Abstract: An information processing apparatus and method, and a program, which are capable of conducting a search more easily and at a higher speed. The information processing apparatus includes a control unit configured to designate a designated section and a designated sound source of an audio signal including sounds of a plurality of sound sources, and configured to obtain a search result of a sound source signal similar to a signal of the designated sound source, the sound source signal having been searched for on the basis of the signal of the designated sound source in the designated section of the audio signal. The present technology is applicable to the information processing apparatus.

Abstract: A computing machine receives a plurality of observations. The computing machine generates an observation data structure. The computing machine extends, in accordance with the causal structures and hierarchical relationships, the observation data structure to include predicted states or predicted actions that are not from the plurality of observations. The computing machine reduces, in accordance with consistency rules stored in a memory of the computing machine, the extended observation data structure. The computing machine provides an output associated with the reduced observation data structure.

Abstract: A search method, a terminal and a server are provided. The server returns a similar image (namely, a second image) of a first image to the terminal. When displaying the second image, the terminal further displays controls of a plurality of attributes corresponding to the second image. When the terminal detects that a user operates a first control corresponding to the second image on an interface, the terminal triggers the server to obtain first attribute information of the second image, where the first attribute information corresponds to the first control.

Abstract: Method for controlling data quality assurance after a migration between a source repository, which includes source data associated with a source data structure, and a target repository, which includes target data associated with a target data structure, according to migration rules. The target data is organized as a set of elements. The method includes simulating the migration by applying migration rules to source data so as to output simulated data according to the target data structure, where the simulated data is organized as a set of elements. The method includes merging the simulated data and the target data by excluding identical elements, to form an input vector for a machine learning algorithm. The method includes applying the machine learning algorithm for pairing elements of the input vector according to a similarity score and determining a discrepancies indicator according to the similarity score for each element of the input vector.

Abstract: A computer-implemented method, system and computer program product for generating a visual transformation of a business analytic artifact. Features from a received business analytic artifact (e.g., dashboard) are extracted. Furthermore, constraints are determined for a transformed representation of the business analytic artifact. A heuristic-based search is then performed on a space of possible transformed representations of the business analytic artifact using the extracted features to identify a transformed version that satisfies the determined constraints and maximizes readability. A final score is then generated for each possible transformed representation of the business analytic artifact based on the extent that the transformed version satisfies the determined constraints and maximizes the readability. The transformed representation of the business analytic artifact that has the highest score is selected and displayed on the target device.

Abstract: Systems and methods to automatically classify records managed by a collaboration environment are described herein. Exemplary implementations may perform one or more of: obtain model training information including model training input information and training output information, the training input information including a subset of work unit information included in records, the training output information including hierarchical information and/or clustering information included in records; train a machine learning model based on the model training information to generate a trained model configured to output classifications within hierarchies and/or clusters; store the train model; and/or other operations.

Abstract: Systems and methods are disclosed for automatically extracting keys and corresponding values in any type of source document. Extracting desired words from the tokens in any type of document is based on a uniform approach to represent the source document. This uniform representation encodes features of the desired tokens along with the neighborhood information so that values associated with a given key can be extracted. The disclosed technique learns the representation of tokens independent of source document type and the learned representation is then used to determine relationships between multiple tokens. The neighborhood information and position information are used to determine various relationships between keys and values.

Abstract: Systems and methods for monitoring and managing versioning changes to computational workflows caused by ongoing development of computational modules implemented within the computational workflows. Exemplary implementations may: store a workflow repository and a user repository; monitor the workflow repository to detect changes to computational modules included in the workflow repository; responsive to detections of changes to the computational modules, identify computational workflows defined by workflow definitions impacted by the detected changes; identify, based on information included in the user repository, users associated with the identified computational workflows; manage information defining user interfaces associated with individual users; update information defining the user interfaces based on the detected changes and the identified users; effectuate presentation of the user interfaces to the users; and/or other exemplary implementations.

Abstract: In various embodiments, a natural language (NL) application receives a first incomplete natural language (NL) request, and generates one or more request completion recommendations based on at least the first incomplete NL request and a first recommendation model, where the first recommendation model is generated via a machine learning algorithm applied to a first data dependency model and a first request completion model. The NL application receives a selection of a first request completion recommendation included in the one or more request completion recommendations, generates a complete request based on the first incomplete NL request and the first request completion recommendation, and causes the complete request to be applied to the data storage system.

Abstract: The present disclosure involves systems, software, and computer implemented methods for automatically extending a partially-editable dataset copy. One example method includes identifying, for a data set, extension filter criteria that extends a current filter that defines an editable portion of the data set. An extended filter is automatically generated for the data set based on the extension filter criteria and the current filter. Additional data is copied into the partially-editable copy of the data set based on the extended filter and the current filter to generate an updated partially-editable copy of the data set. The current filter is replaced with the extended filter to create a new current filter. An updated exposed view is generated using the new current filter that exposes the updated partially-editable copy of the data set and an updated non-editable portion of the data set.

