Abstract: Methods and systems are described for preventing a message from being sent to an unintended recipient. A first context data structure is generated for a first conversation, a second context data structure is created for a second conversation, and then a message input is received as intended for the first conversation. The message is correlated with each of the first context data structures and the second context data structure to determine a relevance score corresponding to each of the first and second conversation. The relevance scores are compared and if the relevance score for the first conversation is greater than the relevance score for the second conversation, the message is sent; however, if the relevance score for the second conversation is greater than the relevance score for the first conversation, the message is not sent and the message is prevented from being sent to, for example, an unintended recipient.

Abstract: In a rack comprising a group of servers and at least two top-of-rack switches, a link fault is detected. A smart data cable connects each of the servers to both top-of-rack switches. A control signal indicates an active communication path from one of the top-of-rack switches to the servers. In response to detecting a failure of the active communication path, the control signal indicates a switch to the second of the top-of-rack switches. In response to the updated control signal, a switching mechanism of the data cable changes the active communication path to the second of the top-of-rack switches.

Abstract: Systems and methods for managing incremental data backups on an object store. A computing device receives first data representing a changed chunk of data in a revision of a data volume on a storage device, the changed chunk includes data having changes from previous data of a previous revision. The computing device creates a block of data representing a copy of the changed chunk on the object store, the object store also includes a previous revision block representing previous revision data. The computing device determines a previous index stored on the object store corresponding to the previous revision, which includes entries including at least one corresponding to the previous revision block. The computing device creates a copy of at least one previous index from the object store, and a revised index that updates the corresponding entry with updated entry data representing the change block.

Abstract: Automatically mapping unlabeled input data onto a target schema via semantic type detection is described. The input data includes data elements that are structured as 2D table rows and columns forming cells. Each data element is included in a cell. The target schema includes a set of fields. Schema mapping includes mapping each column to one or more fields. More particularly, the fields are clustered into field clusters, where each field cluster includes one or more of the fields. Each column is automatically mapped to one of the field clusters of the set of field clusters. The mapping between schema fields and data columns is automatically performed based on appropriate pairings of the detected semantic types, where the semantic types are encoded in vector representations of the fields, the field clusters, and the data elements.

Abstract: A method of associating data from a plurality of databases is disclosed. The method comprises accessing a first database comprising a first dataset and a second database comprising a second dataset. The method further comprises identifying a first set of expressions and a second set of expressions corresponding to the first dataset and the second dataset, respectively. The method further comprises determining a first set of clusters and a second set of clusters corresponding to the first database and the second database, respectively. Furthermore, the method comprises creating a relational database based on a set of relationships and a mapping function determined based on the first set of clusters and the second set of clusters.

Abstract: Disclosed are systems and methods for improving interactions with and between computers searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The methods and systems analyze digital message content in digital communication systems to automatically identify shared user interest(s), to automatically create computerized relationship matrix data identifying user connections, or relationships, using identified shared user interest(s), and to automatically provide a recommendation using the shared user interest and user relationships formed using the shared user interest.

Abstract: Provided are systems and methods that can extract part data from a PLM database and suggest changes to the manufacturing of the part. In one example, the method may include querying a database for a plurality of values of a part to be manufactured from a plurality of fields of computer-aided design (CAD) file stored in the database, mapping the plurality of fields of the CAD file to a plurality of corresponding fields of a host platform based on a type of the database, extracting the plurality of values from the CAD file and transferring the plurality of values to the mapped plurality of corresponding fields of the host platform, determining changes to one or more manufacturing attributes of the part to be manufactured based on the transferred plurality of values, and outputting the changes to a display.

Abstract: The present disclosure provides a cooperative access method, system, and architecture of an external storage.

Abstract: A machine learning system includes encoder and decoder networks. The machine learning system is configured to obtain input data, which includes sensor data and a radius of an p norm ball of admissible perturbations. Input bounding data is generated based on the input data. First bounding data and second bounding data are generated by respectively propagating the input bounding data on first and second outputs of the encoder network. Third bounding data is generated in association with a latent variable based on the first bounding data and the second bounding data. Fourth bounding data is generated by propagating the third bounding data on an output of the decoder network. A robustness certificate is established with respect to the input data by generating a lower bound of an evidence lower bound based on the first, second, third, and fourth bounding data.

