147 results about "Pooled data" patented technology

A distributed OLAP-based method and system for generating association rules. An architecture is provided for processing transaction data to generate summary information, customer profiles, and association rules. The distributed system includes at least two layers of data warehouse / OLAP stations: local data-warehouse OLAP stations (LDOSs) and a global data-warehouse OLAP station (GDOS). The LDOSs perform local data mining and summarization, and the GDOS merges, mines, and summarizes the input data received from LDOSs. The summarized data is then utilized by the GDOS to generate association rules that can be provided to the LDOSs for business planning.

A user interface may be designed to receive conflicting data from multiple data sources during a merger of legacy computer systems. The interface automatically validates the conflicting data against each other to generate a final data set for review. Summary information for each data set can be displayed in a single interface such that the summary data sets are individually selectable and provide an overview of the data merger process for each data set. By drilling down through the summary data, the user interface can display individual data sets where data conflicts can be resolved, missing data can be provided, and duplicate data can be eliminated. When the merger process is complete, the interface can translate the data set into a standardized format that can be exported to form generation modules to generate, for example, a welcome letter based on the translated data set.

A system for matching potential buyers and sellers of complex offers, comprising a plurality of data collection devices, each connected to at least one packet-based data network and adapted to collect data pertaining to a plurality of potential buyers or sellers of complex offers, a summary data generator software module operating on a server computer and connected via a data network to a database, an attribute index generator software module operating on a server computer and connected via a data network to the database, a categorization software module operating on a server computer and connected via a data network to the database, a buyer analysis engine software module operating on a server computer and connected via a data network to the database, an analysis engine software module operating on a server computer and connected via a data network to the database, and a matching engine software module operating on a server computer and connected via a data network to the database. Data collected by the data collection devices is stored in the database and is used by the summary data generator software module to generate a plurality of summary data elements pertaining to a potential buyer of a complex offer, and the plurality of summary data elements is stored in the database and used by the attribute index generator software module to generate attribute indices each based on at least two summary data elements using a weighted relational algorithm, and at least some data collected by the data collection devices is used by the buyer analysis engine software module to determine at least a probability that a buyer will buy a specific complex offer, and the marching engine software module uses an optimization algorithm to determine an optimal matching of potential buyers and complex offers based at least in part on a plurality of attribute indices and a likelihood to buy for each potential pair of offers and potential buyers.

Interactive and dynamic exploring of filter criteria for large amounts of numerical data having multiple dimensions is described. Exploration occurs without excessive amounts of computation or querying of a database based on a data set summary that may be obtained from a server in a search system and applied by a client device. A data set is summarized so as to capture relationships between distributions of items in the data set along multiple dimensions. To explore filter criteria, a user may interactively adjust a range of values that act as a filter criteria along a dimension and determine an effect on a distribution of items along another dimension. The client device may apply the data summary in reverse to determine, based on user input specifying aspects of a distribution along one dimension, filter criteria for another dimension that would result in the specified distribution.

Data is collected and aggregated regarding a particular used item for sale, e.g., automobiles, which is in turn validated and normalized with respect to pre-determined identification models. A historical report may be generated to provide an assessment of value based on qualitative information such as mileage and / or location, and may be presented in a multi-axis graphic format. Data records are collected from a plurality of sources over the Internet, and are validated by comparing data field entries in the aggregate data records with data field entries in an established validation database. The validated data records are normalized with respect to a predetermined set or sets of fields by assigning an identification unit to each validated data record. A web crawler to seek out suitable data records relating to the used items that are sought, a search engine is queried to derive a list of suitable high probability target URLs.

The present invention relates to a method and system for measuring investment performance (e.g., total portfolio performance of individuals). In one example (which example is intended to be illustrative and not restrictive), the method and system may be used for measuring investment performance of personal pension portfolios. In another example (which example is intended to be illustrative and not restrictive), the method and system may provide for measuring performance of an investment portfolio held by an investor, comprising: providing first information indicating how the investment portfolio has performed over one or more predetermined periods of time; and providing second information indicating how investment portfolios of the investor's peer group have performed (e.g., on average) over the predetermined period(s) of time. In other examples (which examples are intended to be illustrative and not restrictive), the present invention may be used to pool data across employers in relation to pension funds and / or to pool data across wealth management firms or trust companies in relation to underlying client accounts. In another example (which example is intended to be illustrative and not restrictive), simplified portfolio level reporting and comparison of asset allocation strategies may be implemented by the present invention via the categorization of essentially all available financial products into a relatively small number of asset classes (e.g., between about 15 and 20 asset classes).

