Fujitsu Corporation

Yui Noma

Makiko Konoshima

Yoshifumi Ujibashi

A processor obtains an input dataset and an output dataset. The processor begins a search process that is a process of searching for a data conversion path of converting the input dataset via one or more intermediate datasets to the output dataset and that includes generating a plurality of intermediate datasets from the input dataset with different data conversion methods, filtering the plurality of intermediate datasets to select a next search intermediate dataset, and generating another intermediate dataset from the next search intermediate dataset. The processor outputs two or more intermediate datasets generated in the course of the search process and receives selection information indicating a selection of part of the two or more intermediate datasets. The processor controls the filtering method for selecting the next search intermediate dataset on the basis of the selection information.

Search control method and search control apparatus

In a search apparatus, a processing unit obtains input data and output data and stores these data in a storage unit. The processing unit classifies a plurality of data conversion methods into a plurality of groups. With respect to each group, the processing unit produces intermediate data from the input data using the data conversion methods belonging to the group, and evaluates the intermediate data using an evaluation function corresponding to the group, in order to thereby search for a combination of data conversion methods within the group. The processing unit determines a combination of data conversion methods that is able to convert the input data into the output data on the basis of the search results obtained for the plurality of groups.

Computer-readable recording medium storing search program and search method

A data conversion apparatus includes a memory and a processor coupled to the memory. The processor is configured to acquire first data. The processor is configured to acquire a part of second data corresponding to a part of the first data. The processor is configured to search for a combination of processes based on an attribute indicating a processing time for performing each process among processes for converting the part of the first data into the part of the second data. The combination of processes is used for converting a remainder of the first data into a remainder of the second data. The processor is configured to output the combination of processes.

Data conversion method and data conversion apparatus

A storage unit stores hyperplane information indicating a first hyperplane, and second and third hyperplanes parallel to the first hyperplane. A computing unit generates a first binary value based on whether the position of a first feature vector is in the direction of a normal vector relative to the second hyperplane, a second binary value based on whether the position of the first feature vector is in the direction of the normal vector relative to the third hyperplane, and a third binary value based on whether the position of a second feature vector is in the direction of the normal vector relative to the first hyperplane, and determines a degree of similarity between the pieces of comparison data, based on a result of multiplying the exclusive OR result of the first and third binary values and the exclusive OR result of the second and third binary values.

Information processing apparatus and data comparison method

A similarity search method that causes a computer to perform a process, the process includes: first calculating, based on a plurality of record data, each of the record data including a plurality of feature quantities, normal hyperplane data representing a normal hyperplane, the normal hyperplane being a hyperplane dividing a feature quantity space, and a distance between a pair of divided areas having symmetry, second calculating, based on the plurality of record data and the normal hyperplane data, one-way hyperplane data representing at least one one-way hyperplane, the one-way hyperplane being a hyperplane dividing the feature quantity space, and a distance between a pair of divided areas having asymmetry, and converting, based on the normal hyperplane data and the one-way hyperplane data, query data including a plurality of feature quantities and the plurality of record data into respective binary strings.

Information processing apparatus, similarity search program, and similarity search method

An information processing apparatus includes a memory and a processor coupled to the memory. The processor receives a compression request which designates data represented by a plurality of integers, and reduces entropy by multiplying a data matrix, which is obtained by representing the data designated by the compression request by a matrix, by a transformation matrix of which determinant is 1.

Information processing apparatus and information processing method

A learning method includes: randomly selecting one or more feature vectors from feature vectors for learning to form a sample set, by a processor; selecting, from the feature vectors for learning, one of feature vectors appended with a label different from a label appended to a feature vector included in the sample set as a reference vector, the selecting being carried out based on a generalized average of distance from a feature vector included in the sample set, by the processor; and learning a hyperplane that divides a feature vector space, the learning being carried out using a pair of one of feature vectors appended with a label different from a label appended to the reference vector, among the feature vectors for learning, and the selected reference vector, by the processor.

Learning method, information processing device, and recording medium

A data placement device creates a similarity index for each of computational resources based on a similarity between each of the pieces of acquired data and each of the pieces of data stored in the computational resources. The data placement device allocates on the basis of the similarity index of each of the computational resources with respect to the pieces of the data, the pieces of the data to each of the computational resources by using a matching system in which the similarity index associated with each allocation becomes stable in a direction in which the similarity index is small. The placement device places the pieces of the acquired data into the computational resources on the basis of the allocation result.

Computer-readable recording medium, data placement method, and data placement device

A data arrangement apparatus executes a process request on data stored in a database, calculates similarity of a process in a combination of the process request and the data, divides the data in such a manner as to distribute the similarity and processes a process request accepted for the divided data.

Non-transitory computer-readable recording medium, data arrangement method, and data arrangement apparatus

A classification method includes: setting a position of a projective point based on information on a domain of definition of a feature value space, using a processor; and projecting a vector present in the feature value space to a sphere present in a space of dimensions higher by at least one dimension than a dimension of the feature value space by using the set position of the projective point, using the processor.

Setting a projective point for projecting a vector to a higher dimensional sphere

An information processing apparatus stores first and second registered feature data respectively expressing first and second features of registered data, generates first and second subject feature data respectively expressing the first and second features of subject data, calculates a first degree of dissimilarity between the first registered feature data and the first subject feature data using a first computational process that exhibits symmetry so that a computational result does not change when two input values are interchanged, calculates a second degree of dissimilarity between the second registered feature data and the second subject feature data using a second computational process that exhibits antisymmetry so that a computational result changes when the two input values are interchanged, and selects the registered data based on the first and second degrees of dissimilarity.

Information processing apparatus and method of searching for similar data

A storage unit stores structure data that includes coordinates of vertices of a plurality of polygons representing a three-dimensional structure. A computation unit calculates coordinates of a certain point with reference to the structure data. This point is used, together with the vertices of the polygons, to produce a graph from the structure data according to spatial arrangement of the polygons and further to calculate characteristic quantities based on the produced graph. The computation unit stores the calculated coordinates of the point in a memory device, as a piece of information relating to the structure data.

Apparatus and method for managing structure data

An information processing method for a computer for data compression, the method includes: performing projective transformation of a first numeric string corresponding to an input signal into a second numeric string which contains more components than the first numeric string and having a sum of squares of components as a predetermined value by using a plurality of projective parameters; and generating a bit string in which bits indicating positive and negative signs of the respective components of an operation result obtained by a vector product operation of the second numeric string obtained by the projective transformation and an observation matrix are arranged.

Information processing device, information processing method, and information processing program for data compression

A search device according to an embodiment maps a feature vector onto a hyper-sphere on the basis of parameters which include an intersection and a distance, with the intersection at which an m-dimensional feature space and a straight line passing through the hyper-sphere present in a space greater in dimension than m intersect and the distance being from the north pole of the hyper-sphere to the feature space. In this case, the search device searches for the parameters which allow the positions of feature vectors mapped onto the hyper-sphere to be concentrated on a predetermined hemisphere of the hyper-sphere.

Search method, search program, and search device

A learning method includes: counting any one of or some of the number of labels added to each of feature amount vectors included in a learning data set, the number of types of the label, the number of feature amount vectors added with the same label, and the number of data pairs used for learning of a hyperplane, by a processor; first selecting, according to a result of the counting, one or more generation methods from a plurality of previously stored generation methods that generate the data pairs from the learning data set, by the processor; generating, using the selected generation methods, the data pairs from the feature amount vectors included in the learning data set, by the processor; and first learning, using the generated data pairs, the hyperplane that divides a feature amount vector space, by the processor.

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Kawasaki, Japan

Yui Noma