authority: WO
Inventors: 俊輔河野; 大地木村; 英司平尾
Original assignee: 日本電気株式会社
Priority date: 2015-12-14
Filing date: 2016-12-09
Publication date: 2017-06-22
Also published as: JPWO2017104571A1

Abstract

The purpose of the present invention is to evaluate the validty of the association between the cause parameter and the effect parameter in a cause-and-effect relationship. The information processing device according to the present invention is provided with: a document accumulation unit which can retain one or more documents; a cause-and-effect relationship extraction unit which extracts, from the one or more documents, an event in which there is an increase in the cause parameter in a cause-and-effect relationship and an event in which there is a decrease in the cause parameter in the cause-and-effect relationship; a consistency analysis unit which analyzes consistency between the two events extracted by the cause-and-effect relationship extraction unit, that is, the event in which there is an increase in the cause parameter in a cause-and-effect relationship and the event in which there is a decrease in the cause parameter in the cause-and-effect relationship; and a result output unit which outputs the results of the analysis performed by the consistency analysis unit.

Description

Information processing apparatus, information processing method, and recording medium

The present invention relates to a technique for analyzing a causal relationship between elements constituting an event.

There are known systems that visualize the elements that make up an event and the causal relationship between each element. For example, Patent Document 1 discloses a technique for generating a causal relationship diagram based on whether the relationship between elements constituting the system is increasing or decreasing. Specifically, the technique disclosed in Patent Document 1 visualizes a causal relationship between elements by using a coincidence rate between a change in a cause-side element and a change in a result-side element.

Patent Document 2 describes a technique for describing a causal relationship structure between nodes by connecting nodes (elements) constituting the system by an arc and generating a simulation program using a simulation model inheriting the structure. Is disclosed.

Patent Document 3 discloses a causal chain relationship (a normal sequence chain, a reverse sequence chain) determined based on a result of comparing a causal direction related to a causal relationship between a plurality of defect records and an order relationship set in the plurality of defect records. ) Is disclosed.

Further, Non-Patent Document 1 discloses a description method for visualizing the causal relationship.

JP 2013-130946 A JP 2007-286777 A International Publication No. 2005/101253

Referring to information representing the causal relationship visualized, there are cases where current status analysis and problem solving methods are examined. Depending on the definition of the cause-and-effect relationship, there may be cases where consistency between the causal element and the resulting element may not be achieved when the causal element increases or decreases. Problems arise. That is, depending on the definition of the causal relationship, the relationship between the change (increase or decrease) of the causal element in a causal relationship and the change (increase or decrease) of the resulting element may not always match. .

As an example, consider the causal relationship of lowering the brand image due to lower product prices. Such a causal relationship can be expressed using, for example, an effective graph composed of nodes called “price” and “brand image” and directional links connecting these nodes, as shown in FIG. is there. From the specific example shown in FIG. 1, it is possible to read a causal relationship that “brand image” also decreases (decreases) when “price” decreases (decreases). On the other hand, from the specific example shown in FIG. 1, it is possible to read the causal relationship that “brand image” also rises (increases) when “price” rises (increases). However, in general, the brand image does not always increase with the price increase. As shown in the above example, if consistency between the causal element and the resulting element is not achieved, there is a possibility that an erroneous decision will be made when analyzing the current situation and examining the problem solving method. is there.

On the other hand, the techniques disclosed in the above patent documents cannot always correctly evaluate the consistency of the causal relationship in the above case. That is, the technique disclosed in Patent Document 1 is a technique for generating a causal relationship diagram representing a relationship between elements based on past data regarding each element, and is not a technique for evaluating the consistency of the causal relationship. . The technique disclosed in Patent Document 2 is a technique for generating a simulation model from a causal relation description format that is easy for humans to understand, and is not a technique for evaluating the consistency of the causal relation. The technique disclosed in Patent Document 3 is a technique for analyzing the chain direction of the causal relationship between elements, and is not a technique for evaluating the consistency of the causal relationship.

The present invention has been made in view of the above circumstances. That is, the present invention provides information that can evaluate the consistency between the causal element and the causal element when the causal element increases and when the causal element increases and decreases. One of the main purposes is to provide an information processing apparatus and the like.

In order to achieve the above object, an information processing apparatus according to an aspect of the present invention includes a document storage unit that can hold one or more documents, an element that causes a causal relationship with respect to an event, and an element that results. The causal relationship extraction unit that extracts the causal relationship between the case where the element causing the increase and the case where the cause element decreases decreases from the document for each of the case where the cause element decreases, The consistency analysis unit that analyzes the consistency between the causal relationship when the causal factor increases and the causal relationship when the causal factor decreases, and the results analyzed by the consistency analysis unit A result output unit for outputting.

Further, in the information processing method according to one aspect of the present invention, a cause-and-effect relationship between an element causing a causal relationship regarding an event and a resulting element is increased when the above-described element causing the cause increases, For each of the cases where the above elements decrease, the causal relationship when the extracted cause elements increase from one or more documents and the causal relationship when the cause elements decrease And the result of the analysis is output.

The object is also achieved by an information processing apparatus having the above-described configuration, a computer program for realizing the information processing method by a computer, a computer-readable recording medium storing the computer program, and the like.

According to the present invention, it is possible to provide information capable of evaluating the consistency between the causal element and the resulting element when the causal element in the causal relationship increases and decreases. is there.

