35 results about "Multidimensional index" patented technology

A computer-based technique is provided for retrieving one or more items from a database in response to a query specified by a user via one or more example sets. Preferably the example sets include multiple positive and negative example sets. The method comprises the following steps. First, a scoring function is constructed from the one or more example sets. The scoring function gives higher scores to database items that are more closely related to the query than to database items that are not as closely related to the query. The scoring function is operable for use with a multidimensional indexing structure associated with the database. Then, the one or more database items that have the highest score as computed using the scoring function are retrieved via the multidimensional indexing structure.

Disclosed herein is a dynamic update cube and hybrid query search method for range-sum queries. The present invention relates to a hybrid query search method, which provides a precise answer or an approximate answer with respect to On-Line Analytic Processing (OLAP) queries by using a delta (.DELTA.)-tree, which has a multidimensional index structure and a prefix-sum cube, so as to effectively support range-sum queries widely used in opinion decisions in enterprises. In the dynamic update cube and hybrid query search method for range-sum queries, a prefixed-sum cube is dense and the dynamic update cube is sparse, such that whenever a data cube changes, the prefixed sum cube is not directly updated and instead, the changes of the data cube are stored in a .DELTA.-Tree and the .DELTA.-Tree is managed.

The present invention builds Home Data Index (HDI) models. One driving force behind this HDI initiative is that no one model or measure can truly capture the widely dynamic movement of home prices. Even within a small geographical area, such as a ZIP code, there is significant variation in property sale types, sale frequencies and sale values. To better describe these variations, the present invention presents a suite of paired sales and price per square foot index models built around an array of property transaction characteristics. These HDI models expand on the usage and understanding of traditional home price indices (HPIs) by implementing a multidimensional index comprised of four main dimensions: geography; time frames; value range; and property sales type. Several layers exist within each dimension, allowing for more than 300 different index model perspectives for a given property address. For each permutation among the layers of the four main dimensions, a model is constructed with an associated confidence score that reflects the statistical relevance of each estimate.

The invention discloses a method for evaluating the innovation degree of text information. The method for evaluating the innovation degree of the text information comprises the steps of performing word segmenting pre-processing on acquired text data, and training an LDA model by using preprocessed data to realize an industry-themed classification for distinguishing texts in different industries so as to enable a trained model to contain model files of keywords of each industry category; establishing a knowledge network composed of key knowledge and technical information extracted from the preprocessed data according to a time sequence, and continuously updating the knowledge network at regular time intervals; utilizing the preprocessed data sorted according to the time sequence to extract attribute information of each piece of literature, establishing a literature text structure network, and determining an innovation type of each piece of literature; using the trained LDA model to analyze which industry technology keywords or knowledge keywords in patent data belong to respectively, and combining the attribute information of the literature text structure network so as to constitute multidimensional indexes for the innovation degree evaluation.

The invention discloses a power consumer segmentation method based on multidimensional indexes; aiming at power consumers, the method creatively proposes 6 evaluation indexes under three dimensions including the client value, the client credit and the client potential, wherein the 6 evaluation indexes refer to the power consumption, the average electricity price, the default power consumption frequency, the arrearage rate, the power consumption growth rate and the install capacity; the method preprocesses the data, and uses a cluster algorithm to evaluate to obtain the optimal segment result according to an average contour coefficient. The power consumer segmentation method based on multidimensional indexes is good in segmentation effect, thus preventing troubles caused by a conventional client segmentation method developing variation marketing services for the power grid.

The embodiment of the invention discloses a method and a device for indexing data. According to the method and the device for indexing data provided by the embodiment of the invention, N unidimensional indexes are obtained according to N dimensions, wherein the N unidimensional indexes are corresponding to the N dimensions and are independent of each other, and whether address records of the N independent unidimensional indexes have intersection is judged, so that data oriented by the address records corresponding to the intersection are obtained as index target data. According to the method and the device for indexing data, the problem that the unidimensional indexing technology can not meet the requirements on combination query and multidimensional analysis of multidimensional indexes is solved, and the count values of the label number of flag bits corresponding to the address records of the N unidimensional indexes are determined, so that the requirements on speed of multidimensional analysis are easily and conveniently satisfied, the indexing complexity is reduced, and the performance for accurately indexing data is improved.

The invention discloses a projection pursuit dynamic cluster method for a multidimensional index based on particle swarm optimization, which effectively combines the advantages of APH, the projection pursuit, the particle swarm optimization and the like, and provides a new projection pursuit dynamic cluster method for the multidimensional index based on the particle swarm optimization. The new method effectively avoids the problems that the subjectivity of the AHP is too strong and the ordinary projection pursuit neglects index weight. Through the application of the method, cluster evaluations of high-capacity and high-dimensionality multidimensional index data of business can be realized, therefore, the method has high practical value.

