Abstract: A matrix calculation system for calculating funny matrix multiplication (FMM) of a matrix A and a matrix B, including: sequentially calculating a permutation of indices {ai} in which values are arranged in a non-decreasing order with respect to each i-th row where i=1 to the number of rows of the matrix A; storing a value, which is greater than expected as a value of a matrix, for C[i, j] with respect to each j-th column where j=1 to the number of columns of the matrix A in the i-th row; sequentially calculating a permutation of indices {bj} in which values are arranged in a non-decreasing order with respect to each j-th column where j=1 to the number of columns of the matrix B; and setting the values of C[i, j], which are i and j components of the matrix C.

Abstract: Methods and systems for searching a path for a vertex include iteratively removing from consideration points in a path, until a number of remaining points is below a path size threshold. The iterative removal includes determining, for each of two endpoints in a path, a lower bound for a shortest path distance from each respective endpoint to a target vertex and removing from consideration points closer to each respective endpoint than the respective lower bound to produce a shortened path. The shortened path is searched with a processor to determine whether the vertex is in the shortened path.

Abstract: Methods and systems for searching a path for a vertex include determining, for each of two endpoints in a path, a lower bound for a shortest path distance from each respective endpoint to a target vertex; determining whether the lower bounds cover all points in the path and, if so, determining that the vertex is not in the path; determining whether a number of uncovered points is below a path size threshold and, if so, performing a search of the uncovered points to determine whether the vertex is in the path; and if the number of uncovered points is above the path size threshold, repeating the steps of determining a lower bound, determining whether the lower bounds cover all points, and determining whether a number of points is below a path size threshold using the uncovered points as a new path.

Abstract: Routing information processing method, computer program, and system. A method for processing routes in a graph, the method including coloring vertices in the graph in such a manner that a condition NP>NC is satisfied, wherein a number of vertices in the graph is represented by NP and a number of colors assigned to the vertices is represented by NC, and wherein a series of colors assigned to the vertices is identified uniquely, the series of colors representing a series of vertices corresponding to each of the routes; and storing a series of vertices corresponding to a route as a series of colors assigned to the vertices into the storing means.

Abstract: Methods and systems for searching a path for a vertex include determining, for each of two endpoints in a path, a lower bound for a shortest path distance from each respective endpoint to a target vertex; determining whether the lower bounds cover all points in the path and, if so, determining that the vertex is not in the path; determining whether a number of uncovered points is below a path size threshold and, if so, performing a search of the uncovered points to determine whether the vertex is in the path; and if the number of uncovered points is above the path size threshold, repeating the steps of determining a lower bound, determining whether the lower bounds cover all points, and determining whether a number of points is below a path size threshold using the uncovered points as a new path.

Abstract: Methods and systems for resource segmentation include dividing a time horizon to be partitioned into time slots based on a minimum partition size; determining resource usage for multiple virtual machines in each of the plurality of time slots; determining a set of partitioning schemes that includes every possible partitioning of the time slots into a fixed number of partitions; for each partitioning scheme in the set of partitioning schemes, determining a cost using a processor based on a duration of each partition and a resource usage metric; and selecting a partitioning scheme that has a lowest cost.

Abstract: A mechanism is provided for enabling prediction of a cost between an origin and a destination even in the case of insufficient past route information. Data D, which includes an origin, a destination, and information on cost between these points, is prepared as well as a subroutine for calculating cost ce along an arbitrary link e on the basis of the set along with a variable denoted by fe. In the first step, the minimum cost route is found from the current {fe} with respect to all pairs of the origin and the destination included in the data D, thereby forming transformed data D?. {fe} is recalculated by using the above subroutine from D? by computer processing and then compared with {fe} calculated last time. If a change is equal to or greater than a threshold, control returns to finding the minimum cost route. Otherwise, {fe} is fixed.

