18336 results about "Data structure" patented technology

A voice-enabled document system facilitates execution of service delivery operations by eliminating the need for manual or visual interaction during information retrieval by an operator. Access to voice-enabled documents can facilitate operations for mobile vendors, on-site or field-service repairs, medical service providers, food service providers, and the like. Service providers can access the voice-enabled documents by using a client device to retrieve the document, display it on a screen, and, via voice commands initiate playback of selected audio files containing information derived from text data objects selected from the document. Data structures that are components of a voice-enabled document include audio playback files and a logical association that links the audio playback files to user-selectable fields, and to a set of voice commands.

A system, including software components, that efficiently and dynamically analyzes changes to data sources, including application programs, within an integration environment and simultaneously re-codes dynamic adapters between the data sources is disclosed. The system also monitors at least two of said data sources to detect similarities within the data structures of said data sources and generates new dynamic adapters to integrate said at least two of said data sources. The system also provides real time error validation of dynamic adapters as well as performance optimization of newly created dynamic adapters that have been generated under changing environmental conditions.

A method and a system for information extraction from Web pages formatted with markup languages such as HTML [8]. A method and system for interactively and visually describing information patterns of interest based on visualized sample Web pages [5,6,16-29]. A method and data structure for representing and storing these patterns [1]. A method and system for extracting information corresponding to a set of previously defined patterns from Web pages [2], and a method for transforming the extracted data into XML is described. Each pattern is defined via the (interactive) specification of one or more filters. Two or more filters for the same pattern contribute disjunctively to the pattern definition [3], that is, an actual pattern describes the set of all targets specified by any of its filters. A method and for extracting relevant elements from Web pages by interpreting and executing a previously defined wrapper program of the above form on an input Web page [9-14] and producing as output the extracted elements represented in a suitable data structure. A method and system for automatically translating said output into XML format by exploiting the hierarchical structure of the patterns and by using pattern names as XML tags is described.

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.

In a radio access network (24) a femto radio base station (28_f) comprises a resident receiver (54) which acquires system information broadcast in a radio access network (24). At least part of the system information is used for building, at the femto radio base station (28_f), a neighbor data structure (59) comprising information for neighboring cells. The neighbor data structure (59) is then used for building a neighbor list. The neighbor list is subsequently transmitted from the femto radio base station (28_f) to a user equipment unit (30) served by the femto radio base station (28_f). In some example embodiments and modes, the femto radio base station (28_f) reports the neighbor data structure to a network node (26, 100) other than the femto radio base station. The other node (26, 100) uses the neighbor data structure for building the neighbor list at the other node. In some example embodiments and modes, acquisition of the system information comprises scanning a surrounding macro coverage area of the femto radio base station for obtaining cell identity information for detected cells. In other example embodiments and modes, the acquisition of the system information can additionally comprise camping on a macro cell and using/consulting at least one system information block in the camped-on macro cell is consulted/used for obtaining information about at least one neighboring cell.

Methods and apparatus for storing erase counts in a non-volatile memory of a non-volatile memory system are disclosed. According to one aspect of the present invention, a data structure in a non-volatile memory includes a first indicator that provides an indication of a number of times a first block of a plurality of blocks in a non-volatile memory has been erased. The data structure also includes a header that is arranged to contain information relating to the blocks in the non-volatile memory.

Connection objects or other such data structures facilitate establishing and configuring connections between objects that model components in a process control system. A first set of data structures (e.g. the object connection type structures) identify valid types for component-to-component pairings and the respective roles of each component in the pairing (e.g., parent or child, source or sink). A second set of data structures (e.g., the parameter connection type structures) supply similar information for parameter-to-parameter connections. Together, these data structures can be used, for example, to validate component-to-component connections suggested by the user and to automatically configure parameter-to-parameter connections. Actual connections, both at the component or parameter level, are reflected using parameter overrides within the parameterized object model—with which the connection objects are constructed.

