280 results about "Multi dimensional analysis" patented technology

A method is provided for qualifying and analyzing business intelligence. At a first part of a data management system receives first, second and third streams of data. The first stream is client provided source data, the second is public source data and the third is data management system internal data previously collected and managed source data in the data management system. The three streams of data are organized into items and their attributes at the data management system. The source data is transformed at a data warehouse where it becomes normalized. Logic is applied to provide multi-dimensional analysis of transformed source data relative to a scale for at least one business intelligence. The data warehouse includes updated data from the multi-dimensional analysis. A user interface communicates with the data management system to create statistical information that illustrates impact over time and value.

Data integration and data analysis using computing equipment, software as well as hardware, includes a system and method for integrating data from various data sources, structured and unstructured, without physically creating a data warehouse and automatically generating queries for analysis of the integrated data from a multitude of different views.

A method is provided for qualifying and analyzing business intelligence. At a first part of a data management system receives first, second and third streams of data. The first stream is client provided source data, the second is public source data and the third is data management system internal data previously collected and managed source data in the data management system. The three streams of data are organized into items and their attributes at the data management system. The source data is transformed at a data warehouse where it becomes normalized. Logic is applied to provide multi-dimensional analysis of transformed source data relative to a scale for at least one business intelligence. The data warehouse includes updated data from the multi-dimensional analysis. A user interface communicates with the data management system to create statistical information that illustrates impact over time and value.

A system and method for analyzing and reporting data from multiple sources is provided. The system is a foundation for an analytical platform that covers not only traditional relational data, but also a new generation of extensible data formats designed for the web, such as those based on XML (FIXML, FpML, ebXML, XBRL, ACORD, etc.), as well as HTML, E-mail, Excel, PDF, and others. In a preferred embodiment, the eXtensible on-line analytical processing (XOLAP), is a scalable client / server platform that allows the multi-dimensional analysis of modern data types, as well as traditional relational data, by bringing them all into an internal common XML-based model, without the time and expense of creating a data warehouse.

The invention discloses a method and a system for making multi-dimensional analysis to message class service data. The steps of the invention comprise a data collection step and a data integration step; a data conversion and loading module is responsible for converting the data in a middle database into a relational database with star framework characteristic, settles various data to be analyzed of message class service, classifies the data with common or similar characteristics and brings the data into a unified dimension hierachy; the data in the middle database is further cleaned and converted to be processed into another multi-dimensional database; and a data analysis and presentation step is included. The corresponding system comprises a data collection module which is independently arranged, the data conversion and loading module and a data analysis and presentation module. With the invention, the multi-dimensional data model can be shared in similar value-added service system, the development cycle and cost of the system can be reduced. To apply the function of multi-dimensional data analysis possessed by the system established by the model can provide operators and equipment manufacturers with more flexible and convenient data statistic method and decision support.

The invention discloses a clinical data mining analysis and aided decision-making method based on an Internet integrated medical platform, and relates to the technical field of an Internet medical platform. The clinical data mining analysis and aided decision-making method includes data mining analysis and aided decision-making, wherein data mining analysis includes a multidimensional analysis algorithm module, a data mining algorithm module and a deep learning algorithm module; and aided remote decision-making includes four parts: a prediction module based on index parameters, a prediction module based on inspection report texts, a model training module and a structurized module. The clinical data mining analysis and aided decision-making method based on an Internet integrated medical platform selects several diseases as research objects for data collection and analysis, such as hyperthyroidism, diabetes, thyroid nodules and breast tumors, and collects and integrates clinical medicaldata depended the integrated platform to realize data mining analysis and aided decision-making services for clinical data diseases, such as hyperthyroidism, diabetes, thyroid nodules and breast tumors, so as to provide systematic support for clinical diagnosis of clinicians and disease research by researchers.

The invention belongs to the technical field of industrial big data application, and particularly relates to an industrial big data multidimensional analysis and visualization method based on a JSON document structure. The method comprises the following steps: by taking JSON as a basic carrier of data, constructing an industrial data mart in parallel by utilizing Spark and ElasticSearch through configuring a relational database and a file system data source and defining data conversion and data cleaning operations; configuring an overall process of data analysis in a graphical mode to construct an analysis data set of a multi-dimensional structure, and repeated association operation on massive data being avoided; and for a specific data analysis scene, customizing each dimension calculation index of the data analysis report in a visual dragging mode based on a pre-constructed multi-dimensional analysis data set, and generating an interactive graphic analysis report. According to the method, the JSON document format is used as a carrier of basic data, and the advantages of the JSON document format in storage and analysis are utilized, so that multi-dimensional analysis structure modeling and user-defined interactive analysis are more convenient and efficient.