Abstract: A method for searching transition routes from an initial state of a plurality of stackable items to a target state by a computer at predetermined conditions includes connecting between transitionable states at an edge by a single handling operation transitioning from the initial state to the target state, to generate a state space graph; evaluating a lower bound of handling operation cost from a certain state to the target state, based on both the stacking sequence of the plurality of items in the certain state and the stacking sequence of the plurality of items in the target state; and searching a route from the initial state to the target state where the handling operation cost is minimal on the state space graph using a heuristic search algorithm based on the lower bound.

Abstract: A method for searching transition routes from an initial state of a plurality of stackable items to a target state by a computer at predetermined conditions includes connecting between transitionable states at an edge by a single handling operation transitioning from the initial state to the target state, to generate a state space graph; evaluating a lower bound of handling operation cost from a certain state to the target state, based on both the stacking sequence of the plurality of items in the certain state and the stacking sequence of the plurality of items in the target state; and searching a route from the initial state to the target state where the handling operation cost is minimal on the state space graph using a heuristic search algorithm based on the lower bound.

Abstract: A method includes hierarchically identifying occurrences of some of the words in the set of sentences; creating a first index for each of some of the words based on the upper hierarchy of occurrences identified for each word; receiving input of a queried word; hierarchically identifying occurrences of the queried word in the set of sentences; creating a second index based on the upper hierarchy of occurrences identified for the queried word; comparing the first index and the second index to calculate an estimated value for the number of occurrences of a word in the neighborhood of the queried word; and calculating the actual value of the number of occurrences of a word in the neighborhood of the queried word based on an upper hierarchy and lower hierarchy of the occurrences on condition that the estimated value is equal to or greater than a predetermined number.

Abstract: A method includes hierarchically identifying occurrences of some of the words in the set of sentences; creating a first index for each of some of the words based on the upper hierarchy of occurrences identified for each word; receiving input of a queried word; hierarchically identifying occurrences of the queried word in the set of sentences; creating a second index based on the upper hierarchy of occurrences identified for the queried word; comparing the first index and the second index to calculate an estimated value for the number of occurrences of a word in the neighborhood of the queried word; and calculating the actual value of the number of occurrences of a word in the neighborhood of the queried word based on an upper hierarchy and lower hierarchy of the occurrences on condition that the estimated value is equal to or greater than a predetermined number.

Abstract: A method of meeting a power demand of a power consumption unit is disclosed. A forecasted power demand for a power demand scenario for the power consumption unit is determined and a probability of occurrence of the power demand scenario is determined. An objective function for operating at least one power supply device is created that includes the forecasted power demand of the power demand scenario and the determined probability of occurrence of the power demand scenario. A substantial minimum of the objective function is located to determine a schedule for operating the at least one power supply device to meet the forecasted power demand. The at least one power supply device may be operated according to the determined schedule to meet the power demand of the power consumption unit.

Abstract: A method of meeting a power demand of a power consumption unit is disclosed. A forecasted power demand for a power demand scenario for the power consumption unit is determined and a probability of occurrence of the power demand scenario is determined. An objective function for operating at least one power supply device is created that includes the forecasted power demand of the power demand scenario and the determined probability of occurrence of the power demand scenario. A substantial minimum of the objective function is located to determine a schedule for operating the at least one power supply device to meet the forecasted power demand. The at least one power supply device may be operated according to the determined schedule to meet the power demand of the power consumption unit.

Abstract: A mechanism is provided for enabling prediction of a cost between an origin and a destination even in the case of insufficient past route information. Data D, which includes an origin, a destination, and information on cost between these points, is prepared as well as a subroutine for calculating cost ce along an arbitrary link e on the basis of the set along with a variable denoted by fe. In the first step, the minimum cost route is found from the current {fe} with respect to all pairs of the origin and the destination included in the data D, thereby forming transformed data D?. {fe} is recalculated by using the above subroutine from D? by computer processing and then compared with {fe} calculated last time. If a change is equal to or greater than a threshold, control returns to finding the minimum cost route. Otherwise, {fe} is fixed.

