Fujitsu Corporation

Tatsuya Asai

Hiroya Inakoshi

Shinichiro Tago

Hiroaki Morikawa

Seishi Okamoto

Nobuhiro Yugami

Takashi Katoh

Junichi Shigezumi

Keisuke Goto

Kotaro Ohori

Masahiko Nagata

Masataka Matsuura

Akira Sato

Hiroaki Iwashita

Kento Uemura

Yusuke Koyanagi

Takahisa Ando

Satoko Shiga

Hiroki Arimura

Hiroya Hayashi

Yoshinobu Shiota

A non-transitory computer-readable recording medium stores an information processing program for causing a computer to execute processing including: generating, from first data in which values of a plurality of attributes included in each sample are accumulated for each sample, second data obtained by binarizing, for each sample, the values of the plurality of attributes included in each sample based on an attribute condition set in advance; enumerating, by using the second data, sets of attribute conditions in which all sample sets indicate true values; computing, for each set of attribute conditions, a correlation between the plurality of attributes in the first data in a sample set associated with each set of attribute conditions; and selecting a set of attribute conditions determined to have a correlation as a condition to be causally searched.

Computer-readable recording medium storing information processing program, information processing device, and information processing method

A non-transitory computer-readable recording medium stores therein a prediction program that causes a computer to execute a process including obtaining a machine learning model trained by using training data, the machine learning model predicting presence or absence of purchase actions or predetermined actions of users corresponding to feature information on the users, the training data including feature information on users and information indicating the presence or the absence of the purchase actions of commercial products or the predetermined actions, receiving input of a budget amount in an entry field displayed on a display in association with a user group including users including a common feature in the feature information, and displaying, in association with the budget amount on the display, feature information on the users included in the user group corresponding to the entry field.

Prediction method, prediction device, and computer-readable recording medium

A non-transitory computer-readable recording medium stores therein an extraction program that causes a computer to execute a process including: generating a plurality of combinations of conditions relating to a plurality of item values included in data; calculating an index value that indicates a degree of cooccurrence between a specified response variable and each of the plurality of combinations, by using a machine learning model that estimates a response variable from the plurality of item values, the machine learning model having been trained by using the data; and extracting a specific combination from among the plurality of combinations based on any one of the condition and the index value.

Extraction method, extraction device, and computer-readable recording medium

An apparatus decomposes a first binary tree pattern into combinations of multiple binary tree units in accordance with a predetermined procedure. When a second binary tree pattern configured as a combination of binary tree units that are among the multiple binary tree units and include a top binary tree unit of the multiple binary units is associated with a subset of a target binary tree data, the apparatus searches the target binary tree data for the first binary tree pattern by using positions of the subset within the target binary tree data.

Efficient discovery of a binary tree pattern from a large amount of binary tree data

A data processing method includes steps of; allowing establishment of a first flag or a second flag for each of a plurality of items where corresponding values are inputted sequentially; upon detecting that a value associated with an item where the first flag is established in an Nth place is inputted and that a value associated with an item where the second flag is established in an Mth place (M is equal to or larger than N) is inputted, executing a predetermined processing to values in a range from the value that is inputted by associating with the item where the first flag is established in the Nth place to the value that is inputted by associating with the item where the second flag is established in the Mth place; and executing a processing of outputting a processed result in order from the item in the Nth place.

Data processing method, apparatus and program for processing data identified in variable range

An apparatus acquires a first piece of trajectory information from among plural pieces of trajectory information, and acquires a first planar graph from among one or more planar graphs. The apparatus generates a second planar graph, based on the first planar graph and plural pieces of position information included in the first piece of trajectory information, and extracts, from among the plural pieces of trajectory information, second pieces of trajectory information indicating trajectories passing a difference portion between the first and second planar graphs. For each of candidate graphs each obtained by excluding a reduction set of edges from the second planar graph, the apparatus calculates optimality of the each candidate graph with which an addition set of trajectories indicated by the first and second pieces of trajectory information are associated, and outputs one of the candidate graphs determined based on the calculated optimality.

Apparatus and method for online generation of an optimum route-graph

A planar graph generation device that includes a processor that executes a process. The process includes: computing a specific value, including components of a value representing complexity of a track of the given track data, and a value representing a non-nearness between the given track data and each of all the other track data; selecting the track data with the smallest specific value among the collection; a first portion of the first track or a second portion of the second track positioned within the specific distance of each other, or a combination of the first portion and the second portion, is approximated to a specific portion such that a track of the addition target track data after addition passes through the specific portion in cases in which there are portions positioned within the specific distance of each other in a combination of the first track with the second track.

