Abstract: A random number generator includes an input receiving unit configured to receive an input for designating a probability distribution of random numbers, a model generation unit configured to generate, based on the probability distribution, an Ising model using n binary variables (n is an integer equal to or greater than 2) each of which is assigned to a respective one of n subintervals obtained by dividing a numerical range of random numbers, an annealing result acquisition unit configured to acquire values of the n binary variables, the values being an execution result of quantum annealing for the Ising model, and a random number output unit configured to output, as a random number, a value included in the subinterval assigned to the binary variable whose value, which has been obtained as the execution result, is equal to a predetermined value.

Abstract: An information processing device 1B mainly includes a machine learning means 15B, a sampling calculation means 16B, and a simulation calculation means 17B. The machine learning means 15B is configured to perform a machine learning of a model which represents the relation among observed data, an observation result, and a simulation parameter, the simulation parameter being required when performing a simulation for predicting the observation result based on observed data. The sampling calculation means 16B is configured to perform, based on a result of the machine learning, sampling of a simulation parameter to be used for machine learning. The simulation calculation means 17B is configured to perform a simulation using the sampled simulation parameter. The machine learning means 15B is configured to perform the machine learning again based on an error evaluation on a simulation result which is a result of the simulation.

Abstract: A learning system (100) includes an information transfer apparatus (10) and a learning processing apparatus (20). The information transfer apparatus (10) includes: an analysis unit (11) that obtains data serving as a learning target, compares the obtained data with a reference model, and assigns, to the data, an index indicating a degree of worthiness of the data as the learning target; and a transmission processing unit (12) that transmits the data to the learning processing apparatus (20) based on a rule that has been set using the index. The learning processing apparatus (20) includes a learning processing unit (21) that updates the model or generates a new model based on the data transmitted from the information transfer apparatus (10).

Abstract: The data processing device includes a display unit, a touch panel unit that detects a touch operation and outputs detection information, a flick detection unit, a label determination unit, and a teacher data generation unit. The flick detection unit detects a flick direction from the detection information of the touch panel unit. The label determination unit determines a label representing a category to which content belongs, based on the flick direction. The teacher data generation unit displays the content on the display unit, and generates teacher data including the displayed content and the label determined by the label determination unit.

Abstract: Even when processing object data includes confidential information, distributed processing can be performed. An apparatus determination unit 220 of a server apparatus 200 selects a client apparatus 100 or the server apparatus 200 as an apparatus which performs a predetermined process based on right information 251 indicating a right of a user of the client apparatus 100 to input data for the predetermined process. When the client apparatus 100 performs the predetermined process, a server side processing unit 230 transmits the input data to the client apparatus 100. When the server apparatus 200 performs the predetermined process, the server side processing unit 230 performs the predetermined process and transmits a processing result of the predetermined process to the client apparatus 100. When the client apparatus 100 performs the predetermined process, the client side processing unit 130 of the client apparatus 100 performs the predetermined process using the input data.

Abstract: A learning system (100) includes an information transfer apparatus (10) and a learning processing apparatus (20). The information transfer apparatus (10) includes: an analysis unit (11) that obtains data serving as a learning target, compares the obtained data with a reference model, and assigns, to the data, an index indicating a degree of worthiness of the data as the learning target; and a transmission processing unit (12) that transmits the data to the learning processing apparatus (20) based on a rule that has been set using the index. The learning processing apparatus (20) includes a learning processing unit (21) that updates the model or generates a new model based on the data transmitted from the information transfer apparatus (10).

Abstract: An information extraction device includes: a storage unit that stores structured model information that is a result obtained by learning a relationship between a type of structured information that is information having a relationship and a data content or a position of data of the structured information; and a structurization executing unit that extracts the structured information from document data that is an extraction object based on the structured model information.

Abstract: The present invention provides an evaluation apparatus and an evaluation method which can evaluate an evaluation target person without difficulty, based on data regarding the evaluation target person. An evaluation apparatus 1 includes a condition determining unit 11 and an evaluation unit 12. On the basis of first data D1, which includes a feature quantity of information generated according to an activity of a first evaluation target person, and an evaluation value E1 of each first evaluation target person, the condition determining unit 11 determines a condition CO which associates the first data D1 and the evaluation value E1. On the basis of second data D2, which includes a feature quantity of information generated according to an activity of a second evaluation target person, and the condition CO, the evaluation unit 12 calculates an evaluation value E2 of the second evaluation target person.

Abstract: Provided are a matching device, a matching method, and a non-transitory computer readable medium storing a program, which are capable of performing matching between two pieces of information having different properties. A matching device that performs matching between a human resource that searches for an organization that meets a specific requirement and an organization that searches for a human resource that meets a specific requirement includes: a storage unit that holds human resource information indicative of a requirement for the human resource and organization information indicative of a requirement for the organization; and a matching processing unit that calculates a matching score representing a relationship between the human resource information and the organization information.

Abstract: The data processing device includes a display unit, a touch panel unit that detects a touch operation and outputs detection information, a flick detection unit, a label determination unit, and a teacher data generation unit. The flick detection unit detects a flick direction from the detection information of the touch panel unit. The label determination unit determines a label representing a category to which content belongs, based on the flick direction. The teacher data generation unit displays the content on the display unit, and generates teacher data including the displayed content and the label determined by the label determination unit.