FIG. 1 is a diagram illustrating an example of a causal relationship. FIG. 2 is a block diagram illustrating a functional configuration of the information processing apparatus according to the first embodiment of this invention. FIG. 3 is a flowchart illustrating an example of processing performed by the information processing apparatus according to the first embodiment of this invention. FIG. 4A is an explanatory diagram illustrating an example of a method for representing information representing elements constituting an event and a causal relationship between the elements in the first embodiment of the present invention. FIG. 4B is an explanatory diagram illustrating another example of a method for representing information representing elements constituting an event and a causal relationship between the elements in the first embodiment of the present invention. FIG. 5A is an explanatory diagram illustrating still another example of a method for representing information representing elements constituting an event and a causal relationship between the elements in the first embodiment of the present invention. FIG. 5B is an explanatory diagram illustrating still another example of a method for representing information representing elements constituting an event and a causal relationship between the elements in the first embodiment of the present invention. FIG. 6 is an explanatory diagram illustrating an example of a criterion for determining causality consistency in the first embodiment of the present invention. FIG. 7 is an explanatory diagram illustrating an example of an analysis result regarding causality consistency in the first embodiment of the present invention. FIG. 8 is a block diagram illustrating a functional configuration of the information processing apparatus according to the second embodiment of this invention. FIG. 9 is a block diagram illustrating a hardware configuration capable of realizing the information processing apparatus according to each embodiment of the present invention.

Hereinafter, an information processing apparatus and the like that can solve the above-described problems will be described in detail using each embodiment. In addition, the structure of the information processing apparatus described in each following embodiment is an illustration, and the technical scope of this invention is not limited to them. The division (for example, division | segmentation by a functional unit) of the component which comprises the information processing apparatus in each following embodiment is an example which can implement | achieve the said information processing apparatus. The implementation of the information processing apparatus is not limited to the following examples, and various configurations are assumed. That is, the constituent elements constituting the information processing apparatus in each of the following embodiments may be further divided, or one or more constituent elements may be integrated.

The information processing device described below may be configured using a single device (physical or virtual device), and may be realized using a plurality of separated devices (physical or virtual devices). Also good. When the information processing apparatus includes a plurality of apparatuses, each apparatus may be connected to be communicable via a wired network, a wireless network, or a communication network (communication line) appropriately combining them. Such a communication network may be a physical communication network or a virtual communication network. An information processing apparatus described below or a hardware configuration capable of realizing the components will be described later.

<First Embodiment>
[Description of configuration]
The first embodiment of the present invention will be described below in detail with reference to the drawings. The components described in the following embodiments are merely examples, and the technical scope of the present invention is not limited thereto.

FIG. 2 is a block diagram illustrating a functional configuration of the information processing apparatus 100 according to the first embodiment of the present invention. The information processing apparatus 100 is an apparatus that operates according to a software program (computer program) such as a computer.

The information processing apparatus 100 includes an input reception unit 101, a document storage unit 102, a causal relationship extraction unit 103, a consistency analysis unit 104, and a result output unit 105.

The input reception unit 101 (input reception unit) receives information representing an element constituting an event as an input. More specifically, the input receiving unit 101 receives, as an input, information representing an element that causes a causal relationship regarding the event and an element that results. In the present embodiment, the above-described event represents something (such as a phenomenon) that can occur in an actual environment or a virtual environment such as an information processing apparatus. Hereinafter, an element constituting an event may be simply referred to as an “element”. In addition, information representing elements and causal relationships between elements may be described as “causal relationship information”.

In the causal relationship information, the elements constituting the event are described or expressed as, for example, some form of data. The causal relationship information is expressed using, for example, a combination of information representing a cause element and information representing a result element. In addition, the causal relationship information may be expressed using, for example, a combination of information representing a cause element, information representing a result element, and information representing a relationship between these elements.

In the present embodiment, the codes related to the causal relationship are determined as follows. A causal relationship that represents the relationship that when the causal element increases (increases), the resulting element increases, and when the causal element decreases (decreases), the resulting element decreases. The sign is represented as a positive sign. Hereinafter, the causal relationship representing the relationship may be referred to as “positive causal relationship”. In addition, when the causal element increases, the resulting element decreases, and when the causal element decreases, the causal relation sign indicating that the resulting element increases is negative. It represents as a code | symbol. Hereinafter, the causal relationship representing the relationship may be referred to as “negative causal relationship”. The above-mentioned signs of the causal relationship are considered to be information representing the causal relationship between the causal element and the resulting element. More specifically, the sign of the causal relationship described above is considered to be information representing the relationship between the increase / decrease in the causal element and the increase / decrease in the resulting element. The information indicating the relationship between the elements may be expressed using, for example, the causal relationship code. Further, the causal relationship code may be expressed by using numerical values such as “+1” and “−1”, or other symbols.

Note that an increase in a certain element indicates an increase (increase) in some attribute (for example, characteristics, properties, quantity, etc.) that can be expressed qualitatively or quantitatively with respect to the element. In addition, a decrease in an element indicates, for example, that an attribute related to the element is decreased (decreased).