A system and method of motion analysis, fall detection, and fall prediction using machine learning and classifiers. A wearable motion sensor for collecting and transmitting motion data for use in a fall prediction model using features and parameters to classify the motion data and notify when a fall is emergent. Using machine learning, the fall prediction model can be created, implemented, evaluated, and it can evolve over time with additional data. The system and method can use individual data or pool data from various individuals for use in fall prediction.

The invention belongs to the field of intelligent transportation, particularly relates to a short-term traffic flow prediction method and system based on hybrid deep learning and devices and aims to solve the problem of low precision of an existing large-scale traffic flow prediction method. The method of the invention comprises a step of acquiring historical traffic flow data of each traffic observation point to be predicted, wherein the historical traffic flow data is r traffic flow data sets of continuous equal-time-length periods before a t moment, a step of merging the historical trafficflow data in each traffic flow data set to obtain corresponding merged data and normalizing each merged data, a step of obtaining a normalized prediction result of each traffic observation point at the t moment by adopting a hybrid deep learning model based on the normalized historical traffic flow data of each traffic observation point, and a step of carrying out reverse normalization on the prediction result to obtain a traffic flow prediction value of each traffic observation point at the t moment. According to the invention, the precision of large-scale traffic flow prediction is improved.

Users of Mainframe computers running under IBM's MVS operating systems have a need to merge migrate data from multiple smaller DASD devices (disk volumes) to larger DASD devices, and / or to migrate data in order to combine data set extents. A method is disclosed for migrating data where a volume merge is involved, and / or when combining of extents is desired, that minimizes the down time of applications using the involved data while satisfying MVS rules for volume and catalog meta-data files as well as data extent limitations. The method may be implemented such that source and target volumes need not be in like manufacturer DASD devices.

A computer system and related computer-implemented methods are designed and configured to store and deliver, upon request, information related to a plurality of asset-backed security pools, and to execute transactions between one or more parties relating to at least one of the plurality of asset backed security pools. The computer system generally comprises a computer including a computer usable medium storing a computer readable program and a network interface that includes software modules and a data storage system in communication with the computer via the network interface, the data storage system storing information relating to the plurality of asset backed securities, and account information related to at least the one or more parties. The computer is operative with the computer readable program to provide information related to a plurality of asset-backed security pools to at least one of the parties, enable the at least one party to select one or more asset-backed security pools for inclusion in a specified pool, provide aggregate pool data related to the selected specified pool, provide information related to the selected specified pool to at least one other party, receive pricing information from the at least one other party, and execute a trade for the asset-backed security pools in the specified pool.

Enables locating and merging potential data record matches. Enables locating duplicates through the definition of matching strategies. Each strategy may include transformations, matching rules and scoring thresholds to implement fuzzy matches that match closely related data records that are not exact matches. Performing a search allows for narrowing down the records to a desired set on which to apply a given matching strategy. Merging is performed on the potential duplicates thus located to consolidate data and remove duplicates. By narrowing down the records to a closely related set via a search, merging is simplified to work on a small number of closely related records, thus simplifying the process. The total matching score obtained via execution of match strategies may be utilized to determine which potential record(s) to merge for example. May utilize past user input to provide intelligent inputs for rules, tokens, weights, fields, parameters or any other past user input.

The invention provides a data processing method for a data warehouse, which comprises: extracting original data from service systems and generating source system data tables; eliminating redundancy of the source system data tables, recording data histories and establishing historical data tables; establishing fact data tables to classify the data of the historical data tables; summarizing data of the fact data tables and establishing summarized data tables; counting index data among two or more summarized data tables, and establishing a statistic data table; based on the data of the fact data tables, the summarized data tables and the statistic data table, establishing an application data table. According to the data processing method for the data warehouse, which is provided by the invention, mutual dependency of tasks inside each level in a universal dimensional model layer is avoided, the parallel number of the tasks is maximized and computer resources can be effectively utilized, so that the data processing efficiency of the data warehouse is improved. The invention also provides a corresponding data processing system for the data warehouse, which can realize the data processing method, which is disclosed by the invention, for the data warehouse.

Disclosed is a computer readable medium containing a program product provided for the development, receipt, storage, and presentation of the data necessary for delivery of quality assurance test activities. In particular, the program product allows users to create quality assurance testing criteria and procedures; define, document, and approve specific actions and allocate unique categorization codes. The program product includes a module for the creation and storage of predefined text and image elements for the provision of enterprise wide knowledge sharing. The program product applies calculations to consolidate and convert data into statistical reports utilizing a variety of user-defined criteria, including but not limited to component descriptor, quality criteria, time period and manufacturer. The program product also accepts, consolidates and calculates post-production quality resource utilization / costs, segregated periodically and / or consolidated, enabling stakeholders to determine appropriate corrective actions based on ongoing quality assurance testing outcomes.