Abstract: A data processing device includes a storage part, a machine learning part, a classifying part, and a user interface part. The storage part stores a plurality of teacher data each including content and a label representing a category to which the content belongs. The machine learning part generates a classification model by using the plurality of teacher data. The classifying part determines the category that the content of each of the plurality of teacher data belongs by using the classification model. The user interface part causes a display part to display the content and label of the teacher data and the category that the content belongs determined by the classifying part.

Abstract: Even when processing object data includes confidential information, distributed processing can be performed. An apparatus determination unit 220 of a server apparatus 200 selects a client apparatus 100 or the server apparatus 200 as an apparatus which performs a predetermined process based on right information 251 indicating a right of a user of the client apparatus 100 to input data for the predetermined process. When the client apparatus 100 performs the predetermined process, a server side processing unit 230 transmits the input data to the client apparatus 100. When the server apparatus 200 performs the predetermined process, the server side processing unit 230 performs the predetermined process and transmits a processing result of the predetermined process to the client apparatus 100. When the client apparatus 100 performs the predetermined process, the client side processing unit 130 of the client apparatus 100 performs the predetermined process using the input data.

Abstract: An input assistance device according to an exemplary aspect of the present invention includes: an operation storing unit which stores a plurality of types of operations targeting a display object arranged in a shared screen shared by a plurality of terminal devices; an operation history storing unit which stores a history operation that is a performed operation targeting an arranged object which is the display object stored in display object storing unit and arranged in the shared screen, in order of performance of the history operation, and stores participating user identifiers that are identifiers of users of the plurality of terminal devices; and an operation score deriving unit which derives an operation probability being a probability that a target user performs next time a candidate operation being the operation stored in the operation storing unit, based on a target user identifier, the history operation, and the participating user identifier.

Abstract: A vehicle state determination unit receives vehicle data from a vehicle sensor and position data from a position sensor with a certain frequency. A mode selection unit selects a driving operation mode on the basis of the data received from the vehicle state determination unit and passes the data to a data comparison unit. The data comparison unit reads out model data of the driving operation mode specified by the mode selection unit, from a model data storage unit, compares data received from the vehicle state determination unit and the model data, and passes the comparison result to a driving state determination unit. The driving state determination unit statistically processes the comparison result received from the data comparison unit and passes the result of the determination to a warning display unit.

Abstract: A stream data control server includes: a processable flow rate managing unit which manages a processable flow rate corresponding to an amount of data per unit time, which can be processed in each of storage units serving as storing destinations; a classified data flow rate managing unit which manages a data flow rate corresponding to an amount of data processed per unit time for each class of data to which a data priority is attached; and a storing destination control unit which controls the storing destinations of respective data based upon the processable flow rate of each of the storage units and the data flow rate for each class in such a manner that the data having higher data priorities are stored in the storage units having higher priorities within a range of the processable flow rate of each of the storage units.

Abstract: An analysis preprocessing system is provided which is capable of, when large amounts of data are received from a large number of data generation sources, rapidly passing those data to means for analyzing the data in order of time of generation thereof. Data acquisition means 71 acquires a data group generated by a plurality of data generation sources. Data clipping means 72 clips each data from the data group. Rearrangement control means 73 retains each clipped data therein, selects data generated prior to the corresponding data when data from a delay maximum data generation source is detected, and rearranges the selected data in order of time of generation thereof. A data storage buffer 74 stores the data rearranged in order of time of generation thereof. Analysis data determination means determines an analysis data group which is a set of data used for analysis, from the data stored in the data storage buffer 74.

Abstract: In a computer system, an SQL as a content of data processing request by a database independent protocol (protocol connected to a DBMS) that is issued by an application 3110 is converted from an SQL for an old DB before a migration to an SQL for a new DBMS 3200, then converted into a protocol that depends on a new DBMS 3210, and then provided to the new DBMS 3210. This operation is realized by an extension DB connection middleware 3120 that is obtained by extending a DB connection middleware that does not depend on the DBMS or an application.

Abstract: In an environment such as the Internet where a wide variety of electronic apparatuses should be managed and which includes many electronic apparatuses, connection must be modified smoothly according to a status change. An apparatus status collection unit collects apparatus status such as types, loads and positions of electronic apparatuses. A communication status collection unit collects communication status such as a type, path and load of communication. A connection rule retention unit retains beforehand a connection rule indicating a communication connection method being relevant to certain apparatus status, communication status and terminal status. A connection method decision unit compares apparatus status, communication status and terminal status with connection rules to extract a connection rule indicating an appropriate connection method.

Abstract: An analysis preprocessing system is provided which is capable of rapidly passing data to means for analyzing data while preventing the data from overflowing, even if large amounts of data are transmitted from a large number of data generation sources. Data acquisition means 71 acquires a data group generated by the plurality of data generation sources. Data clipping means 72 clips each data from the data group acquired by the data acquisition means 71. Sampling means 73 samples part of the clipped data and stores the sampled data in a buffer 74. Analysis data determination means 75 determines an analysis data group which is a set of data used for analysis, from the data stored in the buffer 74.

Abstract: An analysis preprocessing system is provided which is capable of, when large amounts of data are received from a large number of data generation sources, rapidly passing those data to means for analyzing the data in order of time of generation thereof. Data acquisition means 71 acquires a data group generated by a plurality of data generation sources. Data clipping means 72 clips each data from the data group. Rearrangement control means 73 retains each clipped data therein, selects data generated prior to the corresponding data when data from a delay maximum data generation source is detected, and rearranges the selected data in order of time of generation thereof. A data storage buffer 74 stores the data rearranged in order of time of generation thereof. Analysis data determination means determines an analysis data group which is a set of data used for analysis, from the data stored in the data storage buffer 74.