67 results about "Specific data source" patented technology

Enabling dynamic aggregation of content from a plurality of content providers. The invention stores references associated with specific display areas in a document for a particular data source. Responsive to a request for the document, the invention retrieves the references associated with the data source and dynamically inserts the references into the appropriate display area of the document. A client renders the document by obtaining the content associated with the references. In an embodiment, the invention includes a web service for cobranding a login user interface for a user authentication system. The web service places cobranding content provided by an affiliate content provider and sign-in user interface content provided by a user authentication service into different frames of a single web page.

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.

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.

Disclosed are embodiments of a system for optimizing query processing in a federated information system. The system may be used to identify alternative query plans in a simulated environment and to calculate cost estimates associated with the alternative query plans, based not only on database statistics and query statements, but also based on workload and processing latencies associated with specific data source and with the federated information system as a whole. In addition the calculated cost estimates may also factor in data source availability and reliability. The system may use the alternative query plans and the associated cost estimates to influence query processing in a federated information system by feeding to the federated information system query plans that allow for cost-efficient query plan-level load distribution, cost-efficient query fragment plan-level load distribution, and load distribution based upon quality of service cost constraints.

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.

Disclosed are embodiments of a system for optimizing query processing in a federated information system. The system may be used to identify alternative query plans in a simulated environment and to calculate cost estimates associated with the alternative query plans, based not only on database statistics and query statements, but also based on workload and processing latencies associated with specific data source and with the federated information system as a whole. In addition the calculated cost estimates may also factor in data source availability and reliability. The system may use the alternative query plans and the associated cost estimates to influence query processing in a federated information system by feeding to the federated information system query plans that allow for cost-efficient query plan-level load distribution, cost-efficient query fragment plan-level load distribution, and load distribution based upon quality of service cost constraints.

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.

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 system, method and database design is provided for unifying data from a plurality of heterogeneous databases, each having business-context related data and a data access mechanism. A database is created (e.g., the UniDimNet) which contains a node for each dimension of an industry. For each data source which is accessible via the system, a set of data source specific dimensions is created and mapped to the corresponding industry business context dimension(s). A set of templates (e.g., UniViews) is created to query the data sources. Each UniView contains a specific question for a specific dimension designed for a specific data source. UniViews query the database they are associated with by using the data access mechanism of the associated database. A central server coordinates the system and facilitates use of the system through an interface (e.g., the UniViewer). The UniViewer allows a user to query the data sources by identifying an industry business context dimension, a dimension instance and at least one UniView. Multiple UniViews can be combined, cached and saved to facilitate complex queries.

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.

The invention relates to a construction and network resource collection method of a self-adaption network resource collection system, in particular to a construction and network resource collection method of a network resource collection system related to universal open source software projects. According to the method, a network resource collection module and a crawler relying module are included, and corresponding crawler execution units can be configured for the network resource collection module for execution of resource collection according to the relying relation between the network resource collection module established through the crawler relying module and target network resources. Thus, the method has the advantages that the method can adapt to the target network resources of different data types and is high in universality; relying of a specific data source on a certain single-purpose crawler program is decoupled, and high extendibility is achieved.

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.

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.

A data acquisition and processing platform system for Industrial Internet of Things (IIoT) analysis and control, the system configured to receive data from a plurality of data sources having data streams with different properties, the system having an architecture comprising a plurality of platform installations, each installation comprising a node, and the system comprising: a data ingestion subsystem having a plurality of data receivers, each of the plurality of data receivers adapted to acquire data from specific data sources; a routing subsystem and a message bus subsystem, the routing and message bus subsystems together forming a communication backbone of the system; a signal identification subsystem, closely interconnected with a data processing subsystem, and configured to form a separate data stream of alarms; and a user interface (UI) backend, configured to provide front-end applications, including information and actionable insights to the end users; wherein the system architecture is scalable and reliable and configured for continuous handling of data streaming from various data sources.

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.

Systems and methods for defining a composite view and using the definition of the composite view to obtain, aggregate, analyze, and present data from a variety of data sources to a user. These systems and methods may allow for the definition of a visual framework to aggregate and display related data. This visual framework, or composite view, may in turn be composed of a master view and a set of subviews, each of which may display data collected from a particular data source according to a particular format. By interacting with the master view data from a variety of data sources can be displayed.

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 relates to a relaxation search and optimization sequencing method based on form characteristic, comprising firstly using a form information collector to obtain a plurality of relative search form information; constructing a triple information relative to each attribute ranking; according to a relative method in fit with a mode, mapping attributes with different attribute names and the same semantic to a same attribute; filtering the attribute appearing in a certain specific data source; using a suggested formula to compute comprehensive ranking of each attribute; reordering according to the comprehensive ranking of all attributes; and filtering the relaxation result information ranking. The ordering and filtering method is improved, only the attribute influencing the similarity is computed in distance value, and the efficiency of processing the relaxation result ranking is improved.

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.

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.