Abstract: Systems and methods are disclosed for comparing selections of text to show differences between the two selections. The text may be selected from the same source or from two different sources. In one implementation, a system receives a first selection of text for comparison and places the selection in a first buffer. The system receives a second selection of text for comparison and places the second selection in a second buffer. The system compares the first buffer and the second buffer to determine differences and displays the differences. In some embodiments, the system may allow a user to choose two buffers from among a plurality of buffers for comparison.

Abstract: A database can be instantly recovered by a cluster mapped to the database. Nodes of the cluster are mapped over channels to directories of the database. Scripts are generated from one or more templates that specify the order and values to be executed to perform a database job, such as database recovery. To recover the database, a template is executed that generates and populates scripts, which are processed on the host of the database to recover the database in a nearly instant manner without transferring data files.

Abstract: A system and method for storage checkpointing to a group of independent computer applications. The system has a storage disk that stores files; a storage access interface to access the storage disk; and a computer. The computer runs the group of independent computer applications and utilizes the files stored on the storage disk. A file system on the server accesses the files stored on the storage disk. An operating system and at least one device driver can be called by the file system, and at least one buffer buffers first data written to the storage disk and second data read from the storage disk.

Abstract: A method, an apparatus, a system, and a computer program product for synchronizing databases. A computer system detects first information in a live view on a mobile display system while the first information is displayed by a first service on a data processing system. The first information corresponds to second information managed by a second service. The computer system determines whether a discrepancy is present between the first information displayed on the data processing system and the second information managed by the second service. The computer system performs a number of actions to resolve the discrepancy in response to the discrepancy being present.

Abstract: A computer-implemented system or process is programmed or configured to use a configuration file to specify one or more tasks to apply to raw ingested data. A task may be a sequence of instructions programmed or configured to format raw ingested data into a dataset in a CSV format. Examples of tasks may include: a parser to parse Cobol data into a CSV, a parser to parse XML into a CSV, a parser to parse text using fixed-width fields to a CSV, a parser to parse files in a zip archive into a CSV, a regular expression search/replace function, or formatting logic to remove lines or blank lines from raw ingested data. In one embodiment, the configuration file may specify a schema definition for a task to use for generating a dataset. In one embodiment, the configuration file may also include one or more access control list (ACL) definitions for the generated dataset. In one embodiment, the building of datasets using the configuration file is automated, for example, on a nightly basis.

Abstract: Embodiments of the present specification disclose a method, an apparatus, a system, a device, and a storage medium for answering user questions, including: obtaining a user question; encoding the user question and a schema level of pre-constructed structured data to obtain a first feature vector, wherein the structured data further comprises a data level, wherein the data level comprises knowledge for answering questions structured according to the schema level; retrieving one or more candidate sub-graphs related to the user question from the structured data; encoding the one or more candidate sub-graphs to obtain a second feature vector; performing multi-task classification for the user question based on the first feature vector and the second feature vector; and obtaining answer content for the user question based on a result of the multi-task classification.

Abstract: An agent executing on a processor at a data production site detects filesystem events and creates a list of bookmarks describing the filesystem events in user-understandable strings. Each bookmark is associated with metadata about the filesystem event that includes a timestamp and a point-in-time (PiT) snapshot of the filesystem at the time of occurrence of the event. The bookmarks and associated metadata are transferred to a recovery site and the bookmark set is recorded in storage. The storage can be searched for bookmarks in the set that reference the filename of a file of interest, and the file recovered and replicated using an associated PiT.

Abstract: A serverless data processing architecture may be a high-velocity, cost-efficient and massively scalable log ingest application and event parser that may act as the intermediary between data collection and data analysis and may handle the receipt and parsing of incoming event data generated by collector and sensor applications. The log analytics data science portion of an ingest process may determine if arbitrarily structured log data is anomalous and/or security relevant via single event or multievent algorithms. There are numerous applications for both the single and multi-event log analytics platforms. Any application involving reliably finding anomalous pieces of semi-structured or unstructured text data may provide potential use cases. These processes may be particularly widely applicable because these processes are agnostic to and require no prior knowledge of the structure of the data.

Abstract: A device, system and method for anonymously comparing query images to reference images is provided. A computing device receives, from at least one camera, a query image. The computing device generates a query characteristic vector associated with the query image. The computing device applies a mathematical operator on the query characteristic vector to obtain a query vector. The computing device compares the query vector to a reference vector, the reference vector obtained by applying a complementary mathematical operator on a reference characteristic vector associated with a reference image, the complementary mathematical operator comprising a complement of the mathematical operator. The computing device, in response to the comparing indicating a match between the query vector and the reference vector, provides a notification of the match.

Abstract: A system for processing logs comprising at least one computing device adapted to: receiving a plurality of historical logs each generated by at least one client computing device when executing at least one software object generated from at least one source code file, each of the plurality of historical logs is associated with one of a plurality of sessions and comprising log data and a location value identifying a location in the at least one source code file; generating a plurality of log clusters, each log cluster comprising a plurality of logs of the plurality of historical logs, each of the plurality of logs of the respective log cluster comprising a common location value; and in at least one of a plurality of iterations: receiving from the at least one client computing device, via at least one digital communication network interface connected to the at least one computing device.