Abstract: Techniques herein store database blocks (DBBs) in byte-addressable persistent memory (PMEM) and prevent tearing without deadlocking or waiting. In an embodiment, a computer hosts a DBMS. A reader process of the DBMS obtains, without locking and from metadata in PMEM, a first memory address for directly accessing a current version, which is a particular version, of a DBB in PMEM. Concurrently and without locking: a) the reader process reads the particular version of the DBB in PMEM, and b) a writer process of the DBMS replaces, in the metadata in PMEM, the first memory address with a second memory address for directly accessing a new version of the DBB in PMEM. In an embodiment, a computer performs without locking: a) storing, in PMEM, a DBB, b) copying into volatile memory, or reading, an image of the DBB, and c) detecting whether the image of the DBB is torn.

Abstract: Briefly, example methods, apparatuses, devices, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more processing devices to facilitate and/or support one or more operations and/or techniques to access entries in a hash table. In a particular implementation, a hash operation may be selected from between or among multiple hash operations to map key values to entries in a hash table.

Abstract: Persistent storage may contain: (i) a database table containing entries, (ii) a definition of a communication endpoint of a remote system, and (iii) outbound flow processing. One or more processors may be configured to: detect a state change associated with a local entry in the database table; read, from the database table, a set of data representing the local entry; transform, using the outbound flow processing, the set of data into a format receivable by the remote system; create, for the set of data, a correlation record that contains a local correlation identifier, wherein the correlation record specifies the local entry; transmit, to the remote system, the set of data as transformed and the local correlation identifier; receive, from the remote system and for the set of data, a remote correlation identifier; add, to the correlation record, the remote correlation identifier; and write, to a correlation table, the correlation record.

Abstract: Methods and systems are described herein for synchronizing communication records in computer networks. For example, the methods and systems may determine whether or not a first communication relates to a second and generate a recommendation that the communications relate to a single communication. In particular, the methods and systems described herein describe synchronizing communication records in computer networks based on detecting patterns in categories of metadata. For example, the methods and systems retrieve specific types of metadata and compare this metadata between communications in order to synchronize and/or deduplicate them.

Abstract: Apparatus for determining a meaning of an ontology term, the apparatus including an electronic processing device that compares the ontology term to a number of potential ontology term meanings, generates a matching score for the results of each comparison, the matching score being based on a similarity of the ontology term and the potential ontology term meaning and selects a potential ontology term as the ontology term meaning using the matching scores.

Abstract: Selecting tables for compression by threshold statistical values. Identified tables are reordered according to fields having the lowest cardinality to increase the size of character strings replaced by keys during compression. Field locations are mapped between the original table and the reordered table. Dictionary-based compression is performed on reordered tables.

Abstract: A system is provided for electronic data compression by automated time-dependent compression algorithm. In particular, the system may track instances in which a particular dataset is used, copied, or accessed over time. For certain datasets (e.g., datasets that have not been accessed for a threshold amount of time), the system may use a time-based compression algorithm that progressively removes the least significant bits of such datasets as time passes. The compression of the datasets may continue until the system detects that further compression would cause the dataset to be unreadable or unrecoverable. In this way, the system may minimize the computing resources allocated to storing datasets that are not frequently accessed.

Abstract: There is disclosed a method and system for identifying relevant training data points for a prediction by a machine learning algorithm (MLA). The method comprises determining indicators of influence for training data points used to train the MLA. A normalizing function is applied to the indicators of influence to determine normalized indicators of influence. Training data points having the highest and lowest normalized indicators of influence are output for display.

Abstract: A computer-based method and scoring system for management of metadata is provided.

Abstract: A method performed by a block-storage server, of storing data is described. The method includes (1) receiving, from a remote file server, data blocks to be written to persistent block storage managed by the block-storage server; (2) receiving, from the remote file server, metadata describing files to which the data blocks belong in a set of filesystems managed by the remote file server; and (3) selectively applying data reduction when storing the data blocks in the persistent block storage based, at least in part, on the received metadata. An apparatus, system, and computer program product for performing a similar method are also provided.

Abstract: The present disclosure relates to a method and an apparatus for representation of a sparse matrix in a neural network. In some embodiments, an exemplary operation unit includes a buffer for storing a representation of a sparse matrix in a neural network, a sparse engine communicatively coupled with the buffer, and a processing array communicatively coupled with the sparse engine. The sparse engine includes circuitry to: read the representation of the sparse matrix from the buffer, the representation comprising a first level bitmap, a second level bitmap, and an element array; decompress the first level bitmap to determine whether a block of the sparse matrix comprises a non-zero element; and in response to the block comprising a non-zero element, decompress the second level bitmap using the element array to obtain the block of the sparse matrix. The processing array includes circuitry to execute the neural network with the sparse matrix.