Abstract: A classification method executed by a computer for classifying a plurality of records into a plurality of groups, the classification method includes: acquiring the plurality of records, the plurality of records including a variable value respectively; tentatively classifying the plurality of records into the plurality of groups; calculating a commonality value indicating a degree of commonality of the variable value among the plurality of groups, based on the variable value included in each of the tentatively classified groups; classifying the plurality of records into the plurality of groups based on the commonality value; and outputting a result of the classifying.

Abstract: An information processing device including: a storage unit configured to store a first record set including variables of multiple types, and a second record set different from the first record set and including variables of the multiple types; and a processing unit configured to calculate an expected value at which a first variable set representing a combination of variables formed by selecting one variable for each type in the first record set is expected to appear in the second record set, extract the first variable set based on the expected value and the number of records including the first variable set in the second record set, and output at least one of the extracted first variable set and a second variable set, the second variable set representing a combination of variables formed by selecting one or more variables for each type in the second record set.

Abstract: A computing unit obtains a graph including nodes and edges and representing a communication condition at first timing and at second timing and detects an edge that is added between the first and second timing among the edges. The computing unit calculates probabilities of transmitting information from each node to nodes coupled to the added edge, selects a subset of the nodes based on the calculated probabilities, selects nodes included in the subset as the starting points of information, calculates first probabilities of transmitting information from the selected nodes to each node based on the graph obtained at the first timing and second probabilities of transmitting information from the selected nodes to each node based on the graph obtained at the second timing, and detects a change in the communication condition between the first and second timing by comparing the first probabilities with the second probabilities.

Abstract: 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.

Abstract: 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.

Abstract: When a second pattern is to be generated by adding an event to a first pattern including events, an extraction program causes a computer to execute the following process based on combinations of events. That is, the extraction program causes the computer to generate the second pattern when the number of occurrence, in the second pattern, of each of the events included in the combinations is not more than a threshold. The extraction program causes the computer to calculate, based on data including a plurality of events, a frequency at which one or more of the generated second patterns occur in the data. The extraction program causes the computer to extract the second pattern having the frequency satisfying a predetermined condition. The extraction program causes the computer to add a new event to the extracted second pattern.

Abstract: A classification method executed by a computer for classifying a plurality of records into a plurality of groups, the classification method includes: acquiring the plurality of records, the plurality of records including a variable value respectively; tentatively classifying the plurality of records into the plurality of groups; calculating a commonality value indicating a degree of commonality of the variable value among the plurality of groups, based on the variable value included in each of the tentatively classified groups; classifying the plurality of records into the plurality of groups based on the commonality value; and outputting a result of the classifying.

Abstract: A method for detecting an abnormal transition pattern from a transition pattern includes: first extracting an episode pattern with an appearance frequency greater than or equal to a first frequency from an episode pattern represented with a description form so as to include a first transition pattern and a second transition pattern differing in an order of a part of items from the first transition pattern to have a complementary relation thereto; second extracting a third transition pattern with an appearance frequency greater than or equal to a second frequency from the transition pattern; and specifying a transition pattern other than the third transition pattern from transition patterns included in the extracted episode pattern, and determining an abnormal transition pattern based on the transition pattern specified in the specifying when the third transition pattern includes a fourth transition pattern corresponding to the extracted episode pattern in the first extracting.

Abstract: According to one aspect, a computer-readable recording medium stores therein an extracting program 330a causing a computer to execute a process. The process includes based on event data obtained by associating a plurality of events stored in a storage unit and an occurrence time of each event, sequentially adding an event to a first pattern obtained by associating the plurality of events and the occurrence order of each event, and sequentially generating a second pattern which includes the first pattern and occurs in the event data; and extracting a pattern which satisfies a predetermined condition from the generated second pattern.

Abstract: An extraction program causes a computer to execute a process. The process includes adding an event to a first pattern including the events according to the sequential order, thus generating a second pattern in such a manner that the second pattern is generated by adding the event when a first value is less than a predetermined threshold; when the event is added, adding a predetermined value to the first value, and adding the predetermined value to a second value in a column corresponding to an end of the added event among second values corresponding to respective columns of a table; extracting the second pattern that satisfies a predetermined condition; and when an event in a second or subsequent column in the table is added.