The invention provides an OLAP multi-dimensional analysis and data mining system. The system comprises a data model, a distributed OLAP engine, an OLAP analysis engine, a multi-dimensional report analysis interface, a data mining interface and a data visualization tool; the data model is dragged by a user through a visual interface to finish data modeling, and has unified model configuration; thesystem automatically performs model adaptation and enables the data model to be called by cooperation with internal other engines or tools; the distributed OLAP engine provides a multi-dimensional data model preprocessing capability for the OLAP system; the OLAP analysis engine supports a multi-dimensional query analysis engine of a big data platform and a relational database, and analyzes an MDXstatement to obtain a standard SQL; the multi-dimensional report analysis interface and the data mining interface have multi-dimensional data analysis and data mining functions and provide a report analysis method and a data mining algorithm model; and the data visualization tool provides a visual service for report analysis and data mining in the multi-dimensional report analysis interface and the data mining interface, and provides visual result social sharing and chart management functions.

The invention relates to a big data-based social insurance index warehouse building system and method and belongs to the technical field of big data application. The invention aims to build an accurate and regularly-updated multi-dimensional statistical index base based on the organization of cubic structure storage by using the big data processing technology and distributed storage technology. The building system consists of a data source module, a business data collection module, a data pretreatment module, an index calculating module, an index metadata storage module, a data storage module and a data query module. The building method is based on the building system. The system and the method uses social insurance business data as the data source and builds an accurate and regularly and incrementally-updated index data warehouse by using the big data processing technology and distributed storage technology, and allows rapid index multi-dimensional analysis and query.

The invention relates to the technical field of data analysis, and in particular relates to a data analysis self-help data fetching method and system based on indexes. The data analysis self-help data fetching method comprises the following steps: firstly, defining a business index, needing to be used for analyzing and inquiring, through a standard index defining method, and generating index result data; forming a basic data source of self-help data fetching by an index data result; providing various types of defined indexes and dimension information capable of being used for analyzing the indexes on a user data fetching interface; after freely selecting and configuring the needed indexes and inquiring dimension by a user, constructing a data inquiring sentence by the system through an SQL (Structured Query Language) configuration device according to an index and dimension selecting condition of the user; operating and generating a final data result and displaying to the user. The data analysis self-help data fetching method and system based on the indexes have the beneficial effects that free combination of data content and a displaying structure is realized, and a more convenient and flexible data multi-dimensional analysis means is provided for data analysis of the user.

The invention relates to an accident monitoring, anomalous event identifying and multi-dimensional analysis method and relates to an analysis method. As the construction of the power grid continues togrow and the number of power equipment increases, accurate and rapid analysis of faults and anomalies cannot be achieved. The method in the invention comprises the following steps: 1) establishment of a fault and anomaly rule base; 2) tagging analysis; 3) fault event identification; 4) anomalous event identification. The technical solution establishes an intelligent review mechanism by monitoringalarm information; the daily information is automatically tagged according to the information such as alarm level, monitoring operation information, maintenance and the like by using a data label technology; the effective alarm information is extracted; the fault and anomalous information corresponding to the information is identified from mass data in combination with the fault and anomalous information rule base; meanwhile, the residual information is pushed to manual review for special analysis, thereby improving the efficiency and the accuracy.

A system and method employing photokinetic techniques in cell biology imaging applications are disclosed. Systems and methods of acquiring image data of an object may comprise: selectively inducing photoactivation of material at a site on the object; performing an optical axis integration scan; simultaneously executing a time delay integration scan sequence; and processing acquired image data in accordance with one or more desired analyses. Various methodologies and applications may include, inter alia, selective photobleaching of a site on the object, diffusion rate, velocity, and wave-front propagation analyses, multi-dimensional analyses of dispersion characteristics, biomolecular binding in cellular organelles, and photoactivation assisted systematic image segmentation for the study of cellular components.

The invention discloses an early-warning prediction method for water environment safety, which comprises the following steps: performing space-time multi-dimensional analysis on monitoring information acquired from a water environment; establishing a hazard rating threshold early-warning index according to the data acquired by the model analysis to form water environment safety early-warning rating and warning-situation comprehensive assessment data; and establishing a water environment safety early-warning basic database and gradient and abrupt early-warning prediction system models of the water environment safety, and establishing a data adapter between the water environment safety early-warning basic database and the early-warning prediction system models so as to visually express the prediction results of the models and implement full-process monitoring for the early-warning evolution of the water environment safety. Aiming at the complexity of the water environment and the multi-source isomerism of the water environment monitoring information, the method establishes an effective environment monitoring multi-source isomeric data fusion technology framework and a method to form an early-warning prediction system of the water environment safety so as to provide important theoretical direction for water environment management, and the method has broad application prospect.

