67 results about "Specific data source" patented technology

Methods, program products, computer program products and systems for uniquely identifying an individual within a population to the exclusion of all others within the population by comparing data from unique data sources based on the name of the individual for providing a collection of preliminary suspects. An individual search service provider is then searched for additional data relating to the collection of preliminary suspects to locate any potential matches, which are reconciled with data from the unique data sources to locate at least a portion of a unique identifier that may be associated with the individual. The potential matches and portion of the unique identifier are compared with other data records within the individual search data source for locating a complete unique identifier that may be associated with the individual, followed by determining whether or not this complete unique identifier uniquely identifies the individual.

An interactive and dynamic data analysis tool that helps interactive analysis in real time on medium size datasets having complex structure is described. In one aspect, the data analysis tool is capable of being configured to act as a data producer tool arranged to provide a data source. The data analysis tool can also be configured as a data consumer tool capable of receiving and processing a particular data source. The data source tool and the data consumer tool are connected together to form a framework that takes the form of a data mapping context that mediates the data provided by the data source and a particular data role.

A computer implemented method, apparatus, and computer usable program code for collecting data. The data is collected from a particular data source by an application portion of agent to form collected data. The application portion is associated with the particular data source in response to an event. The collected data stored in a temporary data store for transfer to a data storage system to form stored data. The stored data sent to the data storage system using a generic portion of the agent, wherein the generic portion of the agent is configured to send data to the data storage system.

The invention provides an interactive large data analysis query processing method. The interactive large data analysis query processing method comprises steps that, 1), a query request generated by a user or a machine is submitted to an SQL query analyzer; 2), the query quest is analyzed by the SQL query analyzer into a logic plan; 3), the logic plan is read by an optimizer and is converted into a physical plan, and interaction between a storage engine and a specific data source is realized; and 4), the physical plan is performed by a performing engine, and meta-data information is provided based on a meta-database query performing framework. For real-time interactive large data set analysis blank, P-byte data is processed under the condition of low delay response through the method according to design, multiple functions of other SQL-on-Hadoop engines are integrated, the query speed is greatly improved, and thereby Hadoop data query and enterprise-level large data analysis can be rapidly and efficiently carried out for enterprise users.

Methods, systems, and articles of manufacture for proving global annotation services are disclosed. Global annotations are used to annotate a data element independently from the internal representation of a data element employed by a particular software application. Data elements are normalized into a form used by a global annotation system to identify the data element, and corresponding global annotations, independent from the application in which the data element may appear. An annotation cache may be used to store the global annotations that have been created for a particular data source, improving the efficiency of the global annotation system.

Various embodiments of a utility for configuring data sources in a networked computer system are disclosed. A networked computer system may include a number of backend systems hosting a variety of types of data resources including databases produced by a variety of vendors. Application servers running transactional applications as well as many other types of computer systems may be included in the networked system. The data source configuration utility may determine the data source configuration parameters associated with each of the various types of data resources included in the system. When a data source is selected for configuration, the utility may present the configuration parameters corresponding to that particular data source to the user. The utility may create one or more data source configuration files based on parameter values received from the user.

A system and method are disclosed for persisting data received from disparate data sources having different internal schemas. In operation, a data processing engine aggregates related data received from the different data sources and organizes the aggregated data into flexible records. A flexible record is a composite of associated fields aggregated from a set of records received from one or more data sources. Each field associated with a flexible record includes data received from a particular data source and specifies the particular data source as the source of the data. Flexible records are stored in a storage repository, and each flexible record is associated with at least one user who accesses data via a client device.

A system and method for providing a virtual map database, referred to herein as the ''Virtual Database System'' (VDB). The VDB allows integration of map data, often from various sources, in a consistent manner for supply to an end user, while simultaneously ensuring that the entity best able to support a particular data source retains control over the data. In accordance with an embodiment, the VDB environment enables third-party data providers to associate their third-party-files with a base map or file-of-reference, thereby allowing for the creation of dynamic relationships between digital map features and other third-party data providers. The integration may be performed in a dynamic or real-time fashion, receiving up-to-date information from the various sources, creating links, and composing virtual maps, as needed or on-demand. Since the information is linked between the map providers and the various third parties, whenever an item of information or a link between items is updated in either the file-of-reference or in one of the third-party files, that updated information can be propagated back to all of the third-parties for further use in their software applications.