A method and related computer system that allow recalling at least one memory pooling profile, in response to user input, and pooling data processing system memory devices in response to the at least one memory pooling profile.

The technique described herein provides a way to summarize data and can also minimize unnecessary accesses to a data store. In one embodiment, the technique creates and stores an adaptive range filter that contains a compact summary of the contents of an index for a data store in the form of a trie data structure. Before accessing the index of the data store in response to a query, the technique checks the filter to determine whether the data store does not contain any keys for a specific range of data. If the adaptive range filter indicates that the index contains no keys satisfying the query predicate, the index of the data store and the data itself is not accessed. The adaptive range filter of the technique supports both range predicates and equality predicates. It is adaptive to changes in data and queries by learning the query and data distribution.

A method of identifying a network of actors within a data set, the method comprising: —importing data from one or more data sources; —normalising the data in one or more fields to create a consolidated data set; —identifying one or more networks based on identical or similar instances of one or more pieces of data in the consolidated data set; and —calculating a measure of influence of one or more of the actors in an identified network.

The invention discloses an objective positioning and classifying algorithm based on deep learning. The algorithm comprises the following steps: S1, inputting a picture into a first network and outputting a series of objective positioning frames and scores; S2, inputting a picture and a series of sub windows into a second network; S3, forwardly propagating the networks to a last convolution layer to generate a characteristic pattern; S4, performing coordinate transformation on the sub windows by using a zooming coefficient in order to map the coordinates to the characteristic pattern; S5, acquiring a characteristic from the characteristic pattern by using the zoomed sub windows and pooling the characteristic to a regular size; S6, classifying the pooled data to obtain a classification result and a score of an area; and S7, inputting the objective positioning frames and the classification result of the area into a classifier to carry out classification, and outputting the type and the coordinates of the objective. The algorithm may extract characteristics, classifies the objectives, performs positioning and identification by using a unified network, and greatly increases calculating speed.

The invention discloses a wide-net fracturing method for shale gas exploitation. The wide-net fracturing method comprises the following steps: according to seismic data, geological data, logging data, gas pool data and rock mechanics data, structuring a geological model and establishing a rock seepage-stress-damage coupling model; according to the requirement of the rock seepage-stress-damage coupling model, modeling a pre-fracturing initial stress field to obtain a stress field model; according to the geological model and the stress field model, obtaining a gas pool numerical model of a research object, and coupling the geological model, the gas pool numerical model and the rock seepage-stress-damage coupling model to obtain a geological model-numerical model-FSD coupling model; according to the geological model-numerical model-FSD coupling model, confirming perforation parameters, service well sections and gas production profiles of a shale gas horizontal well; according to the confirmed perforation parameters, service well sections and gas production profiles, carrying out wide-net crack fracturing. According to the method, perforation and balanced gas production can be matched and optimized, all perforation clusters are subjected to liquid inlet to form effective cracks, and the yield of shale gas is improved.

Aspects of the subject disclosure may include, for example, a computer that performs a statistical natural language processing analysis on a plurality of text documents to determine a plurality of topics, creates a proper subset of topics from the plurality of topics, based on user input, maps one or more topics in the proper subset of topics to each document in the plurality of text documents, thereby creating a plurality of topic-document pairs, identifies n-dimensions of bias for each topic-document pair from the text, creates clusters of topics from the proper subset of topics, and generates presentable content depicting each cluster of the clusters of topics according to a corresponding image configuration. The topics and n-dimensions of bias data can be further analyzed with co-collected structured data for statistical relationships. The topics and n-dimensions of bias data can be used for a publisher-subscriber network that uses content-driven routing when delivering raw data and summarized data via the network. Other embodiments are disclosed.

The invention discloses a cloud resource pool data security detection method comprising the steps of acquiring established sensitive data; acquiring export data drained from a cloud resource pool; scanning and recognizing the sensitive data in the export data; building a sensitive data life cycle, and hierarchically managing the sensitive data; capturing a host virtual machine of the sensitive data in a cloud resource environment, and monitoring traffic of the virtual machine; and analyzing the sensitive data and abnormal operation behaviors of the host virtual machine of the sensitive data, and giving an alarm. In addition, the invention also provides a cloud resource pool sensitive data security detection system comprising a control module, a collection module, a processing module, a supervising module and an auditing module. By using the method provided by the invention, a full life cycle security control on links such as building, generation, utilization and destroying of various kinds of sensitive data during business data calling and transmission, and business interaction and migration processes under the cloud computing environment is achieved, and thus abnormal and illegal behaviors can be found.

