Information processing device, information processing method, and program

Abstract

To provide a technology for proposing food materials suitable for a food product with a content as a motif on the basis of information related to the content.SOLUTION: An information processing device includes content information acquisition means for acquiring content information showing a content, content emotion information generation means for generating content emotion information showing emotions related to the content with reference to the content information, and food material information output means for outputting food material information showing one or more food materials related to emotions correlating with emotions shown by the content emotion information among a food material group with reference to food emotion information showing emotions related to each of food materials in the food material group, and the content emotion information.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and a program.

Background Art

[0002] An information processing technology for proposing food ingredients based on some information is known. As an example of the technology for proposing food ingredients, there is an information processing apparatus (Patent Document 1, etc.) that provides information on appropriate food ingredients based on the ingredients that a user desires to ingest according to a recipe.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Foods themed on contents (works) such as movies, dramas, and comics are products with high demand that remind consumers of the content, and various foods have been developed so far. However, conventionally, the development of such foods has strongly depended on the imagination of developers. In particular, the selection of food ingredients has had a great impact on important factors such as the taste and appearance of the food, and thus has been a labor-intensive and time-consuming task for developers. Therefore, a technology that technically links contents and food ingredients to assist developers in selecting food ingredients is required.

[0005] The present disclosure has been made in view of the above problems, and an exemplary object thereof is to provide a technology for proposing food ingredients suitable for foods themed on a content based on information related to the content.

Means for Solving the Problems

[0006] An information processing apparatus according to an exemplary aspect of the present disclosure includes: content information acquisition means for acquiring content information indicating content; content emotion information generation means for generating content emotion information indicating an emotion related to the content by referring to the content information; and food material information output means for outputting food material emotion information indicating an emotion related to each food material in a group of food materials and food material information indicating one or more food materials related to an emotion correlated with the emotion indicated by the content emotion information among the group of food materials, with reference to the food material emotion information and the content emotion information.

[0007] An information processing method according to an exemplary aspect of the present disclosure includes: acquiring content information indicating content; generating content emotion information indicating an emotion related to the content by referring to the content information; and outputting food material emotion information indicating an emotion related to each food material in a group of food materials and food material information indicating one or more food materials related to an emotion correlated with the emotion indicated by the content emotion information among the group of food materials, with reference to the food material emotion information and the content emotion information.

[0008] A program according to an exemplary aspect of the present disclosure causes a computer to execute: a content information acquisition process for acquiring content information indicating content; a content emotion information generation process for generating content emotion information indicating an emotion related to the content by referring to the content information; and a food material information output process for outputting food material emotion information indicating an emotion related to each food material in a group of food materials and food material information indicating one or more food materials related to an emotion correlated with the emotion indicated by the content emotion information among the group of food materials, with reference to the food material emotion information and the content emotion information.

Effect of the Invention

[0009] According to an exemplary aspect of the present disclosure, there is an exemplary effect that a technique for proposing food materials suitable for food having the content as a motif can be provided based on information related to the content.

Brief Description of the Drawings

[0010]

Figure 1

Figure 2

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Figure 7

Embodiments for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present invention will be exemplified. However, the present invention is not limited to the following exemplary embodiments, and various modifications are possible within the scope shown in the claims. For example, embodiments obtained by appropriately combining the technical means employed in the following exemplary embodiments may also be included in the scope of the present invention. Also, embodiments obtained by appropriately omitting a part of the technical means employed in the following exemplary embodiments may also be included in the scope of the present invention. Further, the effects mentioned in the following exemplary embodiments are examples of the effects expected in those exemplary embodiments, and do not define the extension of the present invention. That is, embodiments that do not exhibit the effects mentioned in the following exemplary embodiments may also be included in the scope of the present invention.

[0012] 〔The First Exemplary Embodiment〕 A first exemplary embodiment, which is an example of an embodiment of the present invention, will be described in detail with reference to the drawings. This exemplary embodiment is a basic form of each of the exemplary embodiments described below. Note that the scope of application of each technical means employed in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technical means employed in this exemplary embodiment can be employed in other exemplary embodiments included in the present disclosure as long as there is no particular technical obstacle. In addition, each technical means shown in the drawings referred to for explaining this exemplary embodiment can also be employed in other exemplary embodiments included in the present disclosure as long as there is no particular technical obstacle.

[0013] (Configuration of Information Processing Apparatus 1) The configuration of the information processing apparatus 1 according to this exemplary embodiment will be described with reference to FIG. 1. FIG. 1 is a block diagram showing the configuration of the information processing apparatus 1. As shown in FIG. 1, the information processing apparatus 1 includes a content information acquisition unit 11, a content emotion information generation unit 12, and a food ingredient information output unit 13.

[0014] (Content Information Acquisition Unit 11) The content information acquisition unit 11 acquires content information indicating the content. Here, the content is, for example, video content, text content, image content, audio content, or a part of any of these contents. The video content is, for example, a movie, or a TV program such as a drama program or a documentary program. The text content is, for example, a novel or an essay. The image content is, for example, an illustration, a photograph, or a comic such as a combination of an illustration and text. The audio content is, for example, a music piece. The content may be either the whole or a part of a work, and may be, for example, one scene of a movie.

[0015] Content information indicating content is, for example, video data, audio data, text data, or image data included in the content, or data obtained by converting any of these data into another format. Specific examples of content information are not intended to limit this exemplary embodiment, but as an example, · Text data indicating the conversation content between characters in a scene that constitutes a drama program, which is video content · Image data showing the dialogue and illustrations of characters that make up a comic, which is image content, over a plurality of pages may be cited.

[0016] (Content Emotion Information Generation Unit 12) The content emotion information generation unit 12 generates content emotion information indicating emotions related to the content by referring to the content information. As an example, the content emotion information generation unit 12 · refers to the content information, · Based on the content information and a predetermined algorithm, generates table data in which one or more types of predetermined emotions and the intensity of emotions presumed to be held by the user to whom the content is provided are associated for each type of emotion, as the content emotion information. Such a configuration can be adopted. Here, examples of types of emotions include joy, sadness, fear, love, anger, acceptance, anxiety, trance, sorrow, regret, contempt, irritation, optimism, etc. In the content emotion information, the type of emotion may be indicated, for example, by the name of the type of emotion or an attribute label corresponding thereto. Also, in the content emotion information, the intensity of the emotion may be indicated, for example, by a numerical value or rank indicating the intensity of the emotion.

[0017] Here, when text data is referred to as the content information, the predetermined algorithm is, for example, · determines for each type of emotion whether each of one or more phrases pre-associated with the emotion is included in the referred text data, ·Generate the number of phrases included in the text data as a numerical value indicating the strength of the type of emotion associated with the phrase. The following configuration can be adopted.