The document storage unit 102 (document storage unit) holds (accumulates) one or more documents. The document stored in the document storage unit 102 is not particularly limited as long as it is expected that the elements constituting the event and the causal relationship between the elements are described. Such a document may be, for example, a document published on the WEB (World Wide Web), a newspaper article, or a white paper. Such a document is not limited to the above example, and may be another appropriate document. The document storage unit 102 is not limited to a document composed of text data, but includes information that can be documented using appropriate analysis techniques (speech recognition, image analysis, etc.), such as voice, image, and moving image data. Various data may be held. The document storage unit 102 can store the document using, for example, a well-known file system or a database.

The causal relationship extraction unit 103 (causal relationship extraction means) includes a cause element and a result element included in the information (causal relationship information) received by the input receiving unit 101 from the document stored in the document storage unit 102. Extract the causal relationship between and. Specifically, the causal relationship extraction unit 103 extracts the causal relationship from the document for each of cases where the causal element included in the causal relationship information increases and decreases.

For example, the causal relationship extraction unit 103 analyzes the document stored in the document storage unit 102 using a well-known natural language analysis method (for example, morphological analysis), and includes causal elements included in the causal relationship information. Extract sentences that contain the resulting elements. And the causal relationship extraction part 103 extracts the causal relationship between the element used as a cause and the element used as a result represented in the extracted text. In this case, the causal relationship extraction unit 103 may extract such a causal relationship using, for example, a well-known natural language analysis (syntax analysis, semantic analysis, etc.) or a data mining (text mining method). . The causal relationship extraction unit 103 generates, for example, data representing the extracted causal relationship using the above sign, and the data (specifically, data representing the positive sign or the negative sign) is matched as described later. It may be provided to the sex analysis unit 104.

Note that the causal relationship extraction unit 103 uses, for example, voice analysis, image analysis, and other appropriate analysis techniques such as voice recognition and image analysis when the document storage unit 102 holds voice, image, video data, and the like. May be extracted (character information). Then, the causal relationship extraction unit 103 may extract the causal relationship from the extracted documentable information.

The consistency analysis unit 104 (consistency analysis unit) extracts the causal relationship when the causal element increases and the causal relationship when the causal element decreases, extracted by the causal relationship extraction unit 103. Analyze consistency. A method by which the consistency analysis unit 104 determines the consistency of the causal relationship will be described later.

The result output unit 105 (result output unit) outputs the result of the analysis by the consistency analysis unit 104. The method of outputting the analysis result by the result output unit 105 may be, for example, a method of outputting to an appropriate output device (display device) such as a display (not shown) or a method of outputting to a file. The result output unit 105 may transmit data representing the analysis result to another information processing apparatus or the like. The method by which the result output unit 105 outputs the analysis result information is not limited to the above, and other appropriate methods may be adopted.

The information processing apparatus 100 may acquire the causal relationship information from an input device (not shown) such as a keyboard, may be acquired from a database or the like (not shown), or another information processing apparatus (for example, FIG. You may acquire from the server etc. which are not shown. The method by which the information processing apparatus 100 acquires the causal relationship information is not limited to the above, and other appropriate methods may be adopted.

In the present embodiment, the information processing apparatus 100 includes a control unit, a storage unit, and an input / output unit as a hardware configuration. The control unit is configured using an arithmetic device such as a CPU, for example. The storage unit is configured using, for example, a RAM (Random Access Memory), a ROM (Read Only Memory), an HDD (Hard Disk Drive), and the like. The input / output unit is configured using various interfaces such as an operation unit, a display unit, and a communication interface. The functions of the information processing apparatus 100 described above are realized by the cooperation of these hardware and various programs stored in the storage unit. Note that a hardware configuration capable of realizing the information processing apparatus 100 will be described later.

[Description of operation]
Next, a specific example of processing performed by the information processing apparatus 100 will be described with reference to FIG. The flowchart illustrated in FIG. 3 is an example of the operation of the information processing apparatus 100, and the present embodiment is not limited to this. The execution order of the processing steps in the flowchart may be changed within a range that does not affect the processing result, and one or more processing steps may be executed in parallel. Also, the control of the process illustrated in FIG. 3 is performed, for example, by the control unit configuring the information processing apparatus 100 developing and executing a program stored in the storage unit.

First, in step S301, the input receiving unit 101 receives input of information (causal relationship information) representing elements constituting an event and a causal relationship between elements.

FIG. 4A shows an example of information (causal relationship information) representing the elements constituting the event and the causal relationship between the elements. In the specific example shown in FIG. 4A, the causal relationship information 400 is represented using a table format including a column 401 indicating a cause element and a column 402 indicating a result element. In each of the columns, data expressed in an appropriate format such as a character string, a numerical value, a code, and a symbol is set.

It should be noted that the causal relationship information may further include a column 403 indicating the code of the causal relationship as exemplified in FIG. 4B, for example. The causal relationship information may be expressed using other methods (forms). For example, as such an expression method, an expression method that uniquely defines the graph structure as shown in FIG. 5A may be used. In the graph structure shown in FIG. 5A, elements constituting an event are represented by using nodes of the graph, and the causal relationship between the elements is a directed link from the cause element (node) to the result element (node). It is expressed using. In addition, as illustrated in FIG. 5B, for links connecting nodes, a symbol representing the sign of the causal relationship between the nodes (a plus sign (“+”) in the case of a positive causal relationship), a negative case May be added with a minus sign ("-")).

