Abstract: An information processing apparatus extracts a phrase corresponding to a named entity included in an input sentence used for training a natural language processing model from data in which a phrase and a classification name of a named entity are associated with each other, adds the extracted phrase to the classification name corresponding to the extracted phrase among a plurality of different classification names which are set in advance, derives a similarity between a distributed representation of each word included in the input sentence and a distributed representation of each of the plurality of classification names to which the phrase is added, and select a classification name of each word included in the input sentence from among the plurality of classification names based on the derived similarity.

Abstract: An information processing apparatus acquires a plurality of pieces of document data, each including a plurality of partial documents, and date information associated with each of the plurality of pieces of document data, derives partial document relationship information representing a relationship between the partial documents, based on a similarity between the partial documents and the date information, among the plurality of pieces of document data, and derives overall document relationship information representing an overall relationship among the plurality of pieces of document data, based on the partial document relationship information.

Abstract: An information processing method executed by one or more processors, in which a plurality of models, which are trained by using one or more of datasets including a behavior history of a user on an item, which is collected at each of a plurality of first facilities different from each other, are prepared, and the one or more processors include acquiring a characteristic of a second facility, which is different from the plurality of first facilities and acquiring a characteristic of each of the plurality of first facilities, evaluating a similarity degree between the acquired characteristic of the second facility and the characteristic of the first facility where the dataset, which is used for the training of the model, is collected, and selecting a model suitable for the second facility from among the plurality of models based on the similarity degree.

Abstract: A corrosion-resistant member according to the present disclosure is a laminate body including a base and a first layer layered on the base. The first layer is composed of a rare earth element compound containing, as a main constituent, a rare earth element that is a metal element. In the first layer, a crystallinity of a region close to the base is lower than a crystallinity of a region far from the base. A corrosion-resistant member according to the present disclosure is a laminate body including a base, a compound layer layered on the base and composed of a metal element M, and a first layer layered on the compound layer. The first layer is composed of a rare earth element compound containing, as a main constituent, a rare earth element that is a metal element. The compound layer has a uniform crystallinity. In the first layer, a crystallinity of a region close to the base is lower than a crystallinity of a region far from the base.

Abstract: A gas turbine engine includes a cooling air supply passage that feeds air from a compressor, as a cooling medium, to a turbine by swirling the air in a circumferential direction. The cooling air supply passage includes an entry zone to which the air enters, and a swirl zone in which the air flowing past the entry zone is circumferentially redirected. The gas turbine engine also includes a chamber branching from the swirl zone to capture foreign particles in the air. The chamber is formed to meet the relation: ??? where, when viewed in a radial direction, ? is an angle defined by the swirl zone relative to a horizontal direction and ? is an angle defined between the chamber and the swirl zone.

Abstract: A CPU of a training data creation apparatus includes an extraction unit, a derivation unit, and a creation unit. The extraction unit extracts a plurality of unique expressions that are specific term phrases from a medical document. The derivation unit derives a degree of association indicating a degree of association among the plurality of unique expressions. The creation unit selects a target term phrase that is a term phrase as a target to be masked.

Abstract: A CPU of a training data creation apparatus includes an extraction unit, a derivation unit, and a creation unit. The extraction unit extracts a plurality of unique expressions that are specific term phrases from a medical document. The derivation unit derives a degree of association indicating a degree of association among the plurality of unique expressions. The creation unit selects a target term phrase that is a term phrase as a target to be masked.

Abstract: Provided are an information processing method, an information processing apparatus, and a program that realize generation of a dataset of a user behavior history of different domains. An information processing method includes acquiring a dataset in one domain, the dataset being a dataset in which the response variable, the explanatory variable, and a plurality of variables excluding the response variable and the explanatory variable are applied, selecting a plurality of domain candidate variables that are domain candidates from the plurality of variables excluding the response variable and the explanatory variable, generating a dataset candidate that divides the dataset by using the domain candidate variables, and generating, in a case where each of the dataset candidates is a dataset in a different domain, a divided dataset by setting the domain candidate variables as domains.