[0018] Also, as an example, the predetermined algorithm may be a machine learning model that has been machine-learned to input content information that is any one of video data, audio data, text data, or image data and generate content emotion information indicating the emotion associated with the content.

[0019] (Food ingredient information output unit 13) The food ingredient information output unit 13 refers to the food ingredient emotion information indicating the emotion associated with each food ingredient in the food ingredient group and the content emotion information, and outputs food ingredient information indicating one or more food ingredients in the food ingredient group that are associated with the emotion correlated with the emotion indicated by the content emotion information.

[0020] Here, the food ingredient group is, for example, a group including a plurality of predetermined types of food ingredients. The food ingredient emotion information is, for example, table data in which one or more types of emotions included in the content emotion information and the strength of the emotion estimated to be associated by the food ingredients included in the food ingredient group with the user are associated for each type of food ingredient.

[0021] The food ingredient information output unit 13, as an example, ·Refers to the food ingredient emotion information and the content emotion information. ·For each type of food ingredient included in the food ingredient emotion information, determines the degree of correlation between the food ingredient emotion information and the content emotion information regarding the type and strength of the emotion. ·Generates data indicating the type of food ingredient for which the determined degree of correlation is equal to or greater than a predetermined threshold as food ingredient information. ·Outputs the generated food ingredient information. The following configuration can be adopted. When such a configuration is adopted, a developer of a food that uses the food ingredient information can efficiently select food ingredients by considering the food ingredients indicated by the food ingredient information as food ingredients for a food with the content as a motif.

[0022] As another example, the food ingredient information output unit 13 · refers to the food ingredient emotion information and the content emotion information, · for each type of food ingredient included in the food ingredient emotion information, determines the degree of correlation between the food ingredient emotion information and the content emotion information regarding the type and intensity of the emotion, · generates data indicating the degree of correlation determined for each of all types of food ingredients included in the food ingredient group as food ingredient information, · outputs the generated food ingredient information. Such a configuration can also be adopted. When such a configuration is adopted, a developer of a food that uses the food ingredient information can efficiently select food ingredients by considering the food ingredients included in the food ingredient group as food ingredients for a food with the content as a motif in descending order of the degree of correlation.

[0023] (Effect of the information processing apparatus 1) As described above, in the information processing apparatus 1, · acquires content information indicating the content, · refers to the content information and generates content emotion information indicating the emotion related to the content, · refers to the food ingredient emotion information indicating the emotion related to each food ingredient in the food ingredient group and the content emotion information, and outputs food ingredient information indicating one or more food ingredients in the food ingredient group that are related to the emotion correlated with the emotion indicated by the content emotion information. Such a configuration is adopted. Therefore, the information processing apparatus 1 configured as described above outputs food ingredient information indicating food ingredients related to the emotion correlated with the emotion related to the content by referring to the content information indicating the content. Since the food ingredients indicated by the output food ingredient information are related to the emotion correlated with the emotion related to the content, they are suitable as materials for a food with the content as a motif. Therefore, according to the above configuration, a technique can be provided for proposing food ingredients suitable for a food with the content as a motif based on information regarding the content.

[0024] (Flow of Information Processing Method S1) Subsequently, the flow of the information processing method S1 according to this exemplary embodiment will be described with reference to FIG. 2. FIG. 2 is a flowchart showing the flow of the information processing method S1. As shown in FIG. 2, the information processing method S1 includes a step (process) S11 of acquiring content information, a step (process) S12 of generating content emotion information, and a step (process) S13 of outputting food ingredient information.

[0025] (Step S11) In step S11, the content information acquisition unit 11 acquires content information indicating the content. Since the specific processing by the content information acquisition unit 11 has been described above, the description is omitted here.

[0026] (Step S12) In step S12, the content emotion information generation unit 12 generates content emotion information indicating an emotion related to the content with reference to the content information. Since the specific processing by the content emotion information generation unit 12 has been described above, the description is omitted here.

[0027] (Step S13) In step S13, the food ingredient information output unit 13 outputs food ingredient information indicating one or more food ingredients related to an emotion correlated with the emotion indicated by the content emotion information among the food ingredient group, with reference to the food ingredient emotion information indicating the emotion related to each food ingredient in the food ingredient group and the content emotion information. Since the specific processing by the food ingredient information output unit 13 has been described above, the description is omitted here.

[0028] (Effect of Information Processing Method S1) As described above, in the information processing method S1, · acquire content information indicating the content, · generate content emotion information indicating an emotion related to the content with reference to the content information, ·Referring to the food ingredient emotion information indicating the emotion associated with each food ingredient in the food ingredient group and the content emotion information, output food ingredient information indicating one or more food ingredients associated with the emotion correlated with the emotion indicated by the content emotion information among the food ingredient group. The configuration as described above is adopted. Therefore, according to the information processing method S1 configured as above, referring to the content information indicating the content, output the food ingredient information indicating the food ingredients associated with the emotion correlated with the emotion associated with the content. Since the food ingredients indicated by the output food ingredient information are associated with the emotion correlated with the emotion associated with the content, they are suitable as the materials for the food with the content as the motif. Therefore, according to the above configuration, a technique for proposing food ingredients suitable for the food with the content as the motif based on the information related to the content can be provided.

[0029] 〔Second Exemplary Embodiment〕 A second exemplary embodiment, which is an example of the embodiment of the present invention, will be described in detail with reference to the drawings. For the components having the same functions as the components described in the above-described exemplary embodiment, the same reference numerals are given, and the description thereof will be omitted as appropriate. Note that the application range of each technical means adopted in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technical means adopted in this exemplary embodiment can be adopted in other exemplary embodiments included in the present disclosure as long as there is no particular technical obstacle. In addition, each technical means shown in each drawing referred to for explaining this exemplary embodiment can be adopted in other exemplary embodiments included in the present disclosure as long as there is no particular technical obstacle.

[0030] (Configuration of Information Processing Apparatus 1A) The configuration of the information processing apparatus 1A according to this exemplary embodiment will be described with reference to FIG. 3. FIG. 3 is a block diagram showing the configuration of the information processing apparatus 1A. As shown in FIG. 3, the information processing apparatus 1A includes a control unit 10A, a storage unit 20A, a communication unit 30A, and an input / output unit 40A.

[0031] (Communication Unit 30A) The communication unit 30A communicates with devices external to the information processing device 1A via a network. As an example, the communication unit 30A transmits data supplied from the control unit 10A to an external device, or supplies data received from an external device to the control unit 10A. Note that the specific configuration of the network does not limit this exemplary embodiment, but as an example, a wireless LAN (Local Area Network), a wired LAN, a WAN (Wide Area Network), a public switched telephone network, a mobile data communication network, or a combination of these networks can be used.