Next, in step S <b> 302, the causal relationship extraction unit 103 sends the causal relationship between the causal element and the resulting element included in the causal relationship information received by the input receiving unit 101 to the document storage unit 102. Extract from accumulated documents. Specifically, the causal relationship extraction unit 103 extracts the causal relationship between when the causal element increases and when it decreases, from the document. As a method for extracting the causal relationship from the document, for example, a known method such as natural language processing or data mining may be used. As such a method, for example, a technique disclosed in the following reference may be used.

[Reference Document] Japanese Patent Application Laid-Open No. 2013-175097 Note that the method for extracting the causal relationship from the accumulated document is not limited to the above example.

Suppose, for example, that the following text is described in the accumulated document.

“We are reducing the cost of goods by increasing the economy of scale.”
From the above sentence, regarding the fourth line (400A in FIG. 4A) of the causal relationship information 400 in FIG. 4A, when the “economic economy of scale” increases (increases), the resulting “product cost” decreases. A causal relationship (negative causal relationship) with a negative sign of (decrease) is extracted.

As another example, it is assumed that the following text is described in the accumulated document.

“The economy of scale will be reduced and the cost of goods will be higher.”
From the above sentence, for the fourth line in FIG. 4A (400A in FIG. 4A), when the “economic economy of scale” decreases (decreases), the resulting “product cost” increases (increases). , A causal relationship with a negative sign (negative causal relationship) is extracted. In this way, the causal relationship extraction unit 103 determines whether the causal element and the resulting element for each of the cases where the “economic economy of scale” increases and decreases. Extract causality. The causal relationship extraction unit 103 may provide the consistency analysis unit 104 with a code representing the extracted causal relationship (specifically, data representing the code).

Next, in step S303, the consistency analysis unit 104 extracts the causal relationship when the causal element increases and the causal relationship when the causal element decreases, extracted by the causal relationship extraction unit 103. Analyze consistency between.

Specifically, the consistency analysis unit 104 compares the causal relationship when the causal element increases with the sign of the causal relationship when the causal element decreases. If these codes are the same, the consistency analysis unit 104 determines that these causal relationships are consistent. In other words, the consistency analysis unit 104 determines that these causal relationships are consistent when the causal relationships represented by the causal relationships match when the causal element increases and when the causal elements increase.

In addition, the consistency analysis unit 104 extracts the causal relationship when the causal relationship when the causal element increases and the causal relationship when the causal element decreases, or either causal relationship is extracted. If not, it is determined that these causal relationships are not consistent. In other words, the consistency analysis unit 104 does not match the relationship represented by the causal relationship when the causal element increases or decreases, or when any causal relationship cannot be extracted. It is determined that these causal relationships are not consistent.

The consistency analysis unit 104 may determine the consistency of the causal relationship based on, for example, a determination standard 600 illustrated in FIG. The criterion 600 includes a column (601, 604) indicating increase / decrease in the cause element, a column (602, 605) indicating increase / decrease in the result element, and the cause element and the result element. And columns (603, 606) representing the signs of the causal relationship. In addition, the determination criterion 600 represents a column (607) representing a result of comparing the signs of the causal relationship between the case where the factor causing the increase and the case where the cause is decreased, and the result of the consistency determination based on the comparison result. Column (608). In each of the columns, data expressed in an appropriate format such as a character string, a numerical value, a code, and a symbol is set. Arbitrary data may or may not be set at a location represented by the symbol “*” in the determination criterion 600. The consistency analysis unit 106 is not limited to the table format illustrated in FIG. 6, and may hold the determination criterion according to another appropriate format.

As illustrated in FIG. 6, the consistency analysis unit 104 increases the number of elements that cause a certain event (positive causal relationship) and decreases the number that causes the event. When the resulting elements decrease (positive causal relationship), it is determined that these causal relationships are consistent.

In addition, the consistency analysis unit 104 reduces an element that becomes a cause when a factor causing a certain event increases (negative causal relationship), and an element that becomes a result when the cause decreases. Are increased (negative causal relationship), it is determined that these causal relationships are consistent.

The consistency analysis unit 104 increases the element as a result when a factor causing a certain event increases (positive causal relationship), and increases the element as a result when the cause decreases. If yes (negative causal relationship), it is determined that these causal relationships are not consistent. In addition, the consistency analysis unit 104 reduces an element that becomes a cause when a factor causing a certain event increases (negative causal relationship), and an element that becomes a result when the cause decreases. Are decreased (positive causal relationship), it is determined that these causal relationships are not consistent.

In addition, when the causal element between a causal element and a resulting element is not extracted when the causal element related to a certain event increases or decreases, the consistency analysis unit 104 determines whether the causal relationship between the causal element and the resulting element is not extracted. It is determined that the causal relationship is not consistent.

Fig. 7 shows an example of consistency analysis results. In FIG. 7, the consistency analysis result list 700 includes a column 701 indicating a cause element, a column 702 indicating a result element, a column 703 indicating a sign of a causal relationship when the cause elements increase, A column 704 indicating the sign of the causal relationship when the causal element decreases and a column 705 indicating the consistency analysis result are included. In each of the columns, data expressed in an appropriate format such as a character string, a numerical value, a code, and a symbol is set.

In

columns

703 and 704, in addition to a sign indicating positive or negative, if no causal relationship is extracted from the document accumulated in step S <b> 302, data indicating “not extracted” is stored in

columns

703 and 704. Is set.

