Abstract: The present disclosure provides an experimentation framework for a computational environment in a distributed system. A machine-learning model may be created that predicts at least one output produced by the computational environment based on at least one input provided to the computational environment. During an evaluation time period that is subsequent to at least one modification being made to the computational environment, at least one modified output produced by the computational environment may be determined. The machine-learning model may be used to calculate at least one predicted output that would have been produced by the computational environment during the evaluation time period if the at least one modification had not been made. A determination may also be made about how the at least one modification affected the computational environment based on a comparison of the at least one modified output and the at least one predicted output.

Abstract: The invention provides a neural network quantization method and device and a related product. The neural network quantization method is used for quantizing data of a computation layer of a neural network. The technical scheme provided by the invention has the advantage of low cost.

Abstract: Systems and methods herein describe accessing a data processing pipeline, causing presentation of the data processing pipeline on a graphical user interface of a computing device; receiving a selection of a first user interface element within the graphical user interface, generating a datafile representing the data processing pipeline, submitting the datafile and an application to a software framework using an application programming interface, receiving, from the application, the generated datasets, applying the data operations the data processing pipeline, collecting performance data metrics from the data processing pipeline, and dynamically updating the graphical user interface with the collected performance data metrics.

Abstract: The present disclosure relates to a new method for cross-modal retrieval via deep binary hashing and quantization. In a training phase, the system simultaneously learns to generate feature vectors, binary codes, and quantization codes for data across two or more modalities that preserves the semantic similarity correlations in the original data. In a prediction phase, the system retrieve a data item in a database that is semantically similar to a query item of a different modality. To identify the database item closest in semantic meaning to the query item, the system first narrows the database search space based on binary hash code distances between each of the database items and the query item. The system then measures the quantization distances between the query items and the database items in the smaller search space. The system identifies database item have the closest quantization distance to the query item as the closest semantic match to the query item.

Abstract: An online system trains machine learning models that, when applied to gathered sensor data, determines personal characteristics (e.g., age, gender, height) of an individual in a non-intrusive manner. Specifically, the online system trains a first machine learning model that analyzes sensor data gathered from a client device associated with the individual. The first machine learning model determines whether a trigger event, such as whether the individual is walking, is currently occurring. A second machine learning model trained by the online system analyzes sensor data corresponding to the trigger event to identify the personal characteristics of the walking individual.

Abstract: A method including bit-operation and sub-code/substring filtering for image searching using a full-text search engine. The method can include determining a first binary vector comprising first binary substrings for a first image. The method also can include obtaining a respective second binary vector comprising second binary substrings for each of second images from a database. The method additionally can include determining a respective substring distance for each of the binary substring for each of the second images. The respective substring distance can be between at least a pair of a first binary substring of the first binary substrings of the first binary vector and a respective corresponding second binary substring of the second binary substrings of the respective second binary vector for each of the second images.

Abstract: Techniques for schema mismatch detection and evolution are described. When data is being uploaded into a source table, schema of the data to be uploaded can be compared with the schema for the source table. If a schema mismatch is detected, the schema of the source table can be modified, and the upload can be continued without data loss.

Abstract: Various embodiments provide methods, systems, apparatus, computer program products, and/or the like for managing, ingesting, monitoring, updating, and/or extracting/retrieving information/data associated with an electronic record (ER) stored in an ER data store and/or accessing information/data from the ER data store, wherein the ERs are generated, updated/modified, and/or accessed via a graph-based domain ontology.

Abstract: A cloud computing system can be configured to generate data models. A model optimizer of the cloud computing system can provision computing resources of the cloud computing system with a data model. A dataset generator of the cloud computing system can generate a synthetic dataset for training the data model. The computing resources can train the data model using the synthetic dataset. The model optimizer can store the data model and metadata of the data model in a model storage. The cloud computing system can receive production data from a data source by a production instance of the cloud computing system using a common file system. The production data can be processed using the data model by the production instance. The computing resources, the dataset generator, and the model optimizer can be hosted by separate virtual computing instances of the cloud computing system.

Abstract: A method including receiving a feature vector of an unknown sample, computing a MinHash of the unknown sample based on