Abstract: A model generation apparatus includes a processor that is configured to: acquire information data for learning, acquire document data for learning, extract a first portion and a second portion having a lower rate of match with the information data than the first portion from the document data based on a rate of match between the information data and each portion of the document data, generate a first machine learning model by using first learning data in which first data for learning included in the information data is used as input data and the first portion is used as correct answer data, and generate a second machine learning model by using second learning data in which second data for learning included in the information data is used as input data and the second portion is used as correct answer data.

Abstract: An information processing apparatus includes at least one processor, in which the processor is configured to: for a machine learning model that uses a document data group including a plurality of document data as input and outputs output data, derive an evaluation value in the machine learning model for each document data included in the document data group.

Abstract: An information processing apparatus including: plural models including at least a first model that uses first data as input to carry out a first prediction task and a second model that uses second data as input to carry out a second prediction task different from the first prediction task, and at least one processor, in which the processor is configured to: acquire information data representing information related to a specific target; select a selection model to be used for prediction from among the plural models based on the information data; and derive a degree of importance to the specific target for each item included in the information data by using the selection model.

Abstract: An information processing device includes a processor configured to acquire subject information and classification information, the subject information being information related to a subject to advertise, and the classification information being information classifying advertising copy related to the subject into a set, and estimate a user reaction by inputting the acquired subject information and classification information into a trained reaction estimation model that estimates the user reaction.

Abstract: An information processing device includes a processor configured to acquire provision information and subject information, the provision information being information related to at least one of a source that provides a sentence and a destination that indicates where the sentence is written, and the subject information being information related to a subject about which the sentence is generated, and estimate a sentence length for the subject associated with the provision information by inputting the acquired provision information and the acquired subject information into a length estimation model trained to learn the lengths of past sentences for subjects associated with past provision information and past subject information.

Abstract: A controller includes a processor configured to receive an attribute of a device that a user uses, and control, in accordance with the attribute of the device, a representation of association text such that, by selecting a representation of association text out of a plurality of representations of association text and displaying the selected representation of association text, motivation of the user of a behavior performed for an object displayed in a display region of the device is increased, the association text being associated with the object displayed in the display region of the device.

Abstract: An information processing apparatus includes: a processor configured to: receive a text for a target that is input from a user; specify past texts similar to the received text based on similarity degrees between the received text and past texts that are in the past at a time when the text for the target is posted; and predict a user's rating for the target based on ratings associated with the specified past texts.

Abstract: An information processing apparatus includes a processor configured to receive a narrowing condition designated upon a search request of a content, create a sentence which uses a more detailed expression of an expression described in the narrowing condition and indicates details of the content or select the sentence from sentence candidates prepared in advance, and present the created or selected sentence as a search result of the content.

Abstract: An information processing apparatus includes an acquisition unit that acquires an information group in which an abbreviated name is used, a specification unit that specifies a position where the abbreviated name is used in the information group from a type of information group acquired, a first extraction unit that extracts the abbreviated name from the specified position, a second extraction unit that extracts a formal name on the basis of a character related to the information group, and an association unit that associates the abbreviated name and the formal name with each other.

Abstract: An information processing apparatus includes a determination unit that determines a delivery priority of delivery target information on the basis of a disclosure possibility of the delivery target information and a necessity of the information for a receiver, and a disclosure unit that discloses the information to the receiver according to the delivery priority.

Abstract: An output apparatus includes a processor configured to receive an input word expressing a feature of a matter; and, by inputting the input word to a generation model trained on relation between a feature term extracted based on a descriptive text describing the matter and an associative text associated with the matter, the associative text being generated from the descriptive text describing the matter, output an associative text corresponding to the input word.

Abstract: A generation device includes a processor. The processor is configured to input, into a learning model that has learned, using learning data in which user information of a user, a purchase history of the user regarding a product, product information of the product, and text associated with the product, the text being added to the product, are associated with one another, association of the user information, the purchase history, the product information, and the text included in the learning data, the user information of the user and product information of a recommended product recommended to the user, and generate text associated with the recommended product based on the purchase history of the user.

Abstract: An output apparatus includes a processor configured to receive an input word expressing a feature of a matter; and, by inputting the input word to a generation model trained on relation between a feature term extracted based on a descriptive text describing the matter and an associative text associated with the matter, the associative text being generated from the descriptive text describing the matter, output an associative text corresponding to the input word.

Abstract: An information processing device includes a computation unit that computes a similarity between character strings among plural character strings which express a content of electronic information and which are generated from the electronic information, and an association unit that associates a dissimilar character string that is not similar to another character string among the plural character strings with the electronic information as a representative character string that expresses the electronic information.

Abstract: An information processing apparatus includes a first label determination unit that determines a first label from information included in an e-mail, a second label determination unit that determines a second label from a result of a response made to the e-mail by a user, and a third label determination unit that determines a third label as a negative example for machine learning which is imparted to the e-mail, in a case where the first label and the second label do not correspond to each other.

Abstract: A non-transitory computer readable medium stores a program causing a computer to execute a process for learning. The process includes: generating, from an input text, an output text related to content of the input text and different from the input text by using a generation model that generates the output text from the input text; reconstructing the input text from the output text by using a reconstruction model that reconstructs the input text from the output text; and updating at least one of the generation model and the reconstruction model by causing the at least one of the generation model and the reconstruction model to perform learning by using a difference between the input text and a reconstructed text reconstructed in the reconstructing.

Abstract: An information processing apparatus includes a predicting unit that predicts a first transaction count by which a user performs a commercial transaction of an item when an advertisement explaining the item is displayed and a second transaction count by which the user performs the commercial transaction of the item when the advertisement is not displayed, a determination unit that determines a degree of influence that the advertisement has on the commercial transaction of the item from information on the first transaction count and the second transaction count and information on the item, an identifying unit that identifies a combination of an item and an advertisement, the combination having a maximum degree of influence, and a controller that performs control to display the identified combination of the item and the advertisement.

Abstract: An information processing device includes a computation unit that computes a similarity between character strings among plural character strings which express a content of electronic information and which are generated from the electronic information, and an association unit that associates a dissimilar character string that is not similar to another character string among the plural character strings with the electronic information as a representative character string that expresses the electronic information.

Abstract: An information processing apparatus includes a determination unit that determines a delivery priority of delivery target information on the basis of a disclosure possibility of the delivery target information and a necessity of the information for a receiver, and a disclosure unit that discloses the information to the receiver according to the delivery priority.

Abstract: An information processing apparatus includes a first label determination unit that determines a first label from information included in an e-mail, a second label determination unit that determines a second label from a result of a response made to the e-mail by a user, and a third label determination unit that determines a third label as a negative example for machine learning which is imparted to the e-mail, in a case where the first label and the second label do not correspond to each other.