For example, the fourth line (700A in FIG. 7) of the consistency analysis result list 700 illustrated in FIG. 7 is an element whose cause indicates “economy of scale” and whose result indicates “product cost”. . In this example, the sign of the causal relationship when the causal element increases is negative, and the sign of the causal relationship when the causal element decreases is also negative. Since the signs of the causal relationship when the causal element increases and the causal relationship when the causal element decreases, the signs match, the consistency analysis unit 104 determines that these causal relationships are consistent. judge. Therefore, data representing “match” is set in the analysis result (705).

Further, for example, the sixth line in FIG. 7 (700B in FIG. 7) is an element whose cause indicates “price” and whose result indicates “brand image”. In this example, the sign of the causal relationship when the causal element increases is unextracted, and the sign of the causal relationship when the causal element decreases is positive. If the causal relationship when the causal elements increase is not extracted from the accumulated document, the consistency analysis unit 104 determines that these causal relationships are not consistent. Therefore, data representing “inconsistency” is set in the analysis result (705).

Finally, in step S304, the result output unit 105 outputs the consistency analysis result by the consistency analysis unit 104.

The result output method by the result output unit 105 may be, for example, a table format as exemplified in FIG. 7, or may be another format. Further, the result output unit 105 may output only a combination of an element representing a cause and an element representing a result, the consistency analysis result of which is “inconsistent”.

As described above, the information processing apparatus 100 according to the present embodiment accepts input of information (causal relationship information) indicating elements constituting an event and a causal relationship between elements. Then, the information processing apparatus 100 extracts a causal relationship between the causal element and the causal element included in the received causal relationship information from the accumulated document. Specifically, the information processing apparatus 100 extracts the causal relationship between the cause element and the result element for each of cases where the cause element increases and decreases. Then, the information processing apparatus 100 analyzes the consistency between the causal relationship when the causal element increases and the causal relationship when the causal element decreases, and outputs the analysis result.

According to the information processing apparatus 100 as described above, the analysis result on the consistency with respect to the change of the resulting element when the factor causing the increase and the decrease is displayed as the user of the information processing apparatus 100 (not shown). ) Can be provided. For example, the user can check whether or not the causal relationship between the element representing the cause and the element representing the result is consistent using the provided analysis result.

For example, in the sixth row of the consistency analysis result list 700 illustrated in FIG. 7 (700B in FIG. 7), the cause that “price” decreases (decreases) and “brand image” decreases (decreases). Relationships are extracted. However, the causal relationship that “the price” goes up (increases) and the “brand image” goes up (increases) has not been extracted. For example, by presenting the analysis result, the information processing apparatus 100 can provide the user with an opportunity to reconsider whether or not the causal relationship is consistent. As a result, the user can pay attention to the causal relationship, and can prevent errors in decision making. As described above, the information processing apparatus 100 according to the present embodiment evaluates the consistency between the causal element and the resulting element when the causal element increases or decreases. Possible information can be provided.

<Modification of First Embodiment>
Next, a modification of the first embodiment will be described. The information processing apparatus in this modification may have the same configuration as that in the first embodiment.

In the present modification, as illustrated in FIG. 4B, the input receiving unit 101 includes a causal element, a resulting element, and information indicating the relationship between these elements (causal relationship code). Accept relationship information.

In the present modification, when the consistency analysis unit 104 determines the consistency of the causal relationship, the consistency analysis unit 104 further refers to information (symbol of the causal relationship) that represents the relationship between the elements included in the causal relationship information.

Specifically, as in the first embodiment, the consistency analysis unit 104 decreases the causal relationship when the causal element extracted by the causal relationship extraction unit 103 increases and the causal element decrease. Analyze the consistency between the cause and effect.

As a result of the analysis, if it is determined that the causal relationship between the causal element and the causal element is not consistent, the information processing apparatus according to the present modification performs the same process as in the first embodiment. do.

As a result of the above analysis, when it is determined that the causal relationship between the cause element and the result element is consistent, the consistency analysis unit 104 may execute the following processing. That is, the consistency analysis unit 104 compares information representing the relationship between elements included in the causal relationship information with the causal relationship extracted by the causal relationship extraction unit 103.

For example, the “element A” that is the cause element, the “element B” that is the result element, and the “positive sign (+)” that is the code representing the causal relationship between them are the causal relation. Assume that the information is set.

When the causal relationship when “element A” increases and the causal relationship when “element A” decreases are extracted from the accumulated document by the causal relationship extraction unit 103, respectively, are positive causal relationships The consistency analysis unit 104 determines that these causal relationships are consistent, and the codes (positive codes) of these causal relationships are the same as the codes (positive codes) set in the causal relationship information. In this case, the consistency analysis unit 104 determines that the causal relationship code extracted from the document matches the causal relationship code given as an input. The result is provided to the result output unit 105.

On the other hand, the causal relationship in the case where “element A” increases and the causal relationship in the case where “element A” decreases are extracted from the accumulated documents by the causal relationship extraction unit 103, respectively. If it is a causal relationship, the consistency analysis unit 104 determines that these causal relationships are consistent, where the codes (negative signs) of these causal relationships are the codes set in the causal relationship information. Although the consistency analysis unit 104 matches the causal relationship extracted from the document, the consistency analysis unit 104 determines that the code of the causal relationship extracted from the document and the code of the causal relationship given as input are the same. The consistency analysis unit 104 provides the determination result to the result output unit 105, for example.

The result output unit 105 gives a warning or the like when, for example, in the determination result provided from the consistency analysis unit 104, the causal relationship code extracted from the document does not match the causal relationship code given as an input. It may be output.