[0032] (Input / Output Unit 40A) The input / output unit 40A is configured to include at least one of input / output devices such as a keyboard, a mouse, a display, a printer, and a touch panel. Alternatively, input / output devices such as a keyboard, a mouse, a display, a printer, and a touch panel may be connected to the input / output unit 40A. In this case, the input / output unit 40A receives input of various types of information to the information processing device 1A from the connected input devices. Also, the input / output unit 40A outputs various types of information to the connected output devices under the control of the control unit 10A. Examples of the input / output unit 40A include interfaces such as USB (Universal Serial Bus).

[0033] (Storage Unit 20A) The storage unit 20A stores various types of data referred to by the control unit 10A and various types of data generated by the control unit 10A. As an example, the storage unit 20A stores · Content Information CI · Analysis Target Information AOI · Content Emotion Information CEI · Foodstuff Emotion Information FSEI · Foodstuff Information FSI · Learned Model LM · Correlation Analysis Model AM · Food Database FDB Here, the content information CI is data acquired by the content information acquisition unit 21 described later. Specific examples of the content information CI will be described later. The analysis target information AOI is data acquired by the analysis target information acquisition unit 23 described later. Specific examples of the analysis target information AOI will be described later.

[0034] The content sentiment information CEI is data generated by the content sentiment information generation unit 22 described later. Specific examples of the content sentiment information CEI will be described later. The food sentiment information FSEI is data generated by the food sentiment information generation unit 24 described later. Specific examples of the food sentiment information FSEI will be described later. The food information FSI is data generated by the food information output unit 25 described later. Specific examples of the food information FSI will be described later.

[0035] The learned model LM is a machine learning model that has been machine-learned in advance and is a scoring model referred to by the content sentiment information generation unit 22 and the food sentiment information generation unit 24 described later. Various programs and parameters constituting the learned model LM are stored in the storage unit 20A. Specific examples of the learned model LM will be described later.

[0036] The correlation analysis model AM is an analysis model referred to by the food information output unit 25 described later. Various programs and parameters constituting the correlation analysis model AM are stored in the storage unit 20A. Specific examples of the correlation analysis model AM will be described later.

[0037] The food database FDB is a database referred to by the food information output unit 27 described later. Specific examples of the food database FDB will be described later.

[0038] (Control Unit 10A) As shown in FIG. 3, the control unit 10A includes a content information acquisition unit 21, a content sentiment information generation unit 22, an analysis target information acquisition unit 23, a food sentiment information generation unit 24, a food information output unit 25, a text information output unit 26, and a food information output unit 27.

[0039] (Content information acquisition unit 21) The content information acquisition unit 21 acquires content information CI indicating the content. Here, the content is, as an example, video content, text content, image content, audio content, or a part of any of these contents. The video content is, as an example, a movie, or a TV program such as a drama program or a documentary program. The text content is, as an example, a novel or an essay. The image content is, as an example, an illustration, a photograph, or a comic including a combination of an illustration and text. The audio content is, as an example, a music piece. The content may be either the whole or a part of a work, and may be, as an example, one scene of a movie.

[0040] The content information CI indicating the content is, as an example, video data, audio data, text data, or image data included in the content, or data obtained by converting any of these data into another format. Specific examples of the content information CI are not intended to limit this exemplary embodiment, but as an example, · Text data indicating the conversation content between characters in one scene constituting a drama program which is video content · Image data showing the dialogue and illustrations of characters constituting a comic which is image content over a plurality of pages may be mentioned.

[0041] The content information CI acquired by the content information acquisition unit 21 is stored, as an example, in the storage unit 20A and referred to by the content emotion information generation unit 22 and the like.

[0042] (Content emotion information generation unit 22) The content emotion information generation unit 22 refers to the content information CI and generates content emotion information CEI indicating the emotion related to the content. As an example, the content emotion information generation unit 22 · refers to the content information CI, · Input the content information CI into the learned model LM to generate content emotion information CEI. The following configuration can be adopted. Here, the generated content emotion information CEI is, for example, information in which the type of emotion related to the content and the intensity of the emotion are associated. Here, the content emotion information CEI can adopt a configuration in which the type of emotion is predetermined to be one or more types, and the intensity of the emotion is associated with each type of emotion. Here, examples of the type of emotion include joy, sadness, fear, love, anger, acceptance, anxiety, trance, sadness, regret, contempt, irritation, optimism, etc. In the content emotion information CEI, the type of emotion may be indicated, for example, by the name of the type of emotion or the corresponding attribute label. Also, in the content emotion information CEI, the intensity of the emotion may be indicated, for example, by a numerical value or rank indicating the intensity of the emotion.

[0043] Here, the learned model LM may be a machine learning model that has been machine-learned to input content information CI, which is, for example, any of video data, audio data, text data, or image data, and generate content emotion information CEI indicating the emotion related to the content. The learned model LM is not limited to this exemplary embodiment, but, for example, · Uses text data, which is the content information CI, as input, · Extracts phrases with a high correlation with any type of emotion from the input text data, · Based on the extracted phrases and the feature amounts predetermined for the phrases, determines a numerical value indicating the intensity of the above type of emotion, · Generates table data in which the type of emotion and the numerical value determined for each type of emotion are associated as the content emotion information CEI. The following configuration can be adopted.

[0044] The analysis target information AOI generated by the content emotion information generation unit 22 is stored, for example, in the storage unit 20A and referred to by the food ingredient information output unit 25, the text information output unit 26, etc.

[0045] (Analysis target information acquisition unit 23) The analysis target information acquisition unit 23 acquires analysis target information AOI indicating food ingredients and the emotions associated with the food ingredients. Here, the analysis target information AOI is, as an example, information indicating content, and is information including information indicating food ingredients in a part thereof. Here, as an example, for the content, data of the same type as that described for the content information CI can be adopted, and the description thereof will not be repeated. Specific examples of the analysis target information AOI are not intended to limit this exemplary embodiment, but as an example, · Audio data indicating a music piece · Text data indicating the lyrics of a music piece · Image data indicating a comic can be cited.

[0046] The analysis target information AOI acquired by the analysis target information acquisition unit 23 is stored, as an example, in the storage unit 20A and referred to by the food ingredient emotion information generation unit 24 and the like.

[0047] (Food ingredient emotion information generation unit 24) The food ingredient emotion information generation unit 24 inputs the analysis target information AOI indicating food ingredients and the emotions associated with the food ingredients into the learned model LM, and generates food ingredient emotion information FSEI indicating the emotions associated with the food ingredients. As an example, the food ingredient emotion information generation unit 24 · refers to the content information CI, · inputs the analysis target information AOI into the learned model LM, and generates food ingredient emotion information FSEI, can adopt such a configuration.