Enlargement values indicating a degree of enlargement when spatial data is stored in a partial spatial region are calculated for one or more partial spatial regions within a multidimensional index, and in the case where the enlargement value is greater than or equal to a threshold value, a new partial spatial region that contains at least the spatial data is generated.

The invention discloses a data processing method and device for generating multi-dimensional index data, which comprises the following steps: receiving an application request of the multi-dimensionalindex data; determining the indicator and dimension relationship of a plurality of dimensions of the applied multidimensional indicator data and an indicator from a preset indicator dimension relationship table; sorting multiple dimensions of the applied multi-dimensional indicator data according to the preset collation rules; determining a multi-dimensional indicator priority order according tothe sorting results of the multi-dimensional indicator data applied, and generating a multi-dimensional indicator table; associating dimension attributes of the applied multi-dimensional indicator data with the multi-dimensional indicator table to obtain a combination of dimensions, dimension attributes and indicators of the applied multi-dimensional indicator data; obtaining the corresponding multi-dimensional indicator data from the data warehouse according to the applied combination of multiple dimensions and indicators and writing the same into the multi-dimensional indicator table. The invention makes the index generated in the way of periodic table number, which is beneficial to the statistics and analysis of the multi-dimensional index.

A method for indexing semantic, non-transitory, computer-stored data comprising the following steps: storing the data in a database; representing the data in a structured framework having at least three elements derived from an ontology; expressing each element as a hierarchical-index value based on an ontology such that semantic information is embedded therein; combining the elements in a multi-dimensional index; and converting the multi-dimensional index into a one-dimensional index.

A system for separating documents is disclosed. The system includes a multidimensional index creating module and a document separation criterion calculating module. The multidimensional index creating module calculates a multidimensional index for each documental material by calculating a plurality of document characteristic indexes from content information about individual documental materials contained in a primary document search result obtained in response to a search query received from a user device. The document separation criterion calculating module calculates a document separation criterion on the basis of both user preference information regarding at least one specific documental material selected from the documental materials contained in the primary document search result and the multidimensional index for the selected specific documental material. A secondary document search result is selected and provided according to the calculated document separation criterion among the documental materials contained in the primary document search result.

The invention discloses a spare unit and part prediction method of electric energy meters based on state maintenance of the electric energy meters. The method comprises the following steps that (1) multidimensional indexes of the electric energy meters are analyzed, a colinearity problem is solved in a gradual regression analysis method, an obtained main variable is weighted and scored via a statistical average method, a calculation formula of the unhealthy degree is reduced by one dimension, and the batch of electric energy meters whose unhealthy degree is high is replaced; (2) a gradient tree improving algorithm model is used to predict the unhealthy degree of the electric energy meters which do not have serious problems, and the batch of electric energy meters which tend to have serious problems is obtained and replaced; and (3) an Arima time sequence algorithm is used to predict the quantity of newly added users locally in each year. According to the invention, manufacturers and batches serve as analysis objects, an electric energy meter health degree evaluation model, an electric energy meter health degree prediction model and an electric energy meter newly added user quantity prediction model are established, and thus, spare units and parts of the electric energy meters are predicted and analyzed.

The invention discloses a mass spatio-temporal data visualization performance optimization method and system based on multi-dimensional indexes, and the method comprises the steps: mastering the data characteristics and data formats of spatio-temporal data, carrying out the organization and management of the spatio-temporal data according to an application scene, and carrying out the optimization of the visualization performance of the spatio-temporal data. According to the method, a KD-Tree and histogram fused KD-H technology is provided, query performance is optimized for non-aggregation query and aggregation query, after spatio-temporal data is organized and managed, a multi-dimensional index and a histogram are constructed, and after proper KD-Tree and histograms are constructed for different application scenes, the query performance is optimized. A public map geographic space visualization map is used as a base map, on a high-performance WebGL rendering framework based on big data visualization, the incremental visualization technology is used for optimizing the performance of large-scale spatio-temporal data visualization, visualization details are increased or updated through incremental visualization, visualization of a large-scale data set is completed step by step, and the visualization efficiency of the large-scale data set is improved. According to the method, the large-scale spatio-temporal data visualization performance is optimized, the loading time is shortened, and the user experience is enhanced.