The information processing apparatus according to the present modification configured as described above has a matching between the causal element and the resulting element when the causal element is increased or decreased in the causal relationship. Information that can be evaluated for sex can be provided. Furthermore, the information processing apparatus according to the present modification can provide information indicating whether or not the signs of the causal relationship extracted from the document and the causal relationship given as input (causal relationship information) match. Thereby, the user of the information processing apparatus can confirm the result of analyzing the consistency of the causal relationship between the elements included in the causal relationship information based on the accumulated document. Further, the user of the information processing apparatus can confirm whether or not the signs of the causal relationship between elements included in the causal relationship information and the causal relationship between elements extracted from the document match. The information processing apparatus according to the present modification can provide a user with an opportunity to confirm the causal relationship between elements included in the causal relationship information, for example, when the codes of the causal relationship do not match.

<Second Embodiment>
Next, a second embodiment that is a basic embodiment of the present invention will be described. FIG. 8 is a block diagram illustrating a functional configuration of an information processing apparatus according to the second embodiment of the present invention.

As illustrated in FIG. 8, the information processing apparatus 800 includes a causal relationship extraction unit 801, a document storage unit 802, a consistency analysis unit 803, and a result output unit 804. These components constituting the information processing apparatus 800 are communicably connected using an appropriate communication method.

The document storage unit 802 (document storage unit) holds one or more documents. Such a document is not particularly limited, for example, as in the first embodiment, and may be any document that is expected to describe the elements constituting the event and the causal relationship between the elements. The document storage unit 802 can store the document using, for example, a known file system or a database.

The document storage unit 802 may be configured, for example, in the same manner as the document storage unit 102 in the first embodiment, and may hold a document by the same processing as the document storage unit 102.

The causal relationship extracting unit 801 (causal relationship extracting means) includes a case in which the causal relationship between the element causing the causal relationship regarding the event and the resulting element increases as the causal element. Are extracted from the above document for each of the cases where the number of cases decreases. The causal relationship extraction unit may extract a code representing the causal relationship between the causal element and the resulting element, for example, by analyzing the document.

The causal relationship extraction unit 801 may acquire, for example, an element that causes a cause related to the event and an element that is a result related to the event from causal relationship information including information representing an element constituting the event. Such causal relationship information may be provided from, for example, a user (not shown) of the information processing apparatus 800 or another information processing apparatus. The causal relationship extraction unit 801 may acquire the causal relationship information held in a storage device (not shown) in the information processing apparatus 800, for example.

The causal relationship extraction unit 801 may be configured in the same manner as the causal relationship extraction unit 103 in each of the above embodiments, for example, and may execute the same processing as the causal relationship extraction unit 103.

The consistency analysis unit 803 (consistency analysis means) extracts the causal relationship when the causal element increases and the causal relationship when the causal element decreases, extracted by the causal relationship extraction unit. Analyze consistency. The consistency analysis unit 803 includes, for example, a cause-and-effect relationship indicating increase / decrease in the resulting element when the cause element increases, and a cause / effect indicating increase / decrease in the result element when the cause element decreases. The consistency may be analyzed by comparing the relationship. At this time, the consistency analysis unit 803, for example, for the causal relationship when the causal element increases and the causal relationship when the causal element decreases, between the causal element and the causal element You may compare the code | symbol showing the causal relationship between.

The consistency analysis unit 803 may be configured in the same manner as the consistency analysis unit 104 in each of the above embodiments, for example, and may execute the same processing as the consistency analysis unit 104.

The result output unit 804 (result output means) outputs the result of the analysis by the consistency analysis unit 803. The result output unit 804 may output the output information to a display device (not shown), for example, similarly to the result output unit 105 in the first embodiment, and outputs the calculation result in the form of a file or the like. May be. The method by which the result output unit 804 outputs the calculation result is not limited to the above, and an appropriate method may be selected.

The result output unit 804 may be configured, for example, in the same manner as the result output unit 105 in the first embodiment, and may output the output information by the same processing as the result output unit 105.

As described above, the information processing apparatus 800 according to this embodiment extracts the causal relationship between the causal element and the causal element included in the causal relation information from the accumulated document. Specifically, the information processing apparatus 800 extracts the causal relationship between the cause element and the result element for each of cases where the cause element increases and decreases. Then, the information processing apparatus 800 analyzes the consistency between the causal relationship when the causal element increases and the causal relationship when the causal element decreases, and outputs the analysis result.

According to the information processing apparatus 800 as described above, the analysis result regarding the consistency regarding the change in the resulting element when the factor causing the increase and the decrease is displayed as the user of the information processing apparatus 800 (not shown). ) Can be provided. For example, the user can check whether or not the causal relationship between the element representing the cause and the element representing the result is consistent using the provided analysis result. As described above, the information processing apparatus 800 according to the present embodiment evaluates the consistency between the causal element and the resulting element when the causal element in the causal relationship increases and decreases. Possible information can be provided.

<Configuration of hardware and software program (computer program)>
Hereinafter, a hardware configuration capable of realizing each of the above-described embodiments will be described.

In the following description, the information processing apparatuses (100, 800) described in the above embodiments are collectively referred to simply as “information processing apparatus”. Each component of the information processing apparatus may be simply referred to as “component of the information processing apparatus”.