Methods and systems disclosed herein relate generally to data processing by applying machine learning techniques to iteration data to identify anomaly subsets of iteration data. More specifically, iteration data for individual iterations of a workflow involving a set of tasks may contain a client data set, client-associated sparse indicators and their classifications, and a set of processing times for the set of tasks performed in that iteration of the workflow. These individual iterations of the workflow may also be associated with particular data sources. Using the iteration data, anomaly subsets within the iteration data can be identified, such as data items resulting from systematic error associated with particular data sources, sets of sparse indicators to be validated or double-checked, or tasks that are associated with long processing times. The anomaly subsets can be provided in a generated communication or report in order to optimize future iterations of the workflow.

A method for identifying a user among a plurality of users of a multimedia system comprising extracting an i-vector for the speech utterance using total variability modeling, comparing the extracted i-vector with a collection of i-vector sets in order to identify a target set most similar to the extracted i-vector, and granting access to the multimedia system in accordance with an access profile associated with the identified target set. Further, source variation is minimized by, for each speech utterance acquired using a specific data source, re-centering first-order statistics of the speech utterance around the mean of an informative prior associated with the source, and using the co-variance of the informative prior associated with the source when extracting the i-vector for the speech utterance.

A native data collection component may be implemented as a tool, appliance, application and / or utility, and including physical and / or logical implementations thereof. The native data collection component may be responsible for data orchestration, data collection, and aggregation and distribution of collected data from among multiple sources of a storage area network (SAN). The native data collection component is not required to be installed as an agent on any data source of the SAN, and the native data collection component may be independent of a particular data source and act as an independent performance characteristic collection mechanism. In an embodiment, the native data collection component may include three devices / sub-components: a data orchestration device, a data collection interface and a data aggregation and distribution device. Each sub-component may be service based and communication with each service may be done using state-less protocols.

A process, method, and system includes determining if a user has access to a data source. In response to the user being denied access to the data source, a determination is made concerning which upgrade packages would allow the user to access the particular data source.

The invention provides a block chain data networked storage and transfer method. The storage agent layer is inserted into the block chain node, a block chain data storage read-write request is sent tothe storage agent layer, and then the storage agent layer selects a plurality of data sources such as a local file library, a network file library or a relational database to access block chain dataaccording to configuration; through a data source distribution mechanism of the storage agent layer, specific block chain data can be configured into a specific data source, and part of the data sources are allowed to be offline, so that data transfer of the block chain is realized, and the problem of storage pressure of a block chain data production environment is solved.

A method and apparatus for processing data, the data including a set of one or more system inputs; and a set of one or more system outputs; wherein each system output corresponds to a respective system input. Each system input can include a plurality of data points, such that at least one of these data points is from a different data source to at least one other of those data points. The method includes performing a kernel function on a given system input from the data and a further system input to provide kernelised data; and inferring a value indicative of a significance of data from a particular data source; wherein the inferring includes applying a regression technique to the kernelised data.

A serial interface controller (200) provides for transferring data between a data source having a least one channel (110) and a processor. The serial interface controller (200) has a plurality of control registers (220); the control registers (220) in turn include a data structure for configuring the serial interface controller (200) for a data transfer. That data structure further comprises a field for selectively setting the serial interface controller (200) in its run mode or its configuration mode; a field for storing the I / O mode of the serial interface controller (200); a field for storing the address of the active data channel; and, a field for storing the system clock rate. In the preferred embodiment, the control registers (220) include fields for device identification, a flag for the run or configure mode, a I / O-mode control, a value for the channels active (in multi-channel implementations), the data source clock rate, the ADC clock rate, channel-status flags, the CIC decimation rate, the number of taps for FIR filters, and the filter coefficients corresponding to the number of FIR taps in a particular data source.

The invention provides a big data trust management system based on a distributed collaborative trust management framework, and relates to the field of big data evaluation management, and the system comprises a trust processing agent which is used for calculating and storing the direct credibility of a direct management data source; the big data demander is used for sending an acquisition request for the comprehensive credibility of the specific data source to the trust processing agent; and the trust processing agent is also used for querying a result in the direct credibility stored by the trust processing agent based on the acquisition request for the specific data source, calculating the comprehensive credibility of the specific data source according to the query result and outputting the comprehensive credibility to the big data demander. The technical problems of multi-dimensional attributes and uncertainty existing in trust evaluation of big data nodes in a big data environment are solved.