Abstract: Optimizing file system resource reservation is presented herein. The method comprises dividing a virtual file system address space into subspaces, initializing the subspaces with volume slices of a group of volume slices comprising a first volume slice, a second volume slice, and a collection of reserved volume slices allocated based on an allocation pattern that allocates volume slices as a function of a quantitative relationship between a first value associated with a first volume slice and a second value associated with a second volume slice, determining that a data block count is insufficient to service a write operation of user data to the second volume slice; and provisioning a second subspace with a free volume slice obtained from the collection of reserved volume slices, and wherein the provisioning of the second subspace with the free volume slice is performed without invoking a memory exclusion mechanism.

Abstract: A method in a data processing system and apparatus for organizing electronic data, structured or unstructured, of one or more users stored across one or more server computers into structures on a recordable medium of a data processing system. The data items are structured in a heterogeneous string structure, and one or more embedded n-dimensional range structure within the heterogeneous string structure. Searching the plurality of string structures can then be done with a query including at least one term and a range threshold. Each data item is associated with a scoring function that is used to filter and rank the matched results.

Abstract: Aspects of the present disclosure provide techniques for intent matching. Embodiments include receiving input of text by a user via a user interface. Embodiments include determining weights for portions of the text based on a plurality of keywords. Embodiment include generating an embedding of the text. Embodiments include determining an intent of the text by weighting, based on the weights, word mover's distances from the embedding of the text to a known embedding of known text associated with the intent in order to determine a similarity measure between the text and the known text. Embodiments include providing content to the user via the user interface based on the intent.

Abstract: A method for generating a seed for a shuffle algorithm, the method performed by a plurality of computing devices and comprising, at each computing device in the plurality, generating a respective plurality of seeds for a shuffle algorithm, determining a fitness score for each of the generated seeds, and identifying a seed among the generated seeds having the best fitness score, wherein the number of generated seeds is determined based on a predetermined limit.

Abstract: Techniques for automatically determining different data types found in databases are disclosed. In one example, a computer implemented method comprises receiving a portion of identifying information for one or more components of a database, and generating one or more descriptions for the one or more components based at least in part on the portion of the identifying information for the one or more components. The one or more descriptions are inputted to one or more machine learning models, and, using the one or more machine learning models, one or more data types associated with the one or more components are predicted. The prediction is based at least in part on the one or more descriptions.

Abstract: The present disclosure provides a generalization processing method, apparatus, device and computer storage medium, and relates to technical field of artificial intelligence and specifically to a deep learning technique. A specific implementation solution is: determining a set of candidate queries in a query library that are similar to a requested query in at least one of a literal matching manner, a semantic matching manner and a query rewriting manner; determining a generalized query corresponding to the requested query from the set of candidate queries by using a pre-trained query matching model; wherein the query matching model is obtained by pre-training based on a cross attention model. The generalization for the requested query can be achieved according to the present disclosure.

Abstract: The present invention relates to a method and system for facilitating access to recorded data. The system comprises an interface and a processing device. The interface is arranged to receive data and the processing device is arranged to separate the received data in data subsets, compress each data subset and assign an identifier to each compressed data subset, thereby creating data units each comprising a compressed data subset and an associated identifier, the processing device further being arranged to establish an index on the basis of the assigned identifiers.

Abstract: A device receives a request associated with standardizing organization-specific roles within an organization, where the request includes data that identifies titles for the organization-specific roles. The device converts the data to vectors that represent semantic meanings of the titles. The device sets a configuration of a data model by assigning weighted values to title-class identifiers that are used to associate titles, of a standardized set of titles, to a hierarchy of role classifications. The device uses the data model to determine scores that indicate likelihoods of the titles mapping to the title-class identifiers. The device identifies, based on scores, a subset of title-class identifiers that associate particular titles, of the standardized set of titles, and particular role classifications. The subset of title-class identifiers is stored in association with information relating to the particular titles. The device performs an action based on the information relating to the particular titles.

Abstract: Systems, methods, and computer-readable media for providing physical rewards from disbursed networked dispensers are disclosed. The systems and methods may involve at least one processor configured to: maintain and cause to be displayed a workflow table having rows, columns and cells; track a workflow milestone via a designated cell configured to maintain data indicating that the workflow milestone is reached; access a data structure storing a rule containing a condition associated with the designated cell and a conditional trigger associated with at least one dispenser; receive an input via the designated cell; compare the input with the condition to determine a match; and activate the conditional trigger to cause at least one dispensing signal to be transmitted over a network to the at least one dispenser to cause the at least one dispenser to dispense a physical item as a result of the milestone being reached.