The invention discloses a data analysis method and device for offshore wind power business and a storage medium. The method comprises the following steps: dividing data analysis operation for an offshore wind power service into more than two analysis stages based on the life cycle of the offshore wind power service; constructing a multi-dimensional index parameter for data analysis according to the target feature of each analysis stage corresponding to each analysis stage; establishing a stage analysis model based on the analysis stage and the multidimensional index parameters corresponding tothe analysis stage; obtaining current stage data corresponding to the multi-dimensional index parameters in each analysis stage, and inputting the current stage data into a stage analysis model; andanalyzing the current stage data by using the stage analysis model, and outputting the current stage decision data. Therefore, the data analysis of the embodiment of the invention not only has pertinence, but also can improve the efficiency and precision of the data analysis of the offshore wind power.

The invention discloses an implementing method for a multidimensional index structure OBF-Index in a Hadoop environment. The implementing method for the multidimensional index structure OBF-Index in the Hadoop environment comprises the following steps: dividing a data set to obtain data fragments, establishing an OBF index object for each data fragment, serializing the OBF index objects into OBF index files and storing the OBF index files, and constructing to obtain OBF-Index; when the data set requires to be used, setting a data set A which requires to be used at first, then separately reading the OBF index files of each data fragment and serializing the OBF index files to obtain OBF index objects, querying whether data in the data set A exist in the data fragments or not by using the OBFindex objects, if the data in the data set A exist in the data fragments, transmitting the data fragments to corresponding Mapper, and if the data in the data set A do not exist in the data fragments, not operating. The invention designs a multi-dimensional index structure OBF-Index, establishment and query can be realized effectively, and false positive probability can be reduced effectively.

The invention discloses a multi-dimensional query method of satellite remote sensing data on a heterogeneous computing platform. The method comprises the following steps: carrying out data distribution on a remote sensing satellite multi-dimensional data set; optimizing a multi-dimensional index structure, standardizing original main keys, replacing the original main keys with continuous numericalvalue main keys, shielding semantic information of the main keys in the original dimensional data, updating foreign keys on an original fact table, and eliminating semantic information of multi-dimensional indexes of the fact data; carrying out distributed storage on the OLAP multi-dimensional data set oriented to the heterogeneous computing platform; discomposing an OLAP multi-dimensional data set query processing task for remote sensing data into three sub-tasks on three different computing platforms. By means of the method, the requirement for GPU memory capacity is reduced; the design issimple; the collaborative computing of the heterogeneous computing platform is realized, the hardware processing capability is fully utilized, the overall hardware cost is reduced, and the comprehensive OLAP query processing performance is improved.

The invention provides a symmetric regular multidimensional index platform construction method and device and a symmetric regular multidimensional index query method and system. The symmetric regularmultidimensional index platform construction method comprises the steps that at least one server node and at least one client node are set; a k-d tree-based local index on each client node is constructed; part of nodes are selected from local indexes of k-d tree of client nodes, selected nodes are added into glass Kjeldahl graph topology, and the global index based on a glass Kjeldahl graph is constructed.. The problems of high complexity, high index maintenance cost and low complex query efficiency in the prior art are solved.

The invention discloses a radar chart representation method for early warning and assessment indexes of a power system, which comprises the following steps of: radar chart parameter setting; power system index selection, including overall index selection and component index selection of a radar chart; component index computation by adopting a nonlinear monotone increasing primary function; component index normalization; overall index computation, including adopting a primary function similar to the step two to construct the overall operation index of the radar chart; overall index normalization, including normalizing an overall index into an interval of [0, 100]; and index presentation, including presenting component indexes on the same radar chart. By conducting multidimensional index normalization to index states and overall operation state indexes to generate general indexes suitable for the presentation of the radar chart, the operation conditions of a power grid are presented intuitively, scheduling personnel can know the heath condition of the power grid on the whole and therefore the power grid can be monitored from the top to the bottom.

A system is provided for determining coordinated motion between objects. The system includes a velocity data receiving component, a position data receiving component, a multidimensional indexing component and a determining component. The velocity data receiving component receives velocity data of the objects. The position data receiving component receives position data of the objects. The multidimensional indexing component generates multidimensional indices of the objects based on the velocity data and position data. The determining component determines whether there is coordinated motion between objects based on the multidimensional indices.

The invention discloses a data processing method and device. The method comprises the steps of establishing a multi-dimensional function model, the multi-dimensional function model comprises multi-dimensional indexes, and the multi-dimensional indexes correspond to a plurality of conditions for screening corresponding data blocks respectively; determining a multi-dimensional space corresponding tothe multi-dimensional function model and a plurality of centroids of the multi-dimensional space; clustering the plurality of data blocks through a clustering algorithm according to the plurality ofcentroids to obtain a plurality of block clusters corresponding to the plurality of centroids; and selecting a block cluster corresponding to the centroid of which the multidimensional index meets a plurality of conditions as a target block cluster. According to the method and the device, the technical problem of poor consistency and universality of data block processing due to limited feature measurement of the data blocks in a management mode of the data storage blocks in related technologies is solved.