A method for solving any arbitrary multi-dimensional scientific or engineering design problem requiring solutions for stress, strain and deformation, and which therefore demands the incorporation of a material constitutive equation into the mathematical solution and wherein that constitutive equation, which quantitatively defines the relationship between stress and strain, incorporates independent tensor valued coefficients and a scalar valued constitutive function / s, and where the values of the tensor valued coefficients and the form of the constitutive function / s is specific to any particular material under consideration.

The invention discloses a multi-dimensional analysis method for multi-level storage data. The multi-dimensional analysis method comprises the following steps: step 1, building a unified data model; step 2, building a multi-dimensional analysis model; step 3, performing multi-dimensional analytic calculation and demonstration: a calculation engine automatically generates an aggregate calculating sentence, corresponding to a next-level calculation node, of the multi-dimensional analysis model according to routing information, a calculation agent executes aggregation operation to generate a pre-aggregation result and uploads the pre-aggregation result onto a main-control server, and then secondary aggregation calculation is executed to generate a multi-dimensional calculation result set; the calculation engine forms a dimension member inquiry algorithm according to the multi-dimensional analysis model and the unified data model, inquires a dimension member, generates cell objects of a demonstration report and fills the multi-dimensional analysis result into the cell objects to realize multi-dimensional demonstration of the multi-dimensional analysis result. The multi-dimensional analysis method can realize real-time multi-dimensional analysis of hierarchical storage data without centralizing data in advance.

The present invention belongs to the field of computer and information safety technology. The information safety auditing method including adopting Syslog standard protocol and mode matching method based on regular expression in collecting journal information; using the data storehouse to separate the comprehensive analysis processing environment and operation processing environment; adopting multi-dimensional information safety model to correlate the analysis dimensions of several auditing analysis themes and to form multi-dimensional stellar system; performing on-line in-situ multi-dimensional analysis by the multi-dimensional model and data excavation and correlation to find out safety hole and problem; and creating auditing analysis report based on the analysis result. The method of the present invention has expandability, opening and raised auditing efficiency.

Data integration and data analysis using computing equipment, software as well as hardware, includes a system and method for integrating data from various data sources, structured and unstructured, without physically creating a data warehouse and automatically generating queries for analysis of the integrated data from a multitude of different views.

The invention belongs to the technical field of network security, and discloses a network event monitoring analysis method and system, an information data processing terminal. A data acquisition layeris used for realizing acquisition of mirror image data traffic and deep packet detection. A data sharing layer is used for carrying out multi-dimensional analysis on the mirror image data traffic processed by the data acquisition layer and providing a data source for an external output interface; and the business display layer is used for realizing a security event view, a network view, a terminal view, an early warning view, a disposal event view and a work order view. According to the invention, illegal assets, behaviors, policies and threats in the network and attacks and threats outside the network can be effectively discovered and early warned in time; various response modes are provided to help enterprises to discover security threats and risks in advance, timely inform enterprise managers or security equipment to complete blocking of the threats and spreading of the risks, ensure asset and information security and control security events within a minimum range.

The invention provides a multi-dimensional analysis method and device for mass data. The multi-dimensional analysis method and device are used for solving the problems that multi-dimensional analysis can not be efficiently conducted on mass data stored on a mass data source Hadoop platform through existing online multi-dimensional data analysis OLAP in real time. The method includes the steps of analyzing and processing a multi-dimensional analysis query request issued by a user to obtain an analysis result, wherein the analysis result includes cube multi-dimensional mode information corresponding to the multi-dimensional analysis query request and a structured query language (SQL); obtaining a data source matched with the cube multi-dimensional mode information, and establishing the connection relationship with the data source, wherein the data source comprises the Hadoop platform and / or a relationship database; obtaining the data query result from the Hadoop platform or the relationship database according to the connection relationship and the SQL; converting the data query result into a multi-dimensional result according to the cube multi-dimensional model information, and returning the multi-dimensional result to the user. By means of the multi-dimensional analysis method and device, the aim of efficiently conducting multi-dimensional analysis on mass data stored on the Hadoop platform in real time is achieved.

The invention provides a method for detecting teacher sub-health states based on a classification and regression tree. The traditional sub-health assessment for college teachers lacks timeliness, objectivity and efficiency. In the big data environment, the machine learning technology can be used for establishing a sub-health assessment model more effectively, so as to support prediction and early-warning of the sub-health states of the college teachers. The method for detecting teacher sub-health states based on the classification and regression tree comprises the steps of: firstly, performingmulti-dimensional analysis and conceptual modeling on college teacher sub-health influencing factors; secondly, performing analysis and data pre-processing on features of sample data; on this basis,utilizing a classification and regression tree algorithm for giving out a detailed process of modeling a sub-health decision-making model, and analyzing assessment indexes; and finally, utilizing a Spark distributed computing framework to give out parallel implementation of model construction. The method provided by the invention is more efficient and objective, can immediately reflect the sub-health states of the teachers, and supports the prediction and early-warning of the sub-health states of the college teachers.

