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1276 results about "Relational table" patented technology

Method, system, and computer program product for visualizing a data structure

A data structure visualization tool visualizes a data structure such as a decision table classifier. A data file based on a data set of relational data is stored as a relational table, where each row represents an aggregate of all the records for each combination of values of the attributes used. Once loaded into memory, an inducer is used to construct a hierarchy of levels, called a decision table classifier, where each successive level in the hierarchy has two fewer attributes. Besides a column for each attribute, there is a column for the record count (or more generally, sum of record weights), and a column containing a vector of probabilities (each probability gives the proportion of records in each class). Finally, at the top-most level, a single row represents all the data. The decision table classifier is then passed to the visualization tool for display and the decision table classifier is visualized. By building a representative scene graph adaptively, the visualization application never loads the whole data set into memory. Interactive techniques, such as drill-down and drill-through are used view further levels of detail or to retrieve some subset of the original data. The decision table visualizer helps a user understand the importance of specific attribute values for classification.
Owner:RPX CORP +1

Methods and apparatus for storing and manipulating variable length and fixed length data elements as a sequence of fixed length integers

Apparatus for storing and processing a plurality of data items each comprising supplied data values organized in one or more fields each of which stores typed data. Character strings and natural language text are converted to numerical token values in an array of fixed length integers and other forms of typed data (real numbers, dates, times, boolean values, etc.) are also converted to integer form and stored in the array. Stored metadata specifies the data type of all data in the integer array to enable each integer to be rapidly accessed and interpreted. When fixed length data types are present, the metadata specifies location, size and type of each fixed length element. When variable length data is stored in the integer array, size and location data stored in the integer array is accessed to rapidly and directly access the variable size data. The presence of implicit or explicit size information for each data structure, including variable size structures, speeds processing by eliminating the need to scan the data for delimiters, and by reducing the processing needed to perform memory allocation, data movement, lookup operations and data addressing functions. Data stored in the integer array is subdivided into items, and items are subdivided into fields. Items may be organized into more complex data structures, such as relational tables, hierarchical object structures, linked lists and trees, and the like, using special fields called links which identify other referenced items.
Owner:CALL CHARLES G

Mapping of an RDBMS schema onto a multidimensional data model

A Relational Database Management System (RDBMS) having any arbitrary structure is translated into a multi-dimensional data model suitable for performing OLAP operations upon. If a relational table defining the relational model includes any tables with cardinality of 1,1 or 0,1, the tables are merged into a single table. If the relational table is not normalized, then normalization is performed and a relationship between the original table and the normalized table is created. If the relational table is normalized, but not by dependence between columns, such as in the dimension table in a snowflake schema, the normalization process is performed using the foreign key in order to generate the normalized table. Once the normalized table is generated, OLAP measures are derived from the normalized relational table by an automated method. In addition, OLAP dimensions are derived from the normalized relational table and the results of the OLAP measures derivation by an automated method according to the present invention. According to an aspect, it is possible to associate a member of a dimension to another member of the same or another dimension. According to another aspect, it is possible to create a new dimension of analysis, the members of which are all the different values that a scalar expression can take on. According to yet another aspect, it is possible to access the various instances of a Reporting Object as members in an OLAP dimension. According to the yet another aspect, it is possible to apply opaque filters or a combination of them to the data that underlies analysis.
Owner:BUSINESS OBJECTS SOFTWARE

Mapping of an RDBMS schema onto a multidimensional data model

InactiveUS20050015360A1Functional dependencyEasy to createData processing applicationsDigital data processing detailsSnowflake schemaRelational model
A Relational Database Management System (RDBMS) having any arbitrary structure is translated into a multi-dimensional data model suitable for performing OLAP operations upon. If a relational table defining the relational model includes any tables with cardinality of 1,1 or 0,1, the tables are merged into a single table. If the relational table is not normalized, then normalization is performed and a relationship between the original table and the normalized table is created. If the relational table is normalized, but not by dependence between columns, such as in the dimension table in a snowflake schema, the normalization process is performed using the foreign key in order to generate the normalized table. Once the normalized table is generated, OLAP measures are derived from the normalized relational table by an automated method. In addition, OLAP dimensions are derived from the normalized relational table and the results of the OLAP measures derivation by an automated method according to the present invention. According to an aspect, it is possible to associate a member of a dimension to another member of the same or another dimension. According to another aspect, it is possible to create a new dimension of analysis, the members of which are all the different values that a scalar expression can take on. According to yet another aspect, it is possible to access the various instances of a Reporting Object as members in an OLAP dimension. According to the yet another aspect, it is possible to apply opaque filters or a combination of them to the data that underlies analysis.
Owner:BUSINESS OBJECTS SOFTWARE

SQL language extensions for modifying collection-valued and scalar valued columns in a single statement

A technique for updating collection-valued and other complex structured columns in a nested table using a nested extension of an UPDATE statement that uses syntax and semantics to modify collection-valued columns in a way that is analogous to the syntax and semantics of the UPDATE statement that is used to modify scalar-valued columns of the table (called the outer UPDATE). Using the same syntactic and semantic constructs as the table at the outer level allows an existing implementation that processes modifications to relational tables to reuse its implementation techniques for processing outer updates to modify collection-valued columns as well. The UPDATE extensions enable the specification of updates to nested collections embedded at arbitrary levels of depth in the object model. The new syntax is embedded inside the outer UPDATE statement in a way that parallels the structure of the data itself and thus maps more directly to the user's conceptual model of the data. The method for implementing the UPDATE extensions uses a change descriptor, which is a data structure that aggregates substantially all changes, both scalar and collection-valued into a single value that can be applied to the changed collection-valued column. This technique can also be used for modifications to other kinds of complex-structured columns such as objects or xml. The change descriptor includes hierarchical information for the cell, thereby enabling efficient application of multiple updates at various granularity levels in a single operation and enabling the implementation of efficient index maintenance algorithms by updating only the indexes affected by the UPDATE operation and updating only those index rows that were affected by the UPDATE operation.
Owner:MICROSOFT TECH LICENSING LLC

Method, device and system for communicating among different types of networks

The invention discloses a method, a device and a system for communicating among different types of networks, belonging to the communication field. The method comprises the steps of: distributing a unique identification in whole network for all devices in a registering process, establishing a correspondence table between the identification and the registered information, receiving a data frame carrying identifications of a source device and a target device, searching the correspondence table according to the identification of the target device and obtaining corresponding registered information, wherein the corresponding registered information at least comprises the type and the address of a subnet which the target device belongs to, and the network address and the device number of the target device; and converting the frame format of the data frame into the frame format corresponding to the subnet which the target device belongs to, in the converted data frame, packaging the address and the network address of the subnet which the target device belongs to, and forwarding to the target device. The device comprises a registering module, a receiving module, an acquiring module, a converting module and a sending module. The system comprises an intelligent gateway and a server. The invention realizes the communication among the different types of networks, especially communication among networks with different network address formats.
Owner:BEIJING RTMAP TECH
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