Abstract: A continuously updated database is enhanced with virtual dynamic representations of taxonomic groups of records stored in the database. Each record of the database contains a vertical field that identifies a unique entity associated with that record and a horizontal attribute upon which a business decision, related to the corresponding unique entity, may be based. A taxonomic group of database records are defined for each distinct value of the vertical field, and all records in a particular taxonomic group contain a most desirable value of the horizontal field associated with that group's corresponding vertical-field value. The system creates and maintains a virtual representative of each taxonomic group that is automatically updated as the database is updated.

Abstract: In accordance with an embodiment, described herein is a system and method for determining and displaying a list of suggested search items for a search field based on prior user interaction. A suggestion curator provided at a client device can display a plurality of suggested search items to a user who is performing a search. The system can display the plurality of suggested search items in an order that is based on a rating associated with each item. The rating can be assigned to each search item upon its selection by the user, and adjusted in response to subsequent search item selections by the user. The system can be configured to adjust each rating by different amounts based on metadata describing how recently the search item was last selected by the user. The system can then re-order the plurality of suggested search items in accordance with the adjusted ratings.

Abstract: A data analysis system executes data analysis in response to a data analysis request from a plurality of data analysis request sources and includes a filtering unit, a data analysis unit, a data storage unit, and a filter control unit. The filtering unit filters input data by applying a predetermined filter to the input data. The data analysis unit analyzes the filtered input data. The data storage unit stores the input data and result data as data that has been analyzed. The filter control unit records application history of a filter applied in response to the data analysis request, and refers to the filter application history for a new data analysis request to select a filter suitable for data analysis to be executed, and transfers the selected filter to the filtering unit.

Abstract: The present disclosure relates to a method using a database engine for migrating data records from a source database to a target database, where said data records are arranged in a sorted source table of the source database in accordance with a clustered-base-table order following the Hilbert-Filling-Curve algorithm. The method comprises configuring the database engine for storing the CBT order of each data record of the source table in a reference table to said source table or a in a column of said source table. A reading step may be performed to read said data records from said source table, wherein in said reading step said stored CBT order is used. The read data and the stored CBT order may be transferred to the target database in accordance with the stored CBT order. The transferred data may be written at the target database in accordance with the CBT order.

Abstract: A real-time recommender method includes receiving streaming data records; applying tokenizer objects to a received data record to identify, extract and buffer data elements. The method applies the buffered data elements to a feature detect tree that includes a root node and one or more subsequent branch nodes, a set of the subsequent branch nodes defining a path culminating in a leaf node, by applying a data element to the root node and testing the data element to reject or select the data element, applying a prior-selected data element to subsequent branch nodes, and conducting at each of the subsequent branch nodes, a test to reject or select the prior-selected data element, and stopping, for a selected path, the applying and testing after the prior-selected data element reaches a path's leaf node. The method still further includes installing each data element reaching the path's leaf node, as a feature, into one or more recommender algorithm models.

Abstract: Disclosed are apparatus and methods for providing images of memory objects. A computing device can receive a plurality of memory objects for one or more executable software components. The computing device can classify the plurality of memory objects in accord with a plurality of object classifications. A particular object classification can represent a probability that a memory object classified with the particular object classification is to be written to during execution of the one or more executable software components. The computing device can order the plurality of memory objects based on the plurality of object classifications. The computing device can provide an image for the one or more executable software components using the computing device, where the image includes the ordered plurality of memory objects.

Abstract: A data processing device according to an embodiment includes a sub-vector group generating unit, a codebook generating unit, and a converting unit. The sub-vector group generating unit generates, from a feature vector set of N number of D-dimensional feature vectors, M number of sub-vector groups (where M<D holds true). Each of the M number of sub-vector groups includes N number of dimension-variable sub-vectors obtained from the N number of D-dimensional feature vectors. For each of the M number of sub-vector groups, the codebook generating unit performs clustering of the N number of dimension-variable sub-vectors, and generates a codebook in which the representative vector of each cluster is associated with an index. The converting unit performs product quantization using the codebook and converts each of the N number of D-dimensional feature vectors into a compressed code made of a combination of M number of indexes.

Abstract: A method for performing network analysis comprising: receiving telemetry information for a computer network, the telemetry information comprising network device state information for internetworking devices in the computer network and network traffic flow information for data packet flows through the computer network; transforming the telemetry information into a temporal graph that is digitally stored in computer memory, wherein the temporal graph comprises a plurality of graph elements include a plurality of vertices and a plurality of edges, each of the vertices representing an internetworking device, each of the edges representing one or more portions of a data packet flow; digitally storing graph element metadata corresponding to the plurality of graph elements in a structured format, the graph element metadata comprising temporal data for each graph element of the plurality of graph elements, the temporal data comprising a modification time value specifying a modification time that is associated with ea

Abstract: A media agent is configured to perform substantially autonomously to initiate, continue, and manage information management operations such as a backup job of a certain client's primary data, manage the operations, and generate and store resultant system-level metadata from the operations, etc. The media agent is configured to do this even when out of communication with the storage manager that manages the information management system. When communications are restored, the media agent reports the relevant metadata to the storage manager. The storage manager comprises corresponding enhancements, including specialized logic for identifying the media agent as an intelligent media agent capable of some autonomous functionality, for transmitting management parameters thereto, and for seamlessly integrating the received metadata into the storage manager's associated management infrastructure such as a management database.