A system, method, and article for diagnosing a test set of biological cells. For example, in one embodiment a normal set of cells is characterized using flow cytometry. A centroid and radius are defined for a set of clusters in an n-dimensional space corresponding to a normal maturation for a cell lineage in the normal set of cells. A test set of cells is characterized using flow cytometry and the characterization is compared to the set of clusters.

The present invention discloses a distributed OLAP analysis method and system based on pre-computation. The method mainly comprises: constructing a data model based on the distributed data warehouse, and defining data cubes according to the data model; starting pre-computation tasks for the given data cubes so as to pre-build the cubes in a parallel computation manner, and storing results in a distributed key storage system; through a series of steps, converting multi-dimensional analysis operations into key-value query operations on the data cubes, directing obtaining analysis results from the built cubes, and displaying the results in the form of rich and diversified charts; and using the NoSQL to carry out cache optimization on the OLAP query operation. According to the method and system disclosed by the present invention, the powerful processing performance of the Hadoop platform is fully exerted, and data cubes are pre-built, the problem that the query is slow due to that the traditional method needs a large amount of computation from the original data in each query is overcome, so that OLAP analysis efficiency and system performance are improved.

The invention discloses a big data tax-related information analysis system. The system comprises the following modules: a data acquisition module which performs incremental acquisition on data in the internet by adopting a crawler acquisition mode, a data cleaning module which performs data cleaning in ways of unrelated field cleaning, price and discount price filtering, time stamping and currency automatic conversion, a data analysis module which performs multi-dimensional analysis on tax-related information data through online analysis processing and data mining technologies, a data storage module which dispersedly stores the data in a plurality of independent devices by adopting a distributed storage policy and an extendable system structure, and a data output module used for outputting the data required by a user according to a specific rule. According to the big data tax-related information analysis system, a large amount of tax-related information data is provided for taxation collection and management in real time, and a tax-related information law is found and future tax avoidance and tax evasion trends are predicted by utilizing trend indexes.

A computer implemented system and method automates analysis and mining of concepts from unstructured data. At least one concept within at least one object is analyzed. Analysis involves: selecting an object for inclusion in an initial set of objects to be analyzed; using an algorithm to extract a concept from the initial set of objects to create an initial set of concepts; refining the concept based upon relationships to other concepts; and performing multi-dimensional analysis on the concept in the initial set of objects to analyze the concept.

The invention discloses a multi-dimensional assessment and precise construction investment evaluation method based on coverage and value relevance and relates to the technical field of big data analysis in data communication. The method disclosed by the invention performs multi-dimensional analysis on an MR poor coverage ratio, a quantity of MR sampling points, user flow, number of users, user perception data and / or user set information, field road test data, complaint information and suppression flow big data, so that indoor values are excavated, precise planning is performed, site building value is effective improved, service turn-around time is shortened, a network awareness word-of-mouth image of an operator is improved, and finally enterprise benefit is improved.

The invention particularly discloses a measurement calculation method supporting commodity comment data multidimensional analysis. According to the measurement calculation method, a concept of encyclopedia instruction is brought in, a relationship between commodity comments and a theme is excavated through LDA (Linear Discriminant Analysis), comments of general commodities are structuralized and integrated into the encyclopedia instruction, an a measurement result is returned in a form of a theme and an abstract to enable the measurement to have relatively high readability. The measurement calculation method supporting commodity comment data multidimensional analysis obtains a commodity comment collection and integrates the commodity comment collection with relevant encyclopedia instruction based on different dimensional values, and mainly comprises the following steps of: (1) calculating probability of vocabulary-theme in the encyclopedia instruction and the commodity comment collection by using the LDA, and finding similar comments and supplementary comments from the commodity comment collection by utilizing a similarity calculation formula; (2) for the similar comments, excavating the theme of an aspect in the encyclopedia instruction and using the similarity number to represent the concern extent of the theme; and (3) for the supplementary comments, generating an abstract to serve as supplementation of the encyclopedia instruction.

The invention discloses a data analysis system and method based on a distributed multi-dimensional analysis technical scheme. The system comprises the following modules: a data collection module, a data preprocessing module, a data multi-dimensional model design module, a data multi-dimensional analysis module and a data display module. The system and the method have the advantages that the construction process is clear, and the customization capability of each layer is high. Hundred millions of internet log detailed list data containing user information on the daily TB-level data volume can be processed; after the data is converted into a dimension model and a data cube, data of dimensions such as time, geography, network elements, users, terminals and services can be analyzed; and the dimension and indexes of the dimension model are clear, so that the use by business personnel is facilitated. Compared with a distributed big data processing scheme, the number of manually intervened summary models and the development work of data processing tasks can be greatly reduced.