Abstract: For validating information provided in a conversation, apparatus, methods, and program products are disclosed. The apparatus includes an association module that associates a plurality of items of caller identification data with a caller, an information module that identifies, using a speech recognition application, caller information from speech of the caller during a telephonic conversation with a call recipient, a comparison module that compares the plurality of items of caller identification data with the caller information, and a validation module that calculates a confidence score based on the comparison of the plurality of items of caller identification data with the caller information and presents, to the call recipient, the confidence score.

Abstract: A system and method for the matching of database records based on the similarity between fields in the database records and fields in the search queries is provided. A set of database records may be received from a search engine for further refinement of the search results. The database records may be assigned matching strength points, based on comparisons of fields in the search query and fields in the database records. The records that do not meet predetermined qualifying criteria, based on the matching strength points, may be rejected. The remaining records may be merged together, based on the similarity between fields of the remaining records.

Abstract: In one embodiment, a method includes receiving a search query and parsing the search query to identify one or more terms to optionalize, searching one or more data stores to identify a plurality of objects, including a second set of objects associated with the online social network that matches one or more of the search terms and does not match at least one of the optionalized terms, scoring each of the identified objects, where for each object of the second set of objects the score calculated by the scoring algorithm is based on one or more fuzzy matching terms of the object corresponding to one or more optionalized terms of the search query, respectively, and sending a search-results page to the client system of the first user.

Abstract: A method and system for improving a data storage system is provided. The method includes extracting original data storage attributes from metadata comprised by data for storage within a hardware storage system. Additional data storage attributes associated with current storage requirements of the data are retrieved and merged with the original data storage attributes resulting in a group of combined data storage attributes. An attribute matrix categorizing attribute types each attribute is generated. A digital tag defining the attribute matrix is generated and attached to the metadata. Data storage tier definitions and associated tier attributes are received and associated with the digital tag. Resulting specified tiers of the hardware storage system a defined for storage of specified portions of the data and each portion of data is stored within an associated tier.

Abstract: A system and method of dynamic backup policy generation based upon a user's behavior is provided. The method may include detecting a user's usage pattern of files within a computing system based upon the user's backup or restore activities. In some embodiments, the backup system may identify the files that have been modified and calculate the percentage of modification away from a predetermined baseline or another previously stored version. The system may generate a list of the identified files along with these percentages to form the user's usage pattern. The method may further include generating a user's profile including files having high access rates in accordance with this usage pattern and adjusting a backup policy based upon the user's profile such that these files are backed-up more frequently. The backup policy may also be adjusted based upon a detected level of risk associated with the user.

Abstract: A method for use in an issue creation process in an issue tracking system includes receiving an issue description comprising keywords, querying a database of historic issue data representing historic issues maintained by the issue tracking system, the historic issues defined by at least a request type and request data. Querying comprises searching the database of historic issue data using the keywords, locating one or more historic issues that include the keywords in its request data, extracting the request type of each of the located historic issues, selecting request types based on a popularity of each request type amongst the located historic issues, generating a list of possible request types for allocation to the issue description, and allocating a particular request type to an issue corresponding to the issue description in response to receiving input that selects the particular request type from among the list of possible request types.

Abstract: This disclosure relates to a development and application of a deep-learning neural network (DNN) model for identifying relevance of an information item returned by a search engine in response to a search query by a user, with respect to the search query and a profile for the user. The DNN model includes a set of neural networks arranged to learn correlations between queries, search results, and user profiles using dense numerical word or character embeddings and based on training targets derived from a historical search log containing queries, search results, and user-click data. The DNN model help identifying search results that are relevant to users according to their profiles.

Abstract: A computer-implemented method according to one embodiment includes identifying a plurality of different summaries for a single instance of content, calculating a relevancy score for each of the plurality of different summaries, and selecting one of the plurality of different summaries, based on the relevancy score for each of the plurality of different summaries.

Abstract: Digital information is transferred between an application that processes a plurality of on-line transactions executed on the mainframe computer and a file system of an operating system. A programmable processor identifies the data held in memory under control of the application. The programmable processor calls a first routine to associate a portion of the data with a container of the application and calls a second routine to dynamically allocate a file of the file system. The programmable processor opens the file of the file system and calls an input/output routine of the operating system to transfer the data associated with the container to the file of the file system.

Abstract: A method for restoring a target file system in a storage system by a computer system, the computer system being connected to a network, the storage system including a tier of sequential access media, the method includes receiving a backup image including metadata of a file of the target file system, from a remote computer system via the network, the metadata indicating a sequential access medium, and restoring the metadata of the target file system using the backup image, the target file system being restored on the computer system by sharing a resource with a native file system operating on the computer system.

Abstract: A system with methodology for dynamic modular ontology. In one embodiment, for example, a method comprises: receiving a command from an analyst to create a new ontology module; receiving, from the analyst, a selection of a first ontology module to import into the new ontology module; receiving, from the analyst, a selection of a second ontology module to import into the new ontology module; detecting an ambiguous data type definition conflict between a first definition of a data type in the first ontology module and a second definition of the data type in the second ontology module; generating a third definition of the data type reflecting a resolution of the ambiguous data type definition conflict; and storing, in a data container, the new ontology module comprising the third definition of the data type.