[0048] Here, the learned model LM may be a machine-learned model that is machine-learned to input the analysis target information AOI, which is any one of video data, audio data, text data, or image data as an example, and generate food ingredient emotion information FSEI indicating the emotions associated with the food ingredients. The learned model LM is not intended to limit this exemplary embodiment, but as an example, · uses, as an input, the text data indicating the lyrics of a music piece, which is the analysis target information AOI, ·Extract, from the input text data, a first phrase indicating the name of a food ingredient and a second phrase proximate to the first phrase, the second phrase having a high correlation with any type of sentiment. ·Based on the second phrase and a predefined feature amount for the second phrase, determine a numerical value indicating the strength of the above type of sentiment. ·Generate table data in which a food ingredient group including a plurality of types of food ingredients each corresponding to the first phrase, the type of sentiment, and the numerical value determined for each type of sentiment are associated, as food ingredient sentiment information FSEI. A configuration such as this can be adopted. Although not limiting the present exemplary embodiment, as an example, the set of types of sentiment included in the food ingredient sentiment information FSEI and the set of types of sentiment included in the content sentiment information CEI may be the same as each other.

[0049] The generated food ingredient sentiment information FSEI is, as an example, information indicating the sentiment associated with each of the food ingredients in the food ingredient group. Also, as an example, the food ingredient sentiment information FSEI may be information in which the type of sentiment associated with the food ingredient and the strength of the sentiment are associated. The generated food ingredient sentiment information FSEI may adopt a configuration in which the above type of sentiment is predefined by a learning model LM for one or a plurality of types, and the strength of the sentiment is associated for each food ingredient and for each type of sentiment. Here, in the food ingredient sentiment information FSEI, the type of sentiment may be indicated, as an example, by the name of the type of sentiment or an attribute label corresponding thereto. Also, in the food ingredient sentiment information FSEI, the strength of the sentiment may be indicated, as an example, by a numerical value or rank indicating the strength of the sentiment.

[0050] The food ingredient group is, as an example, a set of one or a plurality of types of food ingredients indicated by the analysis target information AOI. Although not limiting the present exemplary embodiment, as an example, when the analysis target information AOI is text data including the names of two types of food ingredients, "apple" and "lemon", the food ingredient group may be a set of apple and lemon.

[0051] The food ingredient emotion information FSEI generated by the food ingredient emotion information generation unit 24 is stored in the storage unit 20A as an example and referred to by the food ingredient information output unit 25 and the like.

[0052] (Food ingredient information output unit 25) The food ingredient information output unit 25 refers to the food ingredient emotion information FSEI indicating the emotion associated with each food ingredient in the food ingredient group and the content emotion information CEI, and outputs food ingredient information FSI indicating one or more food ingredients associated with the emotion correlated with the emotion indicated by the content emotion information CEI among the food ingredient group. Here, the food ingredient information output unit 25 may adopt a configuration that outputs the food ingredient information FSI based on the correlation between the type and intensity of the emotion indicated by the content emotion information CEI and the type and intensity of the emotion indicated by the food ingredient emotion information FSEI.

[0053] The food ingredient information output unit 25, as an example, · Refers to the food ingredient emotion information FSEI and the content emotion information CEI, ·Inputs the food ingredient emotion information FSEI and the content emotion information CEI into the correlation analysis model AM to generate the food ingredient information FSI, · Outputs the generated food ingredient information FSI to the input / output unit 40A, and can adopt such a configuration. An example of the processing by the food ingredient information output unit 25 using the correlation analysis model AM will be described later by changing the reference drawing.

[0054] The food ingredient information FSI output or generated by the food ingredient information output unit 25 is stored in the storage unit 20A as an example and referred to by the text information output unit 26, the food information output unit 27, and the like.

[0055] (Text information output unit 26) The text information output unit 26 refers to the content emotion information CEI and the food ingredient information FSI, and outputs text information TI indicating text in which the emotion indicated by the content emotion information CEI and the food ingredient indicated by the food ingredient information FSI are associated. Here, as an example, the output text information TI may be information that causes a user provided with the text indicated by the text information TI to associate the emotion indicated by the content emotion information CEI and the food ingredient indicated by the FSI.

[0056] Here, as an example, the text information output unit 26 · selects the strongest emotion among one or more types of emotions indicated by the referenced content emotion information CEI, · generates a phrase associated with the selected emotion, · generates a phrase associated with the food ingredient indicated by the referenced food ingredient information FSI, · generates text data indicating text including the generated phrase associated with the emotion and the phrase associated with the food ingredient as the text information TI, · outputs the generated text information TI to the input / output unit 40A, and can adopt the following configuration.

[0057] Note that, as an example, the text information output unit 26 can adopt a configuration in which, in addition to the content emotion information CEI, it refers to the content information CI. When this configuration is adopted, the text information output unit 26 may be configured to output text information TI indicating text in which the content indicated by the content information CI, the emotion indicated by the content emotion information CEI, and the food ingredient indicated by the food ingredient information FSI are associated. In this case, as an example, the output text information TI may be information that causes a user provided with the text indicated by the text information TI to associate the content indicated by the content information CI, the emotion indicated by the content emotion information CEI, and the food ingredient indicated by the FSI.

[0058] Note that, as an example, the text information output unit 26 may adopt a configuration that refers to the content information CI instead of the content emotion information CEI. When this configuration is adopted, the text information output unit 26 may, as an example, be configured to output text information TI indicating text in which the content indicated by the content information CI is associated with the food ingredients indicated by the food ingredient information FSI. In this case, the output text information TI may, as an example, be information that causes the user to whom the text indicated by the text information TI is provided to associate the content indicated by the content information CI with the food ingredients indicated by the FSI.

[0059] The text information TI output or generated by the text information output unit 26 may, as an example, be stored in the storage unit 20A.

[0060] (Food information output unit 27) The food information output unit 27 refers to the food ingredient information FSI and outputs at least one of (1) food information FI indicating a food containing at least one of the food ingredients indicated by the food ingredient information FSI, and (2) advice information ADI that includes the food information FI and assists the user's decision-making. The output food information FI may, as an example, be information indicating a food that contains, as any one of flavor, topping, and coloring agent, a raw material derived from the food ingredient indicated by the food ingredient information FSI. Here, the food information FI may, as an example, be text data or image data indicating a food. The food indicated by the food information FI may be a product such as bread that is eaten alone, or a product such as sprinkles that is eaten in combination with another food.

[0061] The advice information ADI may, as an example, be information indicating information about the food indicated by the food information FI included in the advice information ADI. Here, the information about the food may, as an example, be information indicating the nutritional components of the food.

[0062] The food information output unit 27, as an example, ·Refers to the food ingredient information FSI, · In a food database FDB in which a plurality of predetermined types of foods are associated with the ingredients contained in each of the foods, search for foods containing the ingredients indicated by the ingredient information FSI, · Generate information indicating the extracted foods as food information FI, · Output the generated food information FI to the input / output unit 40A, Such a configuration can be adopted.

[0063] The food information FI and the advice information ADI output or generated by the food information output unit 27 may be stored in the storage unit 20A as an example.