Abstract: The present technology operates in an application layer of an operating system on a client device of a content management system to monitor for changes to shared content items that are likely unintentional—for example the change might move a content item out of a shared space, or otherwise remove the shared content item from access by other users. The present technology can detect a content item change event on a client device, compare a source file system path for the content item change event with a destination file system path for the content item change event to determine a canonical move causing the content item change event, determine that the canonical move was likely unintentional; and display a notification informing the user that a content item change that was likely unintentional was detected and then allow the user to either confirm or deny (undo) the detected change.

Abstract: A user may submit a search query to a search engine, which may process the search query and generate a set of results. Previous actions of the user or of other users may be used to identify recommended search queries. The recommended search queries may be presented to the user along with the search results for the query. The location of the recommended search queries may be fixed, set by the user, or determined on a query-by-query basis. A user interface element operable to cause the presentation of one or more recommended search queries may be presented after a delay. After an additional or independent delay, the recommended search queries may be presented automatically. The delays may be fixed, set by the user, or determined on a query-by-query basis.

Abstract: When an operation request of a file is made, a first storage system performs an operation of the file stored in the first storage system on the basis of the operation request, describes, in an operation log, a counter value of a management information file, associated with the file on which the operation is to be performed, together with operation content with respect to the file, replies to the operation request, and updates the counter value of the management information file when the file stored in the first storage system is transferred to a second storage system.

Abstract: Some embodiments may perform operations of a process that includes obtaining a natural language text document and use a machine learning model to generate a set of attributes based on a set of machine-learning-model-generated classifications in the document. The process may include performing hierarchical data extraction operations to populate the attributes, where different machine learning models may be used in sequence. The process may include using a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model augmented with a pooling operation to determine a BERT output via a multi-channel transformer model to generate vectors on a per-sentence level or other per-text-section level. The process may include using a finer-grain model to extract quantitative or categorical values of interest, where the context of the per-sentence level may be retained for the finer-grain model.

Abstract: Techniques for improved data services are provided. Upon receiving a first request from a first client, a first timeline comprising a first plurality of events for an asset indicated in the first request is generated. Upon receiving a second request from a second client, a second timeline comprising a second plurality of events is generated. A first submission for the asset is provided to the first client, comprising updating a first graphical user interface (GUI) output on a first device of the first client. Upon determining that the first client approved the first submission, a merged timeline is generated based on the first and second timelines, where the merged timeline includes the first and second pluralities of events, comprising: updating the first GUI output on the first device, and a second GUI output on a second device of the second client, to indicate the merged timeline.

Abstract: Embodiments use successive refinement to allow a user to systematically explore the result set of an arbitrary query over RDF, such as a SPARQL query. A user inputs an arbitrary base query and modifies this query by replacing selected variables with values to which each selected variable is bound within the result set of the base query. Embodiments present, via a GUI, variable facets that may be substituted for query variables. Embodiments also present, through a GUI, a query history graph that represents query versions that a user has created. A user may navigate this query history graph to return to previously-created query versions. The GUI also provides information about the facets, including a number of results that would be included in the result set of the query version resulting from substitution of the facet for the associated variable.

Abstract: A computer system processes a group of inputs. A group of entities that is input for processing is intercepted. The intercepted group is expanded into individual entities. Each of the individual entities is processed to produce results for each individual entity. The results for each individual entity are intercepted and merged to produce results for the group of entities. Embodiments of the present invention further include a method and program product for processing a group of inputs in substantially the same manner described above.

Abstract: A mechanism is provided in a data processing system to implement a cognitive natural language processing (NLP) system with descriptor uniqueness identification to support named entity mention clustering. The mechanism annotates a set of documents from a corpus of documents for entity types and mentions, collects descriptor usages from all documents in the corpus of documents, analyzes the descriptor usages to classify the descriptors as base terms or modifier terms, generates compatibility scores for the descriptors, and performs entity merging of entity clusters based on the compatibility scores.

Abstract: Embodiments are directed towards real time display of event records and extracted values based on at least one extraction rule, such as a regular expression. A user interface may be employed to enable a user to have an extraction rule automatically generate and/or to manually enter an extraction rule. The user may be enabled to manually edit a previously provided extraction rule, which may result in real time display of updated extracted values. The extraction rule may be utilized to extract values from each of a plurality of records, including event records of unstructured machine data. Statistics may be determined for each unique extracted value, and may be displayed to the user in real time. The user interface may also enable the user to select at least one unique extracted value to display those event records that include an extracted value that matches the selected value.

Abstract: A computer system is provided that allows participants to submit agent data structures for processing. The computer system performs a dual sided evaluation process to determine when contra-sided agents match with one another.

Abstract: A facial images retrieval system is provided. The facial images retrieval system is adapted to receive an initial textual description of a facial image to perform an initial facial image search that obtains a plurality of facial images based on the textual description. The facial images retrieval system then receives a selection of the first and second facial images that are relatively close to a desired facial image to perform a further facial image search to obtain another facial image.