Abstract: A work content analyzing apparatus of the present embodiment includes a first database storing state information indicating a state of each of one or a plurality of workers in association with time information and identification information of the worker, an estimation unit estimating the work content executed by the worker on the basis of at least two pieces of state information associated with same time in the state information stored in the first database, a specification unit specifying work time spent for the estimated work content on the basis of the state information stored in the first database and the time information associated with the state information, and an analysis unit analyzing the work content on the basis of the estimated work content and the specified work time.

Abstract: An information processing system as an embodiment of the present invention includes: a first computer that generates an edge group that is a group of edges connected to corresponding nodes for each of the nodes in a graph of a Hamiltonian path problem, a binary variable indicating whether the edges included in the edge group are selected as a path for each of edge groups, and an Ising model with the binary variable as a spin; and a second computer that calculates a solution of the Ising model. The first computer acquires a solution of the Hamiltonian path problem based on the solution of the Ising model calculated by the second computer.

Abstract: A classification system according to an embodiment includes a score calculation unit, a determination unit, and a classification unit. The score calculation unit calculates respective scores of predetermined classes from input data. The determination unit determines whether the input data belongs to anyone of the classes based on the respective scores of the classes, which are calculated by the score calculation unit. The classification unit determines which one of the classes the input data belongs to, based on the calculated scores when the determination unit determines that the input data belongs to anyone of the classes and determines that the input data belongs to an unknown class that is other than the classes when the determination unit determines that the input data does not belong the classes.

Abstract: An information presentation device includes a plot unit, a histogram generation unit, and a visual information generation unit. The plot unit plots a plurality of values included in each of a plurality of pieces of multidimensional data on a plurality of axes in a parallel coordinate plot coordinate system. The histogram generation unit divides each of the plurality of axes into a plurality of sections, and generates a plurality of histogram bars each of which corresponds to the number of values plotted in each section in the plurality of sections. When one or more values are selected as selected values, the visual information generation unit generates visual information with which the ratio of the number of selected values to the total number of values contained in any one histogram bar out of the respective histogram bars generated by the histogram generation unit can be identified.

Abstract: According to one embodiment, a processor calculates values of variables in each step of a repetitive calculation using values of the variables calculated in a previous step, and determines whether a difference between the values of the variables calculated in each step and a particular value is larger than a first value. The processor corrects a value of the variables calculated in the previous step to be close to the particular value and calculates a value of the variables in the current step using a corrected value of the variables if the difference is larger than the first value.

Abstract: According to one embodiment, an image-processing apparatus includes an output unit, a tracker, a storage controller, a setter, and an output controller. The tracker tracks a target object in one or more time-series images. The storage controller stores tracking information including a movement trajectory of the object in a predetermined storage. The setter sets a detection region for detecting passing through of the object based on the movement trajectory of the object, on the image, in accordance with a user's operation. An evaluator evaluates a setting mode for the detection region based on the tracking information stored in the predetermined storage and the detection region set by the setter. The output controller outputs the tracking information stored in predetermined storage, from the output unit, in an output mode based on an evaluation result of the evaluator.

Abstract: A communication device according to an embodiment includes an interpreter, a storage, and a generator. The interpreter is configured to interpret a content of a message addressed to a target user. The storage stores information on a personal feature of the target user. The generator is configured to generate a response message simulating a response by the target user on the basis of the content of the message addressed to the target user, which is interpreted by the interpreter, and the information on the personal feature of the target user stored in the storage.

Abstract: A conversation analysis system according to the present embodiment utilizes a computer and includes an input unit, a conversation analysis model unit and an information processing unit. The input unit inputs conversational data of utterers who execute a work in cooperation. The conversation analysis model unit analyzes contents of conversations related to work cooperation made by a plurality of utterers based on the conversational data input by the input unit, using a conversation analysis model created by machine learning. The information processing unit creates a plurality of types of evaluation information related to work cooperation based on a conversation analysis result obtained by the conversation analysis model unit.

Abstract: An information processing device according to an embodiment includes a determination unit and a first training unit. The determination unit determines whether an unlabeled data point whose class label is unknown is a non-targeted data point that is not targeted for pattern recognition. The first training unit trains a first classifier for use in the pattern recognition through semi-supervised learning using a first training dataset including unlabeled data determined not to be the non-targeted data and not including unlabeled data determined to be the non-targeted data.

Abstract: According to one embodiment, an information processing system includes an acquisition unit, an environment setting unit, a model processing unit, a management unit, an interface unit, and a control unit. The acquisition unit acquires design information and target data of machine learning. The environment setting unit sets a framework environment and library information executing the design information, and sets a software configuration supporting execution of the machine learning. The model processing unit generates or updates a model by executing learning for the target data using the design information and framework environment. The management unit manages design information, information about the framework environment and information about the model. The interface providing unit receives, from a user, an output instruction for the environment setting information, and presents, to the user, setting information or the like being recommended.