[0064] (Flow of processing by the information processing device 1A) Subsequently, with reference to FIGS. 4 and 5, the flow of processing by the information processing device 1A will be described. FIG. 4 is a flowchart showing an example of the flow of processing by the information processing device 1A. FIG. 5 is a diagram for explaining an example of the processing by the information processing device 1A.

[0065] As shown in FIG. 4, the information processing method S1A includes a step (processing) S21 of acquiring content information CI, a step (processing) S22 of generating content emotion information CEI, a step (processing) S23 of acquiring analysis target information AOI, a step (processing) S24 of generating ingredient emotion information FSEI, a step (processing) S25 of outputting ingredient information, a step (processing) S26 of outputting text information, and a step (processing) S27 of outputting food information.

[0066] (Step S21) In step S21, the content information acquisition unit 21 acquires the content information CI. Since the specific processing by the content information acquisition unit 21 has been described above, the description is omitted here.

[0067] (Step S22) In step S22, the content emotion information generation unit 22 generates content emotion information CEI. In the example shown in FIG. 5, the content emotion information generation unit 22 refers to the content information CI, inputs the content information CI into the learned model LM, and generates the content emotion information CEI. Since the specific processing by the learned model LM has been described above, the description is omitted here.

[0068] In the example shown in FIG. 5, as the content information CI to be referred to, text data indicating the conversation content between a man and a woman in a scene that constitutes a drama program, which is video content and depicts the love pattern between a man and a woman, is adopted. As the content emotion information CEI to be generated, data indicating the strength of each of the five predetermined emotions as a numerical value for each emotion type is adopted.

[0069] (Step S23) In step S23, the analysis target information acquisition unit 23 generates analysis target information AOI. Since the specific processing by the analysis target information acquisition unit 23 has been described above, the description is omitted here.

[0070] (Step S24) In step S24, the food ingredient emotion information generation unit 24 generates food ingredient emotion information FSEI. In the example shown in FIG. 5, the food ingredient emotion information generation unit 24 refers to the analysis target information AOI, inputs the analysis target information AOI into the learned model LM, and generates the food ingredient emotion information FSEI. Since the specific processing by the learned model LM has been described above, the description is omitted here.

[0071] In the example shown in FIG. 5, as the analysis target information AOI to be referred to, text data indicating the lyrics of a plurality of songs, each of which includes a phrase indicating the name of a food ingredient, is adopted. In the example shown in FIG. 5, the text data indicates (1) lyrics singing about love in combination with apples, (2) lyrics singing about a broken heart in combination with chocolate, and (3) lyrics singing about jealousy in combination with lemons.

[0072] As the generated food ingredient sentiment information FSEI, for each of the five predetermined emotions and for each food ingredient and for each type of emotion, data indicating the intensity of the emotion as a numerical value is adopted. In the example shown in FIG. 5, for apples, chocolate, and lemons, food ingredient sentiment information FSEI indicating the intensity of each type of emotion as a numerical value is generated.

[0073] (Step S25) In step S25, the food ingredient information output unit 25 generates food ingredient sentiment information FSEI. In the example shown in FIG. 5, the food ingredient information output unit 25 refers to the food ingredient sentiment information FSEI and the content sentiment information CEI, inputs the food ingredient sentiment information FSEI and the content sentiment information CEI into the correlation analysis model AM, generates food ingredient information FSI, and outputs the generated food ingredient information FSI to the input / output unit 40A. Since the specific processing by the correlation analysis model AM has been described above, the description is omitted here.

[0074] In the example shown in FIG. 5, as the output food ingredient information FSI, data indicating the name of the food ingredient is adopted. In the example shown in FIG. 5, the output food ingredient information FSI is data indicating the food ingredient "apple".

[0075] (Step S26) In step S26, the text information output unit 26 generates text information TI. In the example shown in FIG. 5, the text information output unit 26 refers to the content sentiment information CEI and the food ingredient information FSI, and outputs text information TI indicating text in which the emotion indicated by the content sentiment information CEI and the food ingredient indicated by the food ingredient information FSI are associated.

[0076] In the example shown in FIG. 5, as the output text information TI, text data indicating text including a phrase associated with the emotion and a phrase associated with the food ingredient is adopted. In the example shown in FIG. 5, the output text information TI is text data including a phrase related to love and the phrase "apple".

[0077] (Step S27) In step S27, the food information output unit 27 generates food information FI. In the example shown in FIG. 5, the food information output unit 27 refers to the foodstuff information FSI and outputs at least one of (1) food information FI indicating a food containing at least one of the foodstuffs indicated by the foodstuff information FSI and (2) advice information ADI that includes the food information FI and assists the user's decision-making. Here, the food information output unit 27 searches for foods containing the foodstuffs indicated by the foodstuff information FSI in a food database FDB in which a plurality of predetermined types of foods are associated with the foodstuffs contained in each of the foods, and generates and outputs information indicating the extracted foods as the food information FI. Further, as an example, the food information output unit 27 may generate and output, as advice information ADI, information that is included in the food database FDB, is associated with the extracted food, and assists the user's decision-making, in combination with the food information FI.

[0078] In the example shown in FIG. 5, as the food information FI to be output, data indicating the food is adopted. In the example shown in FIG. 5, the food information FI to be output is bread containing apples as a material.

[0079] (Example of processing by the foodstuff information output unit 25) Subsequently, an example of the processing by the foodstuff information output unit 25 will be described with reference to FIG. 6. FIG. 6 is a diagram for explaining an example of the processing by the foodstuff information output unit 25.

[0080] The content emotion information CEI is, as an example, information in which the type of emotion associated with the content and the intensity of the emotion are associated. In the example shown in FIG. 6, the content emotion information CEI is table data in which the intensity of the emotion is associated with each type of emotion as a numerical value indicating the intensity. As shown in FIG. 6, in the content emotion information CEI, the "type of emotion: intensity of emotion" associated with the content is "joy: 4", "sadness: 3", "fear: 2", "love: 4", and "anger: 3".

[0081] Food ingredient emotion information FSEI is, for example, information in which the types of emotions related to food ingredients and the intensity of such emotions are associated. In the example shown in FIG. 6, the food ingredient emotion information FSEI is table data that shows the intensity of emotions as numerical values for each food ingredient included in the food ingredient group and for each type of emotion. As shown in FIG. 6, in the food ingredient emotion information FSEI, the "type of emotion: intensity of emotion" associated with the food ingredient "apple" is "joy: 4", "sadness: 3", "fear: 2", "love: 4", and "anger: 3". Similar associations are made for the food ingredients "lemon", "chocolate", "peanut", "cider", and "coffee" in the food ingredient emotion information FSEI.