Abstract: Provided are an information processing method, an information processing apparatus, and a program capable of generating data of a user behavior history of different domains. An information processing method executed by one or more processors, the method includes: causing the one or more processors to represent a simultaneous probability distribution between a response variable and an explanatory variable, with a behavior for an item of an user as the response variable, for a dataset including a behavior history with respect to a plurality of the items of a plurality of the users, modify a part of the simultaneous probability distribution, and generate data based on the modified simultaneous probability distribution.

Abstract: A gas turbine engine includes a cooling air supply passage that feeds air from a compressor, as a cooling medium, to a turbine by swirling the air in a circumferential direction. The cooling air supply passage includes an entry zone to which the air enters, and a swirl zone in which the air flowing past the entry zone is circumferentially redirected. The gas turbine engine also includes a chamber branching from the swirl zone to capture foreign particles in the air. The chamber is formed to meet the relation: ??? where, when viewed in a radial direction, ? is an angle defined by the swirl zone relative to a horizontal direction and ? is an angle defined between the chamber and the swirl zone.

Abstract: An information processing apparatus generates a first character string set by dividing first document data into different lengths, derives an evaluation value of each character string constituting the first character string set by using the first character string set and second document data created from the first document data in accordance with a purpose, and selects, based on the derived evaluation value, a plurality of character strings from the first character string set as correct answer data of a generative model that receives input of document data and outputs a second character string set including a plurality of character strings included in the input document data.

Abstract: An information processing apparatus acquires document data, and an item and a numerical value which are associated with each other, and extracts, in a case in which a second numerical value within an allowable range including an acquired first numerical value is included in the document data, a phrase existing around the second numerical value included in the document data as a candidate for a synonymous term of the item.

Abstract: A prediction device that predicts information related to a patient based on medical data of the patient, including: a processor; and a memory connected the processor, in which the processor being configured to execute: data set extraction processing of extracting M data sets by classifying pieces of medical data of plural patients into any one of M types of predetermined attributes, training data set generation processing of generating M training data sets related to the M types of attributes from the M data sets, similarity calculation processing of calculating, for each pair of the M types of attributes, a similarity between the attributes, training processing of training one or plural machine learning models based on the similarity between the attributes by using the M training data sets, and prediction processing of causing the one or plural machine learning models to predict the information related to the patient.

Abstract: There is provided a device for generating a data merging rule for a machine learning model, the device including: a processor, and a memory connected to or built in the processor, in which the processor is configured to execute specifying processing of specifying a combination of feature vectors that are included in a data set including a correct answer label and are allowed to be merged, and rule generation processing of generating a merging rule of the feature vectors based on a combination of the feature vectors that are allowed to be merged.

Abstract: There is provided a device for determining an execution order of a plurality of tasks, the device including: processor; and a memory connected to or built in the processor, in which the processor is configured to execute execution order determination processing of determining an execution order of the plurality of tasks under a condition that an output of at least one task of the tasks is input to the task in a subsequent stage.

Abstract: An information processing apparatus extracts a phrase corresponding to a named entity included in an input sentence used for training a natural language processing model from data in which a phrase and a classification name of a named entity are associated with each other, adds the extracted phrase to the classification name corresponding to the extracted phrase among a plurality of different classification names which are set in advance, derives a similarity between a distributed representation of each word included in the input sentence and a distributed representation of each of the plurality of classification names to which the phrase is added, and select a classification name of each word included in the input sentence from among the plurality of classification names based on the derived similarity.

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: 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: There is provided an information processing method, an information processing apparatus, and a program capable of preparing a high performance model for an unknown introduction destination facility even in a case where a domain of the introduction destination facility is unknown at a step of training a model. The information processing method includes: dividing a dataset, which indicates a behavior of a user on an item for each of combinations of a plurality of the users and a plurality of the items, into a plurality of subgroups that are robust with respect to domain shift; generating a local model for performing a prediction of the behavior of the user on the item for each of the subgroups; and combining a plurality of the local models generated for each of the subgroups.