Abstract: Systems and methods are disclosed for processing data. The system represents semantic data in the semantic data storage using a schema native to Cloud Analytical Data Store (CADS) based on data defining a semantic model. The system modifies the schema based on a detected change in the semantic model. The system writes semantic data into the CADS, wherein the semantic data is formatted according to the schema using at least one of: (a) bulk load, or (b) a sequence of write requests. The system receives a semantic query. The system translates the semantic query into a translated query in a CADS-native format, wherein the translated query is formatted according to the schema. The system causes the CADS to provide an answer to the translated query based on data contained in the CADS.

Abstract: Methods and systems are provided for enhanced data loss prevention. Data loss prevention may be applied to data that includes a plurality of records and a plurality of categories, with each record including a plurality of fields and each field corresponding to a different one of the categories. Applying of data loss prevention may include selecting a subset of records from the plurality of records; scanning fields of the selected subset of records for sensitive information; computing based on a result of the scanning, for each category, a likelihood the category contains the sensitive information; selecting a subset of categories based on the computed likelihoods of the categories to contain the sensitive information; searching the sensitive information in the selected subset of categories; and in response to detection of sensitive information in at least one of the subset of records, taking one or more data loss prevention related actions.

Abstract: An asset monitoring system receives a first multi-dimensional representation of an asset associated with an industrial process. The asset monitoring system generates a second multi-dimensional representation of the asset from the first multi-dimensional representation. The second multi-dimensional representation may be a two-dimensional vector graphic representation of the asset and may be configurable via a graphical user interface. In generating the second multi-dimensional representation, the asset monitoring system maps at least one operational parameter associated with the asset to the second multi-dimensional representation. The asset may include one or more devices of the asset monitoring system. The asset monitoring system may display, via a dashboard at the graphical user interface, the second multi-dimensional representation and status information associated with the asset.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for automatic database configuration. One example method includes receiving, at a database associated with a data warehouse application, a request to generate a configuration to acquire data objects based on executing calls to corresponding programming interfaces provided by a source application, wherein the programming interfaces are identified in the received instructions and are associated with acquiring the data objects associated with metadata entities defined at the database; in response to the received instructions, configuring the database to automatically execute one or more calls to acquire relevant data for a metadata entity defined at the database, wherein the metadata entity is associated with a section of a first programming interface; and invoking the first programming interface at the source application, wherein invoking the first programming interface results in acquiring the relevant data.

Abstract: Systems and methods for neural machine translation are provided. In one example, a neural machine translation system translates text and comprises processors and a memory storing instructions that, when executed by at least one processor among the processors, cause the system to perform operations comprising, at least, obtaining a text as an input to a neural network system, supplementing the input text with meta information as an extra input to the neural network system, and delivering an output of the neural network system to a user as a translation of the input text, leveraging the meta information for translation.

Abstract: Described herein is a system and method for providing an integrated function editor, for use with a data analytics environment. The function editor can be utilized to create and register functions available within a cloud infrastructure or cloud environment, for use within a data analytics environment. Such functions available for use within the cloud infrastructure or cloud environment can be displayed for the user, and used, for example, in data analytics workbooks, to create an interface or API that allows connection of the data analytics environment to a cloud infrastructure database.

Abstract: A database system operates by: determining a first query that indicates a first request to generate a K nearest neighbors (KNN) model; executing the first query to generate KNN model data for the KNN model, wherein the KNN model data is set as a reduced dataset for one of a plurality of training iterations; determining a second query that indicates a second request to apply the KNN model to input data; and executing the second query to generate model output of the KNN model for the input data based on, for each row in the input data, identifying a classification label for the each row from the discrete set of labels based on performing the KNN classification algorithm to classify the each row in the input data by applying the reduced data set.

Abstract: An apparatus for classifying an entity to an executable data structure, the apparatus including a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive entity input from an entity using a graphical user interface, wherein receiving the entity data includes receiving a low-level entity data at a first time and receiving a high-level entity data at a subsequent time determine a degree of interaction pertaining to the entity by comparing the low-level entity data to the high-level entity data, identify at least a protocol metric as a function of the degree of interaction, determine a protocol object as a function of the high-level entity data and the at least a protocol metric, establish an executable data structure for the entity as a function of the protocol object and display the executable data structure using the graphical user interface.

Abstract: The present disclosure provides techniques and solutions for sorting data. In a particular implementation, a sorting technique is provided that places values in a sorted order by adding an offset value to values that are not in a sorted order. The resulting sorted set of values is not truly sorted, in that the set of modified values is sorted, but the underlying data itself is not sorted. In another implementation, a sorting technique can use multiple streams or sets. When an out of order element is encountered, it can be added to a new stream, if such a stream is available. The sorting techniques can be used for a variety of purposes, including provided sorted data for use in generating summary data, or for providing sorted data to be used in determining an intersection between two datasets.

Abstract: Methods and systems for managing distribution of data are disclosed. The data may be distributed by edge systems to processing systems. The data may be distributed using a data pipeline. The data pipeline may include functionality to process data using different modalities depending on the type of data and operable connectivity between the edge systems and processing systems. By modifying the manner in which the data is processed, limitations in operable connectivity may be managed and a broader array of different types of data may be more efficiently distributed.