[0082] The food ingredient information output unit 25 outputs food ingredient information FSI, for example, based on the correlation between the types and intensities of emotions indicated by the content emotion information CEI and the types and intensities of emotions indicated by the food ingredient emotion information FSEI. In the example shown in FIG. 6, the food ingredient information output unit 25 · refers to the food ingredient emotion information FSEI and the content emotion information CEI, · inputs the food ingredient emotion information FSEI and the content emotion information CEI into the correlation analysis model AM to generate food ingredient information FSI, · outputs the generated food ingredient information FSI to the input / output unit 40A, and can adopt the following configuration. Here, the correlation analysis model AM · calculates a correlation score indicating the degree of correlation between the intensity of emotions in the content emotion information CEI and the intensity of emotions in the food ingredient emotion information FSEI for each food ingredient included in the food ingredient group, · compares the calculated correlation score with a threshold value determined in advance by the correlation analysis model AM for each food ingredient included in the food ingredient group, · generates information indicating the food ingredients for which a correlation score equal to or higher than the threshold value is calculated as the food ingredient information FSI. and can adopt the following configuration. Here, the food ingredient information FSI may be, for example, series data that arranges the food ingredients in descending order of their correlation scores. As an example, the correlation score can adopt a correlation coefficient.

[0083] As shown in FIG. 6, the correlation analysis model AM refers to the "type of emotion: intensity of emotion" associated with the content and the "type of emotion: intensity of emotion" associated with the food ingredient "apple", and calculates the correlation score for the food ingredient "apple" as "4". Next, the correlation analysis model AM compares the correlation score "4" calculated for the food ingredient "apple" with a predetermined threshold "3" for the food ingredient "apple", and determines that the correlation score is equal to or higher than the threshold. The correlation analysis model AM performs the same processing for food ingredients other than "apple". The food ingredient information output unit 25 arranges the food ingredients "apple" and "cider" for which it is determined in the correlation analysis model AM that the correlation score is equal to or higher than the threshold in descending order of the correlation score of the food ingredient, and generates food ingredient information FSI in which "rank: food ingredient" is associated as "1: apple" and "2: cider".

[0084] Note that, as an example, the food ingredient information output unit 25 may generate, as the food ingredient information FSI, data indicating the correlation scores calculated by the correlation analysis model AM for each food ingredient. In this case, the food ingredient information output unit 25 generates food ingredient information FSI in which "food ingredient: correlation score" is associated as "apple: 4", "lemon: 2", "chocolate: 2", "peanut: 2", "cider: 3", and "coffee: 1".

[0085] (Effect of the information processing apparatus 1A) As described above, in the information processing apparatus 1

[0086] As described above, in the information processing apparatus 1A · Output text information TI indicating text in which the emotion indicated by the content emotion information CEI and the food ingredient indicated by the food ingredient information FSI are associated, with reference to the content emotion information CEI and the food ingredient information FSI Such a configuration is adopted. Therefore, the information processing apparatus 1A configured as described above outputs text information TI indicating text in which the emotion indicated by the content emotion information CEI and the food material indicated by the food material information FSI are associated. The text indicated by the text information TI can make the user associate an emotion correlated with the emotion related to the content, and can also make the user associate the food material indicated by the food material information FSI. Therefore, according to the above configuration, the information processing apparatus 1A can output text information TI indicating text that is suitable for explaining to the user a food having the content as a motif and including the food material indicated by the food material information FSI.

[0087] Also, in the information processing apparatus 1A, · Input analysis target information AOI indicating a food material and an emotion associated with the food material into a learned model LM (machine learned model), and generate the food material emotion information FSEI indicating the emotion related to the food material. Such a configuration is adopted. Therefore, the information processing apparatus 1A configured as described above generates the food material emotion information FSEI referred to for outputting the food material information FSI by using the learned model LM (machine learned model). Therefore, according to the above configuration, by adopting emotion as one element of the intermediate information in the machine learned model, it is possible to systematically analyze the relevance between the content and the food material, and provide a technique for proposing a more suitable food material for the food having the content as a motif. Also, according to the above configuration, the information processing apparatus 1A can generate the food material emotion information FSEI for more types of food materials, and therefore can execute a process of outputting the food material information FSI including more types of food materials in the output candidates.

[0088] Also, in the information processing apparatus 1A, · The content emotion information CEI is information in which the type of emotion related to the content and the intensity of the emotion are associated. · The food material emotion information FSEI is information in which the type of emotion related to the food material and the intensity of the emotion are associated. · Based on the correlation between the type and intensity of the emotion indicated by the content emotion information CEI and the type and intensity of the emotion indicated by the food ingredient emotion information FSEI, output the food ingredient information FSI. The above configuration is adopted. Therefore, the information processing apparatus 1A configured as described above outputs the food ingredient information FSI based on the correlation between the type and intensity of the emotion indicated by the content emotion information CEI and the type and intensity of the emotion indicated by the food ingredient emotion information FSEI. Since the food ingredients indicated by the food ingredient information FSI output in this way are more strongly correlated with the emotions related to the content, they are more suitable as materials for foods themed on the content. Therefore, according to the above configuration, it is possible to provide a technique for proposing food ingredients more suitable for foods themed on the content based on information related to the content.

[0089] Also, in the information processing apparatus 1A, · Refer to the food ingredient information FSI and output at least one of (1) food information FI indicating a food containing at least one of the food ingredients indicated by the food ingredient information FSI, and (2) advice information ADI including the food information FI and assisting the user's decision-making. The above configuration is adopted. Therefore, the information processing apparatus 1A configured as described above outputs food information FI indicating a food containing food ingredients indicated by the food ingredient information FSI, which are related to emotions correlated with the emotions related to the content. The food indicated by the output food information FI is suitable as a food themed on the content. Therefore, according to the above configuration, it is possible to provide a technique for proposing foods suitable for foods themed on the content based on information related to the content.

[0090] Also, in the information processing apparatus 1A, · The content information CI is text data. The above configuration is adopted. Therefore, according to the above configuration, it is possible to provide a technique for proposing food ingredients more suitable for foods themed on the content based on the content information CI, which is text data.

[0091] 〔Example of Realization by Software〕 Some or all of the functions of the information processing apparatuses 1 and 1A (hereinafter also referred to as "each of the above apparatuses") may be realized by hardware such as an integrated circuit (IC chip), or may be realized by software.

[0092] In the latter case, each of the above apparatuses is realized by, for example, a computer that executes instructions of a program, which is software for realizing each function. An example of such a computer (hereinafter referred to as computer C) is shown in FIG. 7. FIG. 7 is a block diagram showing the hardware configuration of computer C that functions as each of the above apparatuses.

[0093] Computer C includes at least one processor C1 and at least one memory C2. A program P for operating computer C as each of the above apparatuses is recorded in memory C2. In computer C, processor C1 reads and executes program P from memory C2, whereby each function of each of the above apparatuses is realized.