Abstract: A cognitive cartography system receives a set of legacy documents, such as maps, in the form of physical hardcopy or as simple graphic images. The system, using rules derived from prior training and experience, revises the documents to resolve formal inconsistences like differences in resolution, orientation, or scale. The system assembles the adjusted documents into a seamless composite document represented as a computerized model. Applying learned rules and logic to contextual information received from extrinsic sources, the system infers semantic meaning from features represented by the composite, such as geographical features of a map. These inferences allow the system to derive new knowledge about the represented features, which is added to the model. When additional documents or contextual information are received, the system further refines the model by repeating this procedure. When the model has been sufficiently refined, the system makes the knowledge available to downstream systems.

Abstract: A method and a server for determining parking suggestions for a destination location on a map comprising: acquiring based on the destination location, a set of past routes having been taken on the map by users and terminating at the destination location. A set of final locations associated with the set of past routes is determined, each final location being an actual ending location of users having taken the respective past route. A road graph including a set of map objects is acquired, where each map object has: a respective object location, a respective object class indicative of a respective type of structure on the map. The set of final locations is then clustered based on the destination location, the respective classes and the respective final locations to obtain a set of clusters on the road graph, where each cluster includes a respective subset of final locations.

Abstract: Attributes of a configuration item record of a configuration management database (CMDB) are received. Based on the received attributes, a determination is made that the configuration item record belongs to a new child class and no longer belongs to a previously identified child class. While maintaining a same identifier in the configuration item record, a classification of the configuration item record is changed to the new child class including by adding one or more attributes of the new child class to the configuration item record and removing one or more attributes of the previously identified child class from the configuration item record.

Abstract: A method is provided for selecting a query execution plan, including: receiving an XML document including a plurality of root nodes and a plurality of leaf nodes; determining root-to-leaf paths based on the plurality of root nodes and the plurality of leaf nodes; generating a prime number for each unique root-to-leaf path; calculating a number of instances in which each prime number appears; generating an XML synopsis based on the prime numbers and the number of instances; determining a comparison between a query tree pattern and the XML synopsis; determining a type of the query tree pattern; calculating for each query tree pattern plan, a selectivity estimate based on the comparison and the type of the query tree pattern; determining an optimal query execution plan based on the selectivity estimate; and selecting the optimal query execution plan for performing a query of the XML document based on the determination.

Abstract: Aspects of the invention include determining whether a first log message written by an application during a first job is a message of interest based on a context of the first log message and a probability that the application writes the message for a same job as the first job. Calculating in response to determining that the first log message is a message of interest and by the processor, a correlation score based on intersecting tokens between the first log message and a second log message. Determining the first log message correlates to the second log message based on comparing the score to a threshold score. Modifying a system log of a mainframe to link the first log message to the second log message based on the correlation.

Abstract: Embodiments may provide techniques for clustering using predefined anchors that take into account the knowledge about the anchors. For example, a method of clustering processing may be implemented in a computer comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, the method comprising: receiving a plurality of points of data to be clustered and a plurality of predefined anchor data points and clustering the plurality of points of data and at least a subset of the predefined anchor data points. Further, the method may include creating a similarity function where anchor points pull stronger than regular points, such that they function as attractors.

Abstract: The present embodiments relate to automated memory creation and retrieval from moment content items. In some implementations, the automated memory creation and retrieval system can obtain moment content items from user-designated sources with a single user perspective or multiple user perspectives. The moment content items can be assigned tags and arranged in chronological order. The arranged moment content items can be clustered into memory content items based on clustering conditions. Once memory content items are created, they can be arranged into a memory hierarchy made up of connected nodes. In some implementations, the memory content items are also linked together based on similarity in various dimensions in a memory graph. The automated memory creation and retrieval system can receive search criteria for memories from a user interface and provide the user with memories from matched nodes in the memory hierarchy or linked memories in the memory graph.

Abstract: A file server receives a request for data from a user device. The data is represented at the file server by a virtual cluster descriptor. The file server queries an identifier map using an identifier of the virtual cluster descriptor. Responsive to the identifier map indicating that the requested data is stored at a location remote from the file server, the file server accesses a cold tier translation table that stores a mapping between an identifier of each of a plurality of virtual cluster descriptors and a storage location of data associated with the respective virtual cluster descriptor. The cold tier translation table is queried using the identifier of the virtual cluster descriptor to identify a storage location of the requested data, and the data is loaded to the file server from the identified storage location.

Abstract: Described are computer-based methods and apparatuses, including computer program products, comprising the steps of, or structure for, storing a plurality of expert profiles in a database, each of the plurality of expert profiles comprising information associated with a person having knowledge in a particular category, subject or topic; receiving search criteria over a network from a query source; selecting at least one of the plurality of expert profiles comprising information that satisfy the search criteria; and transmitting expert profile data for each of the selected expert profiles to the remote search engine, the expert profile data comprising data that defines a displayable representation of a corresponding expert profile, the expert profile data further comprising data that facilitates a client-initiated, real-time communication session over the network with a person associated with the corresponding expert profile.

Abstract: A system and method are provided for indexing and mining content of multiple data sources. The method includes: providing a database of learned content of multiple data sources learned using text analysis, the learned content identifying one or more concepts to which a data source relates, wherein the concepts are cognitively associated with the data source and include concepts not explicitly referenced in the data source and providing an index of the learned content including associations between concepts with mappings between concepts and the multiple data sources. The method further includes receiving input of a query and using text analysis to analyze the query to determine one or more query concepts to which it relates and mining the indexed concepts in response to the query concepts to return a list of referenced data sources.