Planar graph generation device and method

A traffic flow rate calculation method includes, by using a road network produced by representing a road system with a plurality of nodes and a plurality of edges including a stationary sensor edge in which a stationary sensor measures the number of moving bodies; obtaining the first number of observations corresponding to the number of trajectories measured by mobile sensors for each path, the each path including the at least one edge, the each of trajectories corresponding to a movement trajectory of the moving body, and the second number of observations corresponding to the number of moving bodies measured by the stationary sensor; estimating an observation rate by using the first number of observations and the second number of observations; calculating a traffic flow rate for the each path by using the estimated observation rate and the first number of observations for each path.

Traffic flow rate calculation method and device

A data output method includes: generating, by a computer, (n&#x2212;1) first conditions (n is an integer number of three or more) on a relationship between two data by dividing, in a sequential order, a common element condition in which an attribute of each of n data includes a common element, the attribute of each of the two data including the common element; extracting first data corresponding to each of n data to set the first data as a node under a condition; creating a first graph in which nodes are coupled with links based on the first condition; creating a second graph by repeatedly performing a first process, a second process and a third process; determining candidates of a combination of data from the second graph; and outputting a combination of data satisfying the common element condition from the candidates of a combination of data.

Data output method, computer-readable recording medium storing data output program and data output system

A data output method, includes: extracting, by a computer, data satisfying a first condition on one data among a plurality of conditions, from a plurality of data, as a node; creating a first graph by coupling two nodes satisfying a second condition on a relationship between two data among the plurality of conditions with a link; creating a second graph by deleting a node that does not satisfy the second condition from the first graph; determining candidates of data combination in the second graph; and outputting a data combination satisfying the plurality of conditions from the candidates of data combination.

A route information processing apparatus includes: a processor configured to execute a program; and a memory configured to store the program, wherein, based on the program, the processor performs operations to: calculate maximum values corresponding to a Frechet distance between one line segment of one or more line segments between observation points included in a trajectory and each of sets of two nodes corresponding to the one line segment, the nodes being included in a route graph including linked paths which link nodes; and acquire a path corresponding to the trajectory having a smallest value among the maximum values of the one or more line segments.

Route information processing apparatus and route information processing method

An analysis method includes: acquiring first path information indicating a first movement path, first velocity information of a first moving body on the first movement path, second path information indicating a second movement path, and second velocity information of a second moving body on the second movement path; calculating, based on a specific rule, a similarity between the first velocity information and the second velocity information when the first path information and the second path information are extracted as candidates to be integrated; determining, based on the similarity, whether the first path information and second path information are to be integrated; and generating graph information to draw at least a part of the first path information and at least a part of the second path information as a single path when it is determined that the first path information and the second path information are to be integrated.

Analysis method and analyzing device

An information processing device includes a memory; and a processor that executes a program stored in the memory, wherein the processor executes an operation including: receiving first stream data and second stream data that each include a piece of reception data representing a set of a key and a numerical value, when detecting, from the second stream data, a piece of reception data with the same key as a key of a piece of reception data of the first stream data, obtaining a processing result by adding together numerical values of the pieces of reception data that have the same key, and storing the processing result in the memory.

Information processing device and information processing method

An observation information processing apparatus calculates, for each mesh, a support and a confidence. The observation information processing apparatus generates an adjacent mesh set by merging adjacent ones of the meshes. The observation information processing apparatus calculates, based on a support and a confidence of each mesh included in the adjacent mesh set, a confidence for each adjacent mesh, and sets the smallest one of the confidences calculated as a new confidence threshold value. The observation information processing apparatus detects and excludes meshes to be excluded from meshes included in the adjacent mesh set, based on the confidences and supports of the meshes included in the adjacent mesh set and the confidence threshold value.

Observation information processing apparatus, non-transitory computer-readable recording medium, and observation information processing method

A computer-readable storage medium storing an update program that causes a computer to execute a process includes: acquiring an automaton performing matching of data in an input stream hierarchized by tags to a keyword in a query, the automaton in which an initial state, a start state indicating a start tag symbol, an end state indicating an end tag symbol, a transition between the initial state and the start state, a transition between the initial state and the end state, and a transition from the initial state to the initial state are defined; generating a path identifying the position of a start tag based on a hierarchy in the input stream when the start tag is read from the input stream; judging whether or not the generated path meets a condition corresponding to the keyword in the query; generating, when the generated path is judged to meet a condition.

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Kawasaki, Japan

Tatsuya Asai