[0094] As processor C1, for example, a CPU (Central Processing Unit), GPU (Graphic Processing Unit), DSP (Digital Signal Processor), MPU (Micro Processing Unit), FPU (Floating point number Processing Unit), PPU (Physics Processing Unit), TPU (Tensor Processing Unit), quantum processor, microcontroller, or a combination thereof can be used. As memory C2, for example, a flash memory, HDD (Hard Disk Drive), SSD (Solid State Drive), or a combination thereof can be used.

[0095] Incidentally, the computer C may further include a RAM (Random Access Memory) for expanding the program P during execution or temporarily storing various data. Also, the computer C may further include a communication interface for transmitting and receiving data to and from other devices. Further, the computer C may further include an input / output interface for connecting input / output devices such as a keyboard, a mouse, a display, and a printer.

[0096] Also, the program P can be recorded on a non-transitory tangible recording medium M readable by the computer C. As such a recording medium M, for example, a tape, a disk, a card, a semiconductor memory, or a programmable logic circuit can be used. The computer C can acquire the program P via such a recording medium M. Also, the program P can be transmitted via a transmission medium. As such a transmission medium, for example, a communication network or a broadcast wave can be used. The computer C can also acquire the program P via such a transmission medium.

[0097] [Supplementary Note A] The present disclosure includes the technologies described in the following supplementary notes. However, the present invention is not limited to the technologies described in the following supplementary notes, and various modifications are possible within the scope indicated in the claims.

[0098] (Supplementary Note A1) Content information acquisition means for acquiring content information indicating content; Content emotion information generation means for generating content emotion information indicating an emotion related to the content by referring to the content information; Food ingredient emotion information indicating an emotion related to each food ingredient in a group of food ingredients, and food ingredient information output means for outputting one or more food ingredients related to an emotion correlated with the emotion indicated by the content emotion information among the group of food ingredients by referring to the food ingredient emotion information and the content emotion information. An information processing apparatus.

[0099] (Appendix A2) Furthermore, it further includes text information output means for outputting text information indicating text in which the emotion indicated by the content emotion information and the food material indicated by the food material information are associated with reference to the content emotion information and the food material information. The information processing apparatus according to Appendix A1.

[0100] (Appendix A3) Furthermore, it further includes food material emotion information generation means for inputting analysis target information indicating a food material and an emotion associated with the food material into a machine learning model and generating food material emotion information indicating an emotion associated with the food material. The information processing apparatus according to Appendix A1 or A2.

[0101] (Appendix A4) The content emotion information is information in which the type of emotion associated with the content and the intensity of the emotion are associated. The food material emotion information is information in which the type of emotion associated with the food material and the intensity of the emotion are associated. The food material information output means outputs the food material information based on the correlation between the type and intensity of the emotion indicated by the content emotion information and the type and intensity of the emotion indicated by the food material emotion information. The information processing apparatus according to any one of Appendices A1 to A3.

[0102] (Appendix A5) With reference to the food material information, food information indicating a food including at least one of the food materials indicated by the food material information, and advice information including the food information and for assisting the user's decision-making Furthermore, it further includes food information output means for outputting at least any one of them. The information processing apparatus according to any one of Appendices A1 to A4.

[0103] (Appendix A6) The content information is text data. An information processing apparatus according to any one of Supplementary Notes A1 to A5.

[0104] [Supplementary Note B] The present disclosure includes the technologies described in the following respective supplementary notes. However, the present invention is not limited to the technologies described in the following respective supplementary notes, and various modifications are possible within the scope indicated in the claims.

[0105] (Supplementary Note B1) At least one processor performs content information acquisition processing for acquiring content information indicating content, the at least one processor performs content emotion information generation processing for generating content emotion information indicating an emotion related to the content by referring to the content information, the at least one processor includes food material information output processing for outputting food material information indicating one or more food materials related to an emotion correlated with the emotion indicated by the content emotion information among the food material group, by referring to food material emotion information indicating an emotion related to each food material in the food material group and the content emotion information. An information processing method.

[0106] (Supplementary Note B2) the at least one processor further includes text information output processing for outputting text information indicating text in which the emotion indicated by the content emotion information and the food material indicated by the food material information are associated, by referring to the content emotion information and the food material information. The information processing method according to Supplementary Note B1.

[0107] (Supplementary Note B3) the at least one processor further includes food material emotion information generation processing for inputting analysis target information indicating a food material and an emotion associated with the food material into a machine learning model and generating the food material emotion information indicating an emotion related to the food material. The information processing method according to Supplementary Note B1 or B2.

[0108] (Supplementary Note B4) The content emotion information is information in which the type of emotion associated with the content and the intensity of the emotion are associated with each other. The food ingredient emotion information is information in which the type of emotion associated with the food ingredient and the intensity of the emotion are associated with each other. In the food ingredient information output process, the at least one processor outputs the food ingredient information based on the correlation between the type and intensity of the emotion indicated by the content emotion information and the type and intensity of the emotion indicated by the food ingredient emotion information. The information processing method according to any one of Appendices B1 to B3.

[0109] (Appendix B5) The at least one processor refers to the food ingredient information, food information indicating a food including at least one of the food ingredients indicated by the food ingredient information, and advice information including the food information and assisting the user's decision-making further includes a food information output process for outputting at least any one of The information processing method according to any one of Appendices B1 to B4.

[0110] (Appendix B6) The content information is text data. The information processing method according to any one of Appendices B1 to B5.

[0111] [Appendix C] This disclosure includes the technologies described in the following appendices. However, the present invention is not limited to the technologies described in the following appendices, and various modifications are possible within the scope shown in the claims.

[0112] (Appendix C1) A program for causing a computer to function as an information processing apparatus, causing the computer to content information acquisition means for acquiring content information indicating content, Content emotion information generation means for generating content emotion information indicating an emotion related to the content with reference to the content information Food ingredient emotion information indicating an emotion related to each food ingredient in the group of food ingredients, and food ingredient information output means for outputting one or more food ingredients related to an emotion correlated with the emotion indicated by the content emotion information among the group of food ingredients, with reference to the food ingredient emotion information and the content emotion information Information processing program

[0113] (Appendix C2) The computer is Further function as text information output means for outputting text information indicating text in which the emotion indicated by the content emotion information and the food ingredients indicated by the food ingredient information are associated, with reference to the content emotion information and the food ingredient information The information processing program according to Appendix C1

[0114] (Appendix C3) The computer is Further function as food ingredient emotion information generation means for inputting analysis target information indicating a food ingredient and an emotion associated with the food ingredient into a machine learning model and generating food ingredient emotion information indicating an emotion related to the food ingredient The information processing program according to Appendix C1 or C2

[0115] (Appendix C4) The content emotion information is information in which the type of emotion related to the content and the intensity of the emotion are associated The food ingredient emotion information is information in which the type of emotion related to the food ingredient and the intensity of the emotion are associated The food ingredient information output means outputs the food ingredient information based on the correlation between the type and intensity of the emotion indicated by the content emotion information and the type and intensity of the emotion indicated by the food ingredient emotion information The information processing program according to any one of Appendices C1 to C3

[0116] (Appendix C5) Cause the computer to, with reference to the food ingredient information, output at least one of food information indicating a food including at least one of the food ingredients indicated by the food ingredient information, and advice information that includes the food information and assists the user's decision-making by further functioning as food information output means. An information processing program according to any one of Supplementary Notes C1 to C4.