A keymap service architecture for a distributed storage system. A system may implement storage nodes configured to store replicas of data objects, where each of the replicas is accessible via a respective locator value, and keymap instances each configured to store keymap entries corresponding respectively to the data objects. A given keymap entry may indicate a mapping from a given key value corresponding to a given data object to each respective locator value of its replicas. Each of the keymap instances may store a replica of the given keymap entry and may index its respective stored keymap entries within a respective index data structure including hierarchically arranged index nodes corresponding to keymap entries. For a given keymap entry having a given corresponding index node, each tag value associated with each ancestor of the given corresponding index node may be a prefix of the given key value.

A method for taking snapshots of data. In an embodiment, a first map data structure is obtained that records locations for a plurality of data blocks. A second map data structure is formed that is initially empty of locations, the second map data structure representing the snapshot after the snapshot is started. Writes on data that arrive before the snapshot starts are applied to the first map, and writes that arrive after the snapshot starts are applied to the second map.

A knowledge-based natural speech dialogue system includes: (i) a knowledge support system, (ii) a flexible dialogue control system, and (iii) a context information system. Flexibilities of the conversation structure, inherent in mixed-initiative mode for dealing with complex user request, are managed because the knowledge structures involved are represented by additional, powerful knowledge representation tools, and because the context information is retained by more specific data structures, which covers larger temporal scopes by the logic of the conversation, rather than by a fixed locality of the grammar flow. This system provides a simple yet reliable method to compensate for these factors to enable more powerful conversation engines with mixed-initiative capabilities.

Techniques for concurrent access to a resource object, such as a database, include generating a lock data structure for a particular resource object. The lock data structure includes data values for a resource object identification, a lock type, and a version number. The version number is related to a number of changes to the resource object since the lock data structure was generated. A request is received from a requesting process. The request is for a requested lock type for access to the particular resource object. It is determined whether to grant the request based on the requested lock type and the lock type in the lock data structure. By carrying a lock version number in a lock data structure managed by a lock manager, improved optimistic locking is provided in a database. In particular, the approach enables introduction of optimistic locking to a legacy database without requiring burdensome changes to a database table schema.

The present invention relates to a method and apparatus based on Bloom filters for detecting predefined signatures (a string of bytes) in a network packet payload. A Bloom filter is a data structure for representing a set of strings in order to support membership queries. Hardware Bloom filters isolate all packets that potentially contain predefined signatures. Another independent process eliminates false positives produced by the Bloom filters. The system is implemented on a FPGA platform, resulting in a set of 10,000 strings being scanned in the network data at the line speed of 2.4 Gbps.

The invention provides systems and methods for continuous back up of data stored on a computer network. To this end the systems of the invention include a synchronization process that replicates selected source data files data stored on the network and to create a corresponding set of replicated data files, called the target data files, that are stored on a back up server. This synchronization process builds a baseline data structure of target data files. In parallel to this synchronization process, the system includes a dynamic replication process that includes a plurality of agents, each of which monitors a portion of the source data files to detect and capture, at the byte-level, changes to the source data files. Each agent may record the changes to a respective journal file, and as the dynamic replication process detects that the journal files contain data, the journal files are transferred or copied to the back up server so that the captured changes can be written to the appropriate ones of the target data files.

A filesystem-aware storage system locates and analyzes host filesystem data structures in order to determine storage usage of the host filesystem. To this end, the storage system might locate an operating system partition, parse the operating system partion to locate its data structures, and parse the operating system data structures to locate the host filesystem data structures. The storage system manages data storage based on the storage usage of the host file system. The storage system can use the storage usage information to identify storage areas that are no longer being used by the host filesystem and reclaim those areas for additional data storage capacity. Also, the storage system can identify the types of data stored by the host filesystem and manage data storage based on the data types, such as selecting a storage layout and/or an encoding scheme for the data based on the data type.