Abstract: In order to attain the object of improving image search accuracy even in a case where the amount or accuracy of information pertaining to an image is not sufficient, an image search apparatus (1) includes: a generation unit (11) that generates explanatory information for each of images stored in an image storage apparatus; an acquisition unit (12) that acquires a search query; a search unit (13) that searches for an image across the image storage apparatus with use of the search query and the explanatory information; an output unit (14) that outputs a search result obtained by the search unit (13); an input unit (15) that receives input of a determination result from a user with respect to the search result; and an update unit (16) that updates the explanatory information on a basis of the determination result and the search query.

Abstract: An information processing apparatus includes an acquisition unit for acquiring event information indicating a target event which is an event likely to be associated with a payment cause of insurance, and an extraction unit for extracting a related payment cause related to the target event from a document describing a payment cause of insurance using an extraction model trained by machine learning to output a portion related to the data in the document using a set of the document and the data as an input. The information processing apparatus supports decision making in insurance payment assessment.

Abstract: An information processing apparatus includes a classification unit that classifies a plurality of pieces of numerical data related to a life plan of a subject into data items for generating support information of life planning using content information indicating content of each piece of numerical data and a language model, and a support information generation unit that generates support information using the numerical data as data of a data item classified by the classification unit. The information processing apparatus supports the decision making of the subject.

Abstract: An information processing apparatus includes an acquisition unit that acquires notification information indicating a candidate item that may be associated with a notification item in an insurance contract, and an extraction unit that extracts a notification item related to the candidate item from a document in which the notification item of the insurance is described, using an extraction model. The information processing apparatus enables an applicant to be supported in making a decision in reporting a notification item.

Abstract: An information processing apparatus includes an acquisition unit that acquires condition information indicating a desired condition of the subject for insurance, and an extraction unit that extracts a related description related to the desired condition from a document describing an insurance product that is a candidate recommended to the subject, using an extraction model with machine learning in such a way as to output a portion related to data in the document using a set of the document and the data as an input. Decision making in a case where the subject selects an insurance product can be supported.

Abstract: At least one processor included in an optical signal state estimation apparatus carries out: an acquisition process for acquiring a constellation of an optical signal; a generation process for generating time series data in which pieces of histogram information are arranged in time series, the histogram information being obtained by counting the number of signal points of the constellation, the signal points being included in each of grids obtained by dividing an in-phase component direction and a quadrature component direction into a specific number of rows and the specific number of columns, respectively; and an estimation process for estimating a state of the optical signal by inputting the time series data to a learned model.

Abstract: A communication route setting device 100 of the present invention includes an optical signal acquisition unit 121 that acquires an optical signal on a transmission path in a network in which optical communication devices are connected to each other via an optical transmission path, a condition determination unit 122 that determines a physical condition of at least one object of the optical transmission path and the optical communication devices on the basis of the optical signal, and a route setting unit 123 that sets a communication route for transmitting the optical signal on the network on the basis of the determined physical condition.

Abstract: In order to attain an object of providing a technique to, upon detection of an abnormality in a welded part, provide notification of a factor of the detected abnormality, an abnormality diagnosis apparatus includes: an acquisition means (21) for acquiring time series data containing at least one of an electric current value and a voltage value at first welding; an abnormality determination means (22) for determining, with use of an abnormality determination model and based on the time series data acquired by the acquisition means, whether or not there is an abnormality in a welded part at the first welding; and an output means (23) for, if the abnormality determination means has determined that there is an abnormality, outputting the determination result and at least one of a factor of the abnormality and a remedial method for solving the abnormality.

Abstract: In an information processing device, a provision means provides multiple terminals with a common search model. A filter acquisition means acquires, from each terminal, a filter configured by a feature value obtained using the search model. A data acquisition means acquires, from each terminal, a target time series data subjected to state estimation. A estimation means estimates a state of the terminal which outputted the target time series data, based on the target time series data and the filter.

Abstract: In order to attain the object of providing a technique that allows a process of constructing a model to be presented in an easily understandable manner, a model generation assistance apparatus includes: an acquisition section that acquires trial information including a parameter used in a trial in a process of constructing an AI model; an inference section that infers association between a plurality of trials on the basis of a difference between respective pieces of trial information of the plurality of trials; and an output section that outputs display data including (i) a plurality of nodes respectively representing the plurality of trials and (ii) a link representing the association.