[0117] (Supplementary Note C6) The content information is text data. An information processing program according to any one of Supplementary Notes C1 to C5.

[0118] [Supplementary Note D] The present disclosure includes the technologies described in the following supplementary notes. However, the present invention is not limited to the technologies described in the following supplementary notes, and various modifications are possible within the scope shown in the claims.

[0119] (Supplementary Note D1) Comprising at least one processor, the at least one processor executes content information acquisition processing for acquiring content information indicating content, content emotion information generation processing for generating content emotion information indicating an emotion related to the content with reference to the content information, and food ingredient emotion information indicating an emotion related to each food ingredient in a group of food ingredients, and food ingredient information output processing for outputting one or more food ingredients related to an emotion correlated with the emotion indicated by the content emotion information from among the group of food ingredients, with reference to the food ingredient emotion information and the content emotion information. An information processing apparatus.

[0120] Note that the information processing apparatus may further include a memory. Also, a program for causing the at least one processor to execute each of the above processes may be stored in the memory.

[0121] (Appendix D2) The at least one processor further executes text information output processing for outputting text information indicating text in which the emotion indicated by the content emotion information and the food material indicated by the food material information are associated with each other, with reference to the content emotion information and the food material information. The information processing apparatus according to Appendix D1.

[0122] (Appendix D3) The at least one processor further executes food material emotion information generation processing for inputting analysis target information indicating a food material and an emotion associated with the food material into a machine learned model and generating food material emotion information indicating an emotion associated with the food material. The information processing apparatus according to Appendix D1 or D2.

[0123] (Appendix D4) The content emotion information is information in which the type of emotion associated with the content and the intensity of the emotion are associated with each other. The food material emotion information is information in which the type of emotion associated with the food material and the intensity of the emotion are associated with each other. In the food material information output processing, the at least one processor outputs the food material information based on the correlation between the type and intensity of the emotion indicated by the content emotion information and the type and intensity of the emotion indicated by the food material emotion information. The information processing apparatus according to any one of Appendices D1 to D3.

[0124] (Appendix D5) The at least one processor refers to the food material information and further executes food information output processing for outputting at least any one of food information indicating a food including at least one of the food materials indicated by the food material information and advice information including the food information and assisting the user's decision-making. The information processing apparatus according to any one of Appendices D1 to D4. ​​​​​

[0125] (Appendix D6) The content information is text data. The information processing apparatus according to any one of Appendices D1 to D5.

[0126] [Appendix Item E] The present disclosure includes the technologies described in the following appendices. However, the present invention is not limited to the technologies described in the following appendices, and various modifications are possible within the scope indicated in the claims.

[0127] (Appendix E1) A program that causes a computer to function as an information processing apparatus, to cause the computer to execute content information acquisition processing for acquiring content information indicating content, content emotion information generation processing for generating content emotion information indicating an emotion related to the content by referring to the content information, ingredient information output processing for outputting ingredient emotion information indicating an emotion related to each ingredient in a group of ingredients and ingredient information indicating one or more ingredients related to an emotion correlated with the emotion indicated by the content emotion information among the group of ingredients by referring to the ingredient emotion information and the content emotion information, a non-transitory recording medium recording an information processing program.

Explanation of Signs

[0128] 1, 1A ···· Information processing apparatus 11, 21 ··· Content information acquisition unit (content information acquisition means) 12, 22 ··· Content emotion information generation unit (content emotion information generation means) 13, 25 ··· Ingredient information output unit (ingredient information output means) 23 ······ Analysis target information acquisition unit (analysis target information acquisition means) 24 ······ Ingredient emotion information generation unit (ingredient emotion information generation means) 26 ······ Text information output unit (text information output means) 27 ······ Food information output unit (food information output means) 20A ····· Memory unit 30A ····· Communication unit 40A ····· Input / output unit

Claims

1. Content information acquisition means for acquiring content information indicating content, Content emotion information generation means for generating content emotion information indicating an emotion related to the content by referring to the content information, Food material emotion information indicating an emotion related to each food material in a group of food materials, and food material information output means for outputting information on one or more food materials related to an emotion correlated with the emotion indicated by the content emotion information among the group of food materials by referring to the food material emotion information and the content emotion information, An information processing apparatus.

2. The information processing apparatus according to claim 1, further comprising text information output means for outputting text information indicating text in which the emotion indicated by the content emotion information and the food material indicated by the food material information are associated by referring to the content emotion information and the food material information. The information processing apparatus according to claim 1.

3. The information processing apparatus according to claim 1 or 2, further comprising food material emotion information generation means for inputting analysis target information indicating a food material and an emotion associated with the food material into a machine learning model and generating the food material emotion information indicating an emotion related to the food material. The information processing apparatus according to claim 1 or 2.

4. The content emotion information is information in which the type of emotion related to the content and the intensity of the emotion are associated, The food material emotion information is information in which the type of emotion related to the food material and the intensity of the emotion are associated, The food material information output means outputs the food material information based on the correlation between the type and intensity of the emotion indicated by the content emotion information and the type and intensity of the emotion indicated by the food material emotion information. The information processing apparatus according to claim 1 or 2.

5. By referring to the food material information, Food information indicating a food including at least one of the food materials indicated by the food material information, and Advice information including the food information and assisting the user's decision-making The information processing apparatus according to claim 1 or 2, further comprising food information output means for outputting at least any one of them. The information processing apparatus according to claim 1 or 2.

6. The content information is text data. The information processing apparatus according to claim 1 or 2.

7. Acquiring content information indicating content, Generating content emotion information indicating an emotion related to the content by referring to the content information, Outputting food material information indicating one or more food materials in the food material group that are related to an emotion correlated with the emotion indicated by the content emotion information, with reference to the food material emotion information indicating the emotion related to each food material in the food material group and the content emotion information. Information processing method. **Claim 8** Causing a computer to perform a content information acquisition process of acquiring content information indicating content; a content emotion information generation process of generating content emotion information indicating an emotion related to the content with reference to the content information; and a food material information output process of outputting food material information indicating one or more food materials in the food material group that are related to an emotion correlated with the emotion indicated by the content emotion information, with reference to the food material emotion information indicating the emotion related to each food material in the food material group and the content emotion information. Program.

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