The invention discloses a method for dynamically allocating on-chip heterogeneous memory resources by utilizing a virtual memory mechanism, comprising the following steps of: analyzing the time and space distribution of data sections (comprising global data, stack data, pile data and constant pool data) with data Cache conflicts caused by high frequency by adopting a time slot analyzing method, then obtaining the time slot conflict diagram of the data Cache by the distribution and carrying out mathematical abstraction for the time slot conflict diagram. According to the target function of energy consumption and the target function of performance, a program part to be optimized is selected by using an integer nonlinear programming method and then is dynamically remapped in an on-chip data SPM (Scratch-pad Memory) by utilizing clock interrupt, and thereby, the extra memory access caused by the data Cache conflicts can be avoided. The method can reduce the energy consumption of a system and enhance the performance of the system due to the full utilization of on-chip heterogeneous memory.

The invention discloses a method for diagrammatizing data, comprising the following steps: data collection; summarization data: an integrated platform for supporting data processing is established according to the definition of the data so as to record basic data and all items of data completely; data selection: summarization data is specifically selected; data processing: the data is processed in order to find out maximum value and minimum value in the data; and diagram display data: drawing display is carried out by taking the maximum value and the minimum value in the data as an upper limit and a lower limit of a graph coordinate axis respectively.

Today's cloud software, especially cloud management software, faces a complex, distributed, cross platform environment with extremely diversified software components. Cloud Connection Pool (CCP) is a technique to obtain a connection in such an environment and is more complex than a traditional connection pool. CCP allows requesting components to establish connections to target components. CCP uses cloud mapping data that associates cloud components with each other and stores pool data that identifies connection pools for components (or “managing components”) that manage target components. In response to a request for a connection from a requesting component, the CCP determines a managing component that is associated with the requested target component and identifies (or creates) a connection pool that is associated with the managing component. The CCP then retrieves a connection from the connection pool and returns the connection to the requesting component.

The invention provides a system basing on network for the processing of the data of a client protocol capital pool and a method thereof. The system includes a system host, external financial network and a transaction terminal which is linked with the system host through the external financial network and sends a transaction request to the system host through the external financial network. The system host includes a data storing device, a data processing device and a plurality of interfaces. The data processing device receives the transaction request of the transaction terminal through the interfaces, verifies the qualification and the authority of a user, visits the data storing device for the processing of the transaction request and returns the processing result to the transaction terminal through the interfaces and the external financial network. The data storing device includes at least one capital pool account unit which includes a capital pool account and at least two member accounts which are corresponding to the capital pool account through the protocol. The data processing device converges the capital of member accounts through the capital poll account and distributes profit amount to the member accounts through the protocol.

Said method includes defining data block buffering pool data management unit structure, designing MB memory block buffer pool manager, buffer type memory allocation process and buffer memory releasing process. The present invention adopts embedded system buffer type memory allocation method, said method utilizing data block buffering pool posting distributed memory to data block buffering pool instead of immediately recovering system. Said invented method can directly use idleness data cell, until need to call system memory allocation, capable of avoid calling more operation system memory allocation and memory releasing, thereby raising system efficiency.

The present invention describes a method for receiving data within an aggregation facility, precalculating, and fixing a dimension of the data table. The data may be aggregated, wherein at least one data dimension remains flexible. An analytic query may be received that is associated with at least one data dimension. An analytic query may be processed by accessing the aggregated data.

The invention discloses a video buffering determination method and device. The method comprises that play log data for recording the total amount of data played by a client and buffer log data for recording the total amount of data cached in a preset memory by the client are recorded; buffer pool data for indicting the total amount of residual data cached in the preset memory by the client is determined according to the play log data and buffer log data; and whether the client is in a buffering state is determined according to the buffer pool data, and the client is stopped when playing the video in the buffering state. The technical problem that that whether the client is buffering when loading the video cannot be detected accurately in the related art is solved.

A domain independent system and method for automatically generating at least one presentation-ready report from either detailed or summarized data from database queries. The process of getting useful information requires querying a database to get detailed records, then meaningfully aggregating detailed data based on user experience and business needs and, finally, presenting the data using appropriate reports. This process of data aggregation and presentation can be automated and is accomplished by aggregating detailed data using domain metrics selected based on predefined and configurable rules or past usage; selecting one or more presentations based on predefined and configurable rules or past usage; and displaying one or more presentations based on device constraints and characteristics.