Abstract: A learning device 100 according to this invention includes: a classification unit 121 configured to classify measurement value data measuring performance of an object on the basis of situation data each representing a situation of the object when the measurement value data are measured; a selection unit 122 configured to select the measurement value data from each of the classifications according to the number of the measurement value data for each of the classifications; and a learning unit 123 configured to perform machine learning on the basis of the selected measurement value data.

Abstract: An information processing apparatus (10) includes acquisition means (11) for acquiring information indicating a defect of a first relay apparatus (20), and control means (12) for changing at least one of a setting of the first relay apparatus regarding communication and a setting of a second relay apparatus (20) regarding communication based on the information acquired by the acquisition means, the second relay apparatus being configured to communicate with the first relay apparatus.

Abstract: In a model optimization device for a parameter estimation concerning optical communications, A model acquisition acquires a trained model. A data acquisition means acquires data from a terminal device. A model update means performs a model update of the trained model step by step to generate an updated model based on the data. A model output means outputs to an output destination device corresponding to the terminal device.

Abstract: A warning apparatus (2000) acquires first detected event information (10) representing, at a first abstraction level, an event set being a set of events having occurred in a target system. The warning apparatus (2000) generates second detected event information (20) from the first detected event information (10). The second detected event information (20) represents, at a second abstraction level, the event set represented by the first detected event information (10). The warning apparatus (2000) determines, from among a plurality of pieces of threat information (30) each representing a threat activity, the threat information (30) having a high degree of relevance to at least either of the first detected event information (10) and the second detected event information (20).

Abstract: The present invention reduces the load on a user when performing remote machine diagnosis. An acquisition unit (11) acquires time-series data obtained from equipment of the machine, a prediction unit (12) predicts the state of the machine on the basis of the time-series data, a search unit (13) uses the time-series data as a query to search a knowledge database, storing records of past diagnoses, for knowledge information related to the state of the machine, and a provision unit (14) provides the prediction result and the knowledge information.

Abstract: An information processing apparatus (2000) classifies each event that occurred in a target apparatus to be determined (10) either as an event (event of a first class) that also occurs in a standard apparatus (20) or as an event (event of a second class) that does not occur in the standard apparatus (20). Herein, a first model used for a determination with respect to an event that also occurs in the standard apparatus (20) and a second model used for a determination with respect to an event that does not occur in the standard apparatus (20) are used as models for determining whether an event that occurs in a target apparatus to be determined (10) is a target for warning. The information processing apparatus (2000) performs learning of the first model using an event of the first class. Further, the information processing apparatus (2000) performs learning of the second model using an event of the second class.

Abstract: At least one processor included in an optical signal state estimation apparatus carries out: an acquisition process for acquiring a constellation of an optical signal; a generation process for generating time series data in which pieces of histogram information are arranged in time series, the histogram information being obtained by counting the number of signal points of the constellation, the signal points being included in each of grids obtained by dividing an in-phase component direction and a quadrature component direction into a specific number of rows and the specific number of columns, respectively; and an estimation process for estimating a state of the optical signal by inputting the time series data to a learned model.

Abstract: A learning model is trained so that a signal state can be estimated with high accuracy even in a case where a constellation on a complex plane is rotated. A learning apparatus (1) includes: an acquisition section (11) that acquires a constellation of a known state optical signal transmitted through optical fiber; a generation section (12) that generates a corrected constellation obtained by rotating the constellation on a complex plane; and a learning section (13) that uses the constellation and the corrected constellation to train a learning model.

Abstract: To extract data-for-machine-leaning so as to enable accurate detection of an abnormality while reducing normal state patterns in a mobile network. A learning data extracting apparatus includes: an issuing section that issues a network service use request which is to be processed by cooperation of a plurality of communication apparatuses constituting C-plane; an obtaining section that obtains, as pieces of candidate learning data, time series data of information relating to the plurality of communication apparatuses; and an extracting section that extracts, as data-for-machine-leaning, a piece of candidate learning data with which the process in response to the network service use request has been successfully ended, from among the pieces of candidate learning data.

Abstract: A first information processing apparatus (2000) determines an alternative representation (20) of an event sequence represented by a plurality of event histories (12), by use of dictionary data (30). The first information processing apparatus (2000) outputs information including the determined alternative representation (20). The dictionary data (30) indicate an event sequence and an alternative representation (20) relating to the event sequence in association with each other.