Abstract: A data partitioning apparatus receives stream data and stores with previous-and-subsequent information that specifies data previous and subsequent to the data. Then, for groups, each of which contains the data that are stored and that are partitioned into the number of the groups, the data partitioning apparatus stores top information specifying data located at the top in a corresponding group and end information specifying data located at the end in the corresponding group. Then, when new data is stored, the data partitioning apparatus specifies data previous and subsequent to the new data and stores the new data by associating it with the previous-and-subsequent information that specifies the data previous and subsequent to the new data. Then, when data is inserted, the data partitioning apparatus updates information for each group such that the difference between the number of data belonging to each group is equal to or less than one.

Abstract: An apparatus includes a unit dividing a region into blocks having a predetermined bit length and generating addition data having the predetermined bit length corresponding to coordinate data, a unit storing storage data having the predetermined bit length, a unit generating composite data having a bit length twice the length of the predetermined bit length by connecting the addition data to the storage data, and storing the composite data, and a unit repeating an operation of designating the bit length of the composite data as the predetermined bit length, instructing to generate the addition data, and instructing to generate and store the composite data. The number of different bits between a bit string of a location corresponding to the input coordinate data and a bit string of a reference location tends to increase as a distance between the location corresponding to the coordinate data and the reference location increases.

Abstract: An information processing device including: a storage unit configured to store a first record set including variables of multiple types, and a second record set different from the first record set and including variables of the multiple types; and a processing unit configured to calculate an expected value at which a first variable set representing a combination of variables formed by selecting one variable for each type in the first record set is expected to appear in the second record set, extract the first variable set based on the expected value and the number of records including the first variable set in the second record set, and output at least one of the extracted first variable set and a second variable set, the second variable set representing a combination of variables formed by selecting one or more variables for each type in the second record set.

Abstract: An apparatus extracts an area having a highest score or a lowest score that is calculated based on evaluation values of points from a target area including a set of a plurality of points that can be distributed at two-dimensional coordinates. It determines whether the area extracted and an area overlapping a plurality of the target areas intersect with each other, and deletes an area having a lower score or a higher score out of the areas determined to intersect with each other. It selects an area having a highest score or a lowest score out of the areas extracted at the extracting and not deleted at the determining. One or a plurality of areas are generated as the target areas based on an area acquired by excluding the area selected from the target area and an area acquired by excluding the area deleted at the determining.

Abstract: A matching device builds a parse tree from an event pattern. The matching device builds an automaton by, while traversing the parse tree, joining child nodes of an AND node in parallel to the AND node and joining child nodes of an OR node in parallel to the OR node. The matching device performs matching of determining whether an event stream includes the event pattern by comparing the event stream with the automaton.

Abstract: A computing unit obtains a graph including nodes and edges and representing a communication condition at first timing and at second timing and detects an edge that is added between the first and second timing among the edges. The computing unit calculates probabilities of transmitting information from each node to nodes coupled to the added edge, selects a subset of the nodes based on the calculated probabilities, selects nodes included in the subset as the starting points of information, calculates first probabilities of transmitting information from the selected nodes to each node based on the graph obtained at the first timing and second probabilities of transmitting information from the selected nodes to each node based on the graph obtained at the second timing, and detects a change in the communication condition between the first and second timing by comparing the first probabilities with the second probabilities.

Abstract: A trajectory interpolation apparatus is disclosed. The first storage part stores first time and first location information of a movable body at the first time. The second storage stores second time and second location information of the movable body at the second time. The calculation part calculates a first moving distance from the first time and a second moving distance from the second time based on a relationship between the time and the speed stored in the second storage part, regarding third time between the first time and the second time. The determination part determines, as the interpolation point, one of intersection points for a circle in which the first location is set as its center and the first moving distance is set as its radius, and another circle in which the second location is set as its center and the second moving distance is set as its radius.

Abstract: 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.

Abstract: The matching apparatus 100 stores, with respect to a branching pattern included in event patterns 140a, a reception time of an event that serves as the branching point in a source node that indicates the transition destination of the event, connects the source node to the branch node by a transition with an interval condition, connects the branch nodes to the link node that indicates the linking point at which these branch nodes are linked together, and thereby generates NFAs 140b. Then, the matching apparatus 100 compares event streams 140c with the NFAs 140b to determine whether the event streams 140c includes the event patterns 140a.

Abstract: An extraction program causes a computer to execute a process. The process includes adding an event to a first pattern including the events according to the sequential order, thus generating a second pattern in such a manner that the second pattern is generated by adding the event when a first value is less than a predetermined threshold; when the event is added, adding a predetermined value to the first value, and adding the predetermined value to a second value in a column corresponding to an end of the added event among second values corresponding to respective columns of a table; extracting the second pattern that satisfies a predetermined condition; and when an event in a second or subsequent column in the table is added.