Abstract: Systems for rule-based data protection of virtualized computing entities. A method embodiment commences upon receiving specification parameters that correspond to one or more data protection schemes or data protection configurations such as schemes for making backups or snapshots. Based on the specification parameters and the data protection configurations, one or more resource entities associated with the data protection configurations are identified. Each of the resource entities are accessed and one or more applicable data protection administration rules that correspond to the respective resource entities are applied. The resource entities might be organized hierarchically. Determination of which data protection administration rules are applicable to the resource entities is based on the type of resource entity being considered. The combination of the resource entity type and respective applicable rules is used to generate entity-specific data protection commands.

Abstract: A method of separating read operations from write operations includes obtaining and storing a client ID after establishing a slave database connection with a slave database corresponding to a client, and receiving an operation request from the client. If the operation request is a write request, the method also includes establishing a master database connection with a master database by use of a public ID and a public passcode and sending the client ID to the master database, where upon receiving, the master database updates the public ID with the received client ID, and updates access permissions associated with the public ID with access permissions associated with the client ID. The method further includes sending the write request to the master database by use of the master database connection, where a write operation corresponding to the write request and to the access permissions associated with client ID is executed.

Abstract: Performing replication of snapshots between storage systems is disclosed. A request to store at a destination system a snapshot data to represent at the destination system a state of a set of data at a first point-in-time is received. A first source system snapshot data that represents at a source system the state of the set of data at the first point-in-time depends on a second source system snapshot data that represents at the source system a state of the set of data at a second point-in-time. The snapshot data to represent at the destination system the state of the set of data at the first point-in-time is determined based on data comprising the first source system snapshot data and a destination system snapshot data that represents at the destination system a state of the set of data at a third point-in-time.

Abstract: Systems, products and methods for enabling symptom verification. Verifying a symptom may include eliminating repeated symptom definitions or eliminating symptoms having low accuracy. A computer system enables verification of a symptom including a rule for detecting a set of events related to a given problem. The computer system includes a symptom database which stores the symptom, a specimen database which stores a specimen including a set of events detected according to a rule of a certain symptom, and an analysis unit which analyzes the specimen stored in the specimen database using a new symptom in order to determine whether to add the new symptom to the symptom database. The present disclosure also includes a method and a computer program for enabling verification of a symptom including a rule for detecting a set of events related to a given problem.

Abstract: An audio file is transformed into a Gabor spectrogram. This is used to compare the audio file to a database of audio files, each represented as a Gabor spectrogram. Before two spectrograms are compared, they are aligned. The spectrograms are broken into blocks and individual Gabor vectors in the blocks are compared. Similarities are stored and an aggregate similarity value is derived for the block. After a series of such comparisons and shifting of the secondary spectrogram block, essentially a running window, an offset value is determined. This offset is used to align the two spectrograms at which stage the spectrograms can be compared in a more effective and meaningful manner. A set of observables is derived from the comparisons and the primary spectrogram is classified in way suitable for the application environment.

Abstract: Physiology-based selection of performance enhancing music for a specific individual is disclosed. Internal effort data and external work data both measured from a user performing an exercise while listening to a specific music track are obtained. The internal effort data describes a measured bodily input of the user, and the external work data describes a measured output effect of the user. A comparison between the internal effort data and the external work data is performed. At least one performance enhancing music track for the user is selected based on the comparison.

Abstract: A method for document similarity analysis. The method includes generating a reference document content identifier for a reference document, including identifying frequently occurring terms in reference document content, encoding each frequently occurring term in a term identifier and combining the term identifiers to form the reference document content identifier associated with the reference document. The method also includes obtaining at least one document similarity value by comparing the reference document content identifier to a set of archived document content identifiers stored in a document repository.

Abstract: A technique preserves efficiency for replication of data between a source node of a source cluster (“source”) and a destination node of a destination cluster (“destination”) of a clustered network. Replication in the clustered network may be effected by leveraging global in-line deduplication at the source to identify and avoid copying duplicate data from the source to the destination. To ensure that the copy of the data on the destination is synchronized with the data received at the source, the source creates a snapshot of the data for use as a baseline copy at the destination. Thereafter, new data received at the source that differs from the baseline snapshot are transmitted and copied to the destination. In addition, the source and destination nodes negotiate to establish a mapping of name-to-data when transferring data (i.e., an extent) between the clusters.

Abstract: Embodiments of the invention provide systems and methods for analyzing sequential data. Analyzing the sequential data can include grouping or clustering data that are similar in some way, e.g., similar ranges of quantities, similar categories, etc. More specifically, a method for hierarchical clustering of sequential data can comprise creating a dotplot of the sequential data. The dotplot can represent a plurality of sequences within the sequential data. A number of clusters represented by the plurality of sequences can be initialized, e.g., one cluster per sequence. A pair of sequences of the plurality of sequences having a longest sequential match can be identified, e.g., based on a line fitting technique, and merged into a single cluster. Identifying a pair of sequences of the plurality of sequences having a longest sequential match and merging the identified pair of sequences into a single cluster can be repeated until a single cluster remains.