2703results about "Digital data" patented technology

Methods and apparatus consistent with the invention provide the ability to organize and build understandings of machine data generated by a variety of information-processing environments. Machine data is a product of information-processing systems (e.g., activity logs, configuration files, messages, database records) and represents the evidence of particular events that have taken place and been recorded in raw data format. In one embodiment, machine data is turned into a machine data web by organizing machine data into events and then linking events together.

The present invention relates to a system and method for problem solving using intelligent agents. The intelligent agents may be embodied as processor-readable software code stored on a processor-readable medium. The intelligent agents may include a brain agent to parse the input and direct the parsed input query to other intelligent agents within the system. The apparatus and method may use, for example, a personality agent, a language agent, a knowledge agent, a mood agent, a visual agent, sound agent, a tactile agent, and a smell / taste agent and various connectors to external data sources or other intelligent systems to interpret questions and provide responses back to the user. The apparatus and method may further parse questions in a conceptual manner. The apparatus and method may further optimize its system performance by evolving with and reacting to specific user interactions. Thus, the present invention may be configured to receive a human question and to output a human answer.

A system and method for generating context vectors for use in storage and retrieval of documents and other information items. Context vectors represent conceptual relationships among information items by quantitative means. A neural network operates on a training corpus of records to develop relationship-based context vectors based on word proximity and co-importance using a technique of “windowed co-occurrence”. Relationships among context vectors are deterministic, so that a context vector set has one logical solution, although it may have a plurality of physical solutions. No human knowledge, thesaurus, synonym list, knowledge base, or conceptual hierarchy, is required. Summary vectors of records may be clustered to reduce searching time, by forming a tree of clustered nodes. Once the context vectors are determined, records may be retrieved using a query interface that allows a user to specify content terms, Boolean terms, and / or document feedback. The present invention further facilitates visualization of textual information by translating context vectors into visual and graphical representations. Thus, a user can explore visual representations of meaning, and can apply human visual pattern recognition skills to document searches.

A method and system for entering information into a software application resident on a mobile communication facility is provided. The method and system may include recording speech presented by a user using a mobile communication facility resident capture facility, transmitting the recording through a wireless communication facility to a speech recognition facility, transmitting information relating to the software application to the speech recognition facility, generating results utilizing the speech recognition facility using an unstructured language model based at least in part on the information relating to the software application and the recording, transmitting the results to the mobile communications facility, loading the results into the software application and simultaneously displaying the results as a set of words and as a set of application results based on those words.

A computer-based method and a system for indexing, querying, and ranking documents based on layout are provided. The method includes providing a plurality of documents to computer memory, extracting layout blocks from the provided documents, clustering the layout blocks into a plurality of layout block clusters, computing a representative block for each of the layout block clusters, generating a document index for each provided document based on the layout blocks of the document and the computed representatives blocks, clustering the created document indexes into a plurality of document index clusters, and generating a representative cluster index for each of the document index clusters. The indexes generated, together with the representative blocks and document index clusters, can be stored and used for retrieval of documents responsive to a layout query.

Analog processors for solving various computational problems are provided. Such analog processors comprise a plurality of quantum devices, arranged in a lattice, together with a plurality of coupling devices. The analog processors further comprise bias control systems each configured to apply a local effective bias on a corresponding quantum device. A set of coupling devices in the plurality of coupling devices is configured to couple nearest-neighbor quantum devices in the lattice. Another set of coupling devices is configured to couple next-nearest neighbor quantum devices. The analog processors further comprise a plurality of coupling control systems each configured to tune the coupling value of a corresponding coupling device in the plurality of coupling devices to a coupling. Such quantum processors further comprise a set of readout devices each configured to measure the information from a corresponding quantum device in the plurality of quantum devices.

Documents from a data stream are clustered by first generating a feature vector for each document. A set of cluster centroids (e.g., feature vectors of their corresponding clusters) are retrieved from a memory based on the feature vector of the document using a locality sensitive hashing function. The centroids may be retrieved by retrieving a set of cluster identifiers from a cluster table, the cluster identifiers each indicative of a respective cluster centroid, and retrieving the cluster centroids corresponding to the retrieved cluster identifiers from a memory. Documents may then be clustered into one or more of the candidate clusters using distance measures from the feature vector of the document to the cluster centroids.