Abstract: According to one embodiment, a train operation planning support system displays a timetable of a train in which a first required time and a first buffer time are placed for running time of the train and a second required time and a second buffer time are placed for dwell time of the train. The first required time is time required for a train running between a departure station and an arrival station. The first buffer time is buffer time obtained by subtracting the first required time from running time of the train set as a target value. The second required time is time required for the train stopping at the arrival station. The second buffer time is buffer time obtained by subtracting the second required time from dwell time of the train which is set as a target value.

Abstract: According to one embodiment, a moving block signaling headway calculation system recursively executes a process until an interval reaches a limit value. The process includes calculating headway values for a plurality of points on the running section for each interval, extracting a section between adjacent two points, in which an amount of variation in the headway values between the adjacent two points exceeds a threshold value, a section between two points before and after a front point and an end point of a point or a section where a headway value changes from rise to fall, or a section between two points before and after a front point and an end point of a point or a section where a headway value changes from fall to rise, and subdividing the interval in the extracted sections.

Abstract: An image processing apparatus according to an embodiment includes a processor. The processor acquires a classification result of classifying each of a plurality of regions set in a processing target image into one of a plurality of predetermined classes. The processor converts multidimensional data corresponding to each of the plurality of regions set in the image into low-dimensional data. The processor causes a display image including one or more regions to be displayed together with a plotted diagram including a plurality of plot points having different colors or patterns applied according to the classification result to the low-dimensional data in each of the plurality of regions, and in a case where an instruction for selecting a selected point from among the plot points is issued, the processor performs a discriminative display causing the selected point and a region corresponding to the selected point in the display image to be visually identifiable.

Abstract: A product state estimation device includes: an examination result acquisition device that acquires an examination result related to a state of a product obtained through each shot by a die-casting machine; a time series data acquisition device that acquires time series data based on an output from a sensor that detects an operation state of the die-casting machine at each shot; a time series data manipulation device that performs manipulation that clips data of a predetermined time interval out of the time series data; an estimation model generation device that generates an estimation model by using a neural network with the examination result of the product and the manipulated time series data as learning data; and an estimation device that estimates information related to quality of the product based on the manipulated time series data obtained from a plurality of detection signals at each shot by using the estimation model.

Abstract: An information processing device includes an association information acquiring unit, a first position information acquiring unit, and an output control unit. The association information acquiring unit acquires association information in which first identification information used for identifying baggage and second identification information used for identifying an owner of baggage identified by the first identification information are associated with each other. The first position information acquiring unit acquires position information of target baggage that is baggage identified by the first identification information included in the association information. The output control unit causes a mobile terminal held by a target owner who is an owner of the baggage identified by the second identification information associated with the first identification information relating to the target baggage in the association information to output information based on the position information of the target baggage.

Abstract: According to an embodiment, an information processing apparatus includes an extraction unit and a generation unit. The extraction unit is configured to use a learning model that extracts a combining region from a subject image to extract the combining region from a first subject image of a first subject. The generation unit is configured to generate a combined image obtained by combining the extracted combining region with a target region of a corrected image in which transparency of the target region in a second subject image of a second subject has been corrected to a threshold or more.

Abstract: In general, according to one embodiment, a named-entity extraction apparatus according to an embodiment includes: an unit extracting, using an extraction dictionary, named entities and relations from extraction document data; a unit designating character strings corresponding to the named entities extracted among character strings in learning document data; a generator generating, by applying a relation extraction rule, a learning document in which relations between named entities belonging to the categories of the relation extraction rule among the named entities designated; and a unit learning the extraction dictionary based on the learning document.

Abstract: An episode management device includes: an episode acquisition part that acquires an episode input, in form of text, by a registering user; an episode management part that manages the acquired episode; a registered tag extraction part that extracts a registered tag which is meta information of the episode based on the acquired episode; a registered tag management part that manages the extracted tag as tag information associated with the managed episode; a condition acquisition part that acquires, as condition information, a condition input by a searching user; a search tag extraction part that extracts a search tag from the condition information; a registered tag presentation part that user-selectably presents, to the searching user, the registered tag having high similarity to the search tag; and an episode presentation part that presents, to the searching user, the episode having high similarity to the registered tag selected by the searching user.

Abstract: An information processing device, an information processing method, and a program capable of rejecting only a part of a series in a recognition process performed in units of series are provided. An information processing device includes a rejection class adding unit, a label sequence selecting unit, and an output unit. The rejection class adding unit adds a rejection class by acquiring a categorical distribution sequence formed by aligning a plurality of categorical distributions having scores for each class and acquiring a score of a rejection class on the basis of the categorical distribution for each of the categorical distributions included in the categorical distribution sequence.

Abstract: According to one embodiment, an information processing device includes a first storage and a first processing circuit. The first storage is configured to store constraint data which includes a constraint of a combinatorial optimization problem expressed in a formal language. The first processing circuit is configured to generate logical expression data from the constraint data and generate a penalty term data including a penalty term having a binary variable parameter by converting the logical expression data.