Abstract: Systems and methods are disclosed for managing partial-edit files for shared storage applications. A network-attached storage device (NAS) includes a non-volatile memory module, a network interface, and control circuitry configured to connect to a first client over a network connection using the network interface, receive, from the first client, a request to access a first portion of an existing file stored in the non-volatile memory module, create a first partial-edit file based on the existing file, receive modifications associated with the first portion of the existing file from the first client, modify the first partial-edit file according to the received modifications, and at least partially overwrite the existing file with at least a portion of the first partial-edit file.

Abstract: A machine-readable medium that gathers a plurality of key terms is described. In an exemplary embodiment, the machine-readable medium receives a plurality of terms and selects a plurality of key terms from the plurality of terms, wherein each of the plurality of key terms is a term that is highlighted in a running application. The machine-readable medium further associates a predictive search query for each of the plurality of key terms, wherein the predictive search query is executed when that term is found in a running application and the user selects this term in the running application. The machine-readable medium additionally sends the plurality of key terms to a plurality of devices, wherein each of the plurality of devices matches at least one of the plurality of key terms in that device.

Abstract: According to embodiments of the present invention, machines, systems, methods and computer program products for hardware acceleration are presented. A plurality of computational nodes for processing data is provided, each node performing a corresponding operation for data received at that node. A metric module is used to determine a compression benefit metric pertaining to performance of the corresponding operations of one or more computational nodes with recompressed data. An accelerator module recompresses data for processing by the one or more computational nodes based on the compression benefit metric indicating a benefit gained by using the recompressed data. A distribution function may be used to distribute data among a plurality of nodes.

Abstract: Provided is a process including: sampling of nodes of a first graph; and forming a second graph comprising nodes, each of which corresponds to at least one entity mentioned in unstructured text documents. Forming the second graph comprises, for each pair of the nodes of the second graph, setting a relationship between the pair, the pair comprising (i) a first node corresponding to a first entity and (ii) a second node corresponding to a second entity, by: identifying, in the first graph, a node corresponding to an unstructured text document in which the first entity is mentioned; and setting the relationship between the pair based on a determination of whether or which of the sampled nodes comprises a node satisfying a set of criteria, the criteria comprising (i) having a relationship with the identified node and (ii) corresponding to an unstructured text document in which the second entity is mentioned.

Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.

Abstract: Systems and methods for forming a data table are provided. A data construct comprising a plurality of tokens is obtained. Application of a configuration construct to the tokens labels a first subset of the tokens as header tokens and a second subset of the tokens as value tokens based on the positions of tokens in the first and second subsets in the data construct. Application of the configuration construct associates specific tokens in the first subset to tokens in the second subset based on the relative or absolute position of tokens and/or by delimiters between tokens in the first and second subsets in the data construct. The associating transforms the data construct into the data table in which each token in the first subset is a header and each token in the second subset is a data value in a single column in the data table.

Abstract: Method for supplying data to remotely cultivate a digital content reference library, to be executed by an electronic terminal device capable of visually displaying digital content to a user and communicating with a communications network, comprising establishing, by automatic observation logic, visual characteristics data representing the on-screen appearance of digital content, such as application, shown via a display of the terminal device (406), and transmitting the visual characteristics data to a remote server for updating a digital content reference library thereat linking content identity information with associated visual characteristics data in the received or processed form (408). A compatible method to be executed on the network side is presented as well as related, applicable terminal devices and server arrangements.

Abstract: A method to identify potentially duplicative records in a data set is provided. A computer may collect a data profile for the data set that provides descriptive information with regard to attributes of the data set. Based, at least in part, on the data profile, weights are determined for the attributes. As values of a data record are compared to values of the same respective attributes in other records, the overall likelihood of a match or duplicate, as indicated by the degree of similarity between values, is modified based on the determined weights associated with the respective attributes.

Abstract: The technology disclosed relates to de-duplicating contextually similar news feed items. In particular, it relates to assembling a set of news feed items from a plurality of electronic sources and preprocessing the set to generate normalized news feed items that share common company-name mentions and token occurrences. The normalized news feed items are used to calculate one or more resemblance measures based on a sequence alignment score and/or a hyperlink score. The sequence alignment score determines contextual similarity between news feed item pairs, arranged as sequences, based on a number of matching elements in the news feed item sequences and a number of edit operations, such as insertion, deletion, and substitution, required to match the news feed item sequences. The hyperlink score determines contextual similarity between news feed item pairs by comparing the respective search results retrieved in response to supplying the news feed item pairs to a search engine.

Abstract: Implementations generally relate to providing document analytics. In some implementations, a method includes receiving a plurality of documents related to e-discovery. The method further includes generating a graphical user interface that includes an analytics panel that provides analytics information about the plurality of documents. The method further includes receiving, from one or more users, manual tags for one or more documents of the plurality of documents. The method further includes performing a first iteration that determines a first group of documents that are improperly associated with one or more of the manual tags based on at least one of content and metadata of the plurality of documents. The method further includes performing a second iteration that determines a second group of documents that are improperly associated with one or more of the manual tags based on the reclassification.

Abstract: Techniques for enhancing usability and electronic resource efficiency using comment relevance are disclosed herein. In some embodiments, a comment relevance system receives member feature data, including professional identity data such as professional experience or professional skill, and at least one of comment feature data and commenter feature data for comments for post on a social networking service, generates a score for each comment based on the member feature data and the comment or commenter feature data, ranks the comments based on the scores, and causes one or more of the comments to be displayed in a particular position based on the ranking. In some embodiments, the member feature data comprises professional identity data of a member of the social networking service, the comment feature data indicates at least one attribute of the comment, and the commenter feature data indicates at least one attribute of the commenter of the comment.