The information processing apparatus described in each of the above embodiments may be configured by one or a plurality of dedicated hardware devices. In that case, each component shown in each of the above drawings (FIGS. 2 and 8) is realized by using a hardware (an integrated circuit or a storage device on which processing logic is mounted) that is partially or fully integrated. Also good.

When the information processing apparatus is realized by dedicated hardware, the components of the information processing apparatus may be realized by, for example, a circuit configuration capable of providing each function. Such a circuit configuration includes, for example, an integrated circuit such as SoC (System on a Chip), a chip set realized using the integrated circuit, and the like. In this case, the data held by the components of the information processing apparatus is, for example, a RAM (Random Access Memory) area integrated as SoC, a flash memory area, or a storage device (such as a semiconductor storage device) connected to the SoC. May be stored. The data includes, for example, the causal relationship extracted by the causal relationship extraction unit (103, 801), the analysis result by the consistency analysis unit (104, 803), or the document stored in the document storage unit (102, 802). Etc. may be included. In addition, the data may include processing data generated by the components of the information processing apparatus during the processing. In this case, a known communication network (for example, a communication bus) may be employed as a communication line that connects each component of the information processing apparatus. Further, the communication line connecting each component may be connected between each component by peer-to-peer.

Further, the information processing apparatus described above may be configured by general-purpose hardware exemplified in FIG. 9 and various software programs (computer programs) executed by the hardware. In this case, the information processing apparatus may be configured by an arbitrary number of general-purpose hardware devices and software programs. That is, an individual hardware device may be assigned to each component configuring the information processing apparatus, and a plurality of components may be realized using a single hardware device.

The arithmetic device 901 in FIG. 9 is an arithmetic processing device such as a general-purpose CPU (Central Processing Unit) or a microprocessor. The arithmetic device 901 may read various software programs stored in a nonvolatile storage device 903, which will be described later, into the storage device 902, and execute processing according to the software programs. In this case, the function of the component of the information processing apparatus in each of the above embodiments is realized using a software program executed by the arithmetic device 901.

The storage device 902 is a memory device such as a RAM or a ROM that can be referred to from the arithmetic device 901, and stores software programs, various data, and the like. Note that the storage device 902 may be a volatile memory device or a nonvolatile memory device.

The data held by the components of the information processing apparatus may be temporarily stored in the storage device 902. The data includes, for example, the causal relationship information received by the input receiving unit 101, the causal relationship extracted by the causal relationship extracting unit (103, 801), the analysis result by the consistency analyzing unit (104, 803), or the document accumulation Documents read from the sections (102, 802) may be included. In addition, the data may include processing data generated by the components of the information processing apparatus during the processing.

The nonvolatile storage device 903 is a nonvolatile storage device such as a magnetic disk drive or a semiconductor storage device using a flash memory. The nonvolatile storage device 903 can store various software programs, data, and the like. For example, various documents stored in the document storage unit (102, 802) may be stored in the nonvolatile storage device 903.

The network interface 906 is an interface device that is connected to a communication network. For example, a wired or wireless LAN connection interface device may be employed.

The drive device 904 is, for example, a device that processes reading and writing of data with respect to a recording medium 905 described later.

The recording medium 905 is an arbitrary recording medium capable of recording data, such as an optical disk, a magneto-optical disk, and a semiconductor flash memory.

The input / output interface 907 is a device that controls input / output with an external device. For example, the input receiving unit 101 may receive input of causal relationship information from an input device (such as a keyboard) connected via the input / output interface 907. In addition, the result output unit (105, 804) may output the calculation result of the causal relationship or the determination result of the consistency to the display device connected via the input / output interface 907.

The information processing apparatus according to the present invention described with the above-described embodiments as an example, or a component thereof, for example, software capable of realizing the functions described in the above-described embodiments with respect to the hardware apparatus illustrated in FIG. -It may be realized by supplying a program. More specifically, for example, the present invention may be realized by causing the arithmetic device 901 to execute a software program supplied to the hardware device. In this case, an operating system running on the hardware device, database management software, network software, middleware such as a virtual environment platform, etc. may execute part of each process.

In each of the above-described embodiments, each unit illustrated in each drawing can be realized as a software module, which is a function (processing) unit of a software program executed by the above-described hardware. However, the division of each software module shown in these drawings is a configuration for convenience of explanation, and various configurations can be assumed for implementation.

For example, when each component of the information processing apparatus illustrated in FIGS. 2 and 8 is realized as a software module, these software modules are stored in the nonvolatile storage device 903. Then, when the arithmetic device 901 executes each process, these software modules are read out to the storage device 902.

Further, these software modules may be configured to transmit various data to each other by an appropriate method such as shared memory or inter-process communication. With such a configuration, these software modules are connected so as to communicate with each other.

Further, the software program may be recorded on the recording medium 905. In this case, the software program may be configured to be stored in the nonvolatile storage device 903 through the drive device 904 as appropriate at the shipment stage or operation stage of the components of the information processing apparatus.

In the above case, the method of supplying various software programs to the hardware is installed in the apparatus using an appropriate jig in the manufacturing stage before shipment or the maintenance stage after shipment. A method may be adopted. As a method for supplying various software programs, a general procedure may be adopted at present, such as a method of downloading from the outside via a communication line such as the Internet.