Abstract: An apparatus and method for solving mathematical programming problems. The apparatus includes a first-time-point-solution generating unit generating at least one solution to a mathematical programming problem, a second-time-point-problem generating unit generating a plurality of mathematical programming problems to be on the basis of the solution to the mathematical programming problem to be solved at the first time point, a second-time-point optimum value calculating unit calculating an optimum value of each of a plurality of mathematical programming problems to be solved at the second time point, a relational expression estimating unit estimating a relational expression between the solution to the mathematical programming problem to be solved at the first time point and an optimum value of a mathematical programming problem to be solved at the second time point, and a correcting unit correcting the mathematical programming problem at the first time point based on the relational expression.

Abstract: A method and system for solving shortest paths from multiple sources to multiple destinations faster. A method of solving the multiple-pairs shortest path problem is provided using processing by a computer having storage means. The method includes the steps of: (A) reading graph data S on multiple vertices as search starting points from a storage area of the computer; (B) reading graph data T on multiple vertices as search targets from the storage area of the computer; (C) selecting k vertices s1, s2, . . . , sk from the graph data S; (D) deleting the k vertices from the graph data S; (E) finding and storing, in the storage area, shortest path lengths from each of the selected k vertices to the graph data T; and (F) repeating the steps from (C) to (E) until the graph data S becomes empty.

Abstract: A matrix calculation system for calculating funny matrix multiplication (FMM) of a matrix A and a matrix B, including: sequentially calculating a permutation of indices {ai} in which values are arranged in a non-decreasing order with respect to each i-th row where i=1 to the number of rows of the matrix A; storing a value, which is greater than expected as a value of a matrix, for C[i, j] with respect to each j-th column where j=1 to the number of columns of the matrix A in the i-th row; sequentially calculating a permutation of indices {bj} in which values are arranged in a non-decreasing order with respect to each j-th column where j=1 to the number of columns of the matrix B; and setting the values of C[i, j], which are i and j components of the matrix C.

Abstract: A mechanism is provided for enabling prediction of a cost between an origin and a destination even in the case of insufficient past route information. Data D, which includes an origin, a destination, and information on cost between these points, is prepared as well as a subroutine for calculating cost ce along an arbitrary link e on the basis of the set along with a variable denoted by fe. In the first step, the minimum cost route is found from the current {fe} with respect to all pairs of the origin and the destination included in the data D, thereby forming transformed data D?. {fe} is recalculated by using the above subroutine from D? by computer processing and then compared with {fe} calculated last time. If a change is equal to or greater than a threshold, control returns to finding the minimum cost route. Otherwise, {fe} is fixed.

Abstract: A mechanism is provided for enabling prediction of a cost between an origin and a destination even in the case of insufficient past route information. Data D, which includes an origin, a destination, and information on cost between these points, is prepared as well as a subroutine for calculating cost ce along an arbitrary link e on the basis of the set along with a variable denoted by fe. In the first step, the minimum cost route is found from the current {fe} with respect to all pairs of the origin and the destination included in the data D, thereby forming transformed data D?. {fe} is recalculated by using the above subroutine from D? by computer processing and then compared with {fe} calculated last time. If a change is equal to or greater than a threshold, control returns to finding the minimum cost route. Otherwise, {fe} is fixed.

Abstract: An information processor and method for classifying user attributes of a plurality of nodes connected to a network. The information processor includes: an action history obtaining unit for generating a spammer-reporting action history set; a related node obtaining unit for generating a node set and a link set related to the spammer-reporting actions; an undirected graph generation unit for generating an undirected graph from the node set and the link set; and a max-cut computation unit classifying the nodes constituting the undirected graph into two exclusive sets that do not commonly include any element so as to maximize an indicator value defined by links bridging the two sets.