In such a case, the present invention can be understood to be constituted by a code constituting the software program or a computer-readable recording medium on which the code is recorded. In this case, the recording medium is not limited to a medium independent of the hardware device, but includes a recording medium in which a software program transmitted via a LAN or the Internet is downloaded and stored or temporarily stored.

Further, the components of the information processing apparatus described above are configured by a virtualized environment in which the hardware device illustrated in FIG. 9 is virtualized and various software programs (computer programs) executed in the virtualized environment. May be. In this case, the components of the hardware device illustrated in FIG. 9 are provided as virtual devices in the virtual environment. In this case as well, the present invention can be realized with the same configuration as when the hardware device illustrated in FIG. 9 is configured as a physical device.

The present invention has been described above as an example applied to the exemplary embodiment described above. However, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications and improvements can be made to such embodiments. In such a case, new embodiments to which such changes or improvements are added can also be included in the technical scope of the present invention. Furthermore, the embodiments described above, or embodiments obtained by combining new embodiments with such changes or improvements may be included in the technical scope of the present invention. This is clear from the matters described in the claims.

This application claims priority based on Japanese Patent Application No. 2015-243102 filed on Dec. 14, 2015, the entire disclosure of which is incorporated herein.

DESCRIPTION OF SYMBOLS 100 Information processing apparatus 101 Input reception part 102 Document storage part 103 Causal relation extraction part 104 Consistency analysis part 105 Result output part 800 Information processing apparatus 801 Causal relation extraction part 802 Document storage part 803 Consistency analysis part 804 Result output part 901 Calculation Device 902 Storage device 903 Non-volatile storage device 904 Drive device 905 Recording medium 906 Network interface 907 Input / output interface

Claims

Document storage means capable of holding one or more documents;
The causal relationship between the causal element and the causal element of the causal relationship relating to the event from the document when the causal element increases and when the causal element decreases Causal relationship extraction means to extract;
Consistency analysis means for analyzing consistency between the causal relation when the causal element is extracted and the causal relation when the causal element is reduced, extracted by the causal relation extraction means;
A result output means for outputting a result analyzed by the consistency analysis means;
An information processing apparatus comprising:
The consistency analysis unit is configured so that the causal relationship between the causal element extracted from the document by the causal relationship extracting unit and the causal relationship between the element and the resulting element is the causal element. A causal relationship in the case where the causal element increases, and a causal case in which the causal element decreases, based on whether or not the causal element increases and whether the causal element decreases The information processing apparatus according to claim 1, wherein consistency between relationships is determined.
The consistency analysis means has a causal relationship between the causal element extracted from the document by the causal relation extraction means and the resulting element.
Represents a causal relationship in which the resulting element increases when the causal element increases and the resulting element decreases when the causal element decreases, or
If the causal relationship represents a causal relationship in which the resulting element decreases when the causal element increases and the resulting element increases when the causal element decreases, the causal relationship is consistent The information processing apparatus according to claim 1, wherein the information processing apparatus determines that the information is being performed.
The consistency analysis means has a causal relationship between the causal element extracted from the document by the causal relation extraction means and the resulting element.
Represents a causal relationship in which the resulting element increases when the causal element increases and the resulting element increases when the causal element decreases, or
If the causal relationship represents a causal relationship in which the resulting element decreases when the causal element increases, and the resulting element decreases when the causal element decreases, the causal relationship is consistent The information processing apparatus according to claim 1, wherein the information processing apparatus determines that it has not been performed.
The consistency analysis means includes the element that causes the element and the element that results in at least one of the case where the cause element increases and the cause element decreases. The information processing apparatus according to any one of claims 1 to 4, wherein when the causal relationship between the two is not extracted from the document, the causal relationship is determined not to be consistent.
The causal relationship extraction unit analyzes the document, and causes the element and the result to be the cause for each of the case where the element causing the increase and the element causing the cause decrease. A code representing a causal relationship between the elements to be provided, and providing a code representing the causal relationship to the consistency analysis means,
In the case where the factor causing the cause increases, the consistency analysis unit includes a sign indicating a causal relationship between the factor causing the factor and the factor causing the result, and the factor causing the factor decreases. 6. The method according to claim 1, wherein when the causal element and the sign representing the causal relation between the element and the result coincide with each other, it is determined that the causal relation is consistent. The information processing apparatus according to any one of the above.
An input receiving means for receiving causal relationship information in which the element that causes the event, the resulting element, and a code representing the causal relationship between them are set;
The consistency analysis unit includes a code extracted from the document by the causal relationship extraction unit with respect to the causal relationship between the cause element and the resulting element, and the input reception unit receives the code. The result of determining whether or not the code included in the causal relationship information matches is output to the result output means,
The information processing apparatus according to claim 6, wherein the result output unit outputs a result of determination by the consistency analysis unit.
The causal relationship between the causal element of the causal relationship regarding the event and the resulting element is greater than or equal to one when the causal element increases and when the causal element decreases Extracted from documents
Analyzing the consistency between the extracted causal relationship when the causal element increases and the causal relationship when the causal element decreases;
Output the result of the analysis,
Information processing method.
Processing to hold one or more documents;
The document for each of a case where the causal relationship between the element causing the causal relationship regarding the event and the resulting element is increased and the factor causing the causal relationship are decreased. Processing to extract from
A process of analyzing consistency between the extracted causal relationship when the causal element increases and the causal relationship when the causal element decreases;
A recording medium on which a computer program for causing a computer to execute processing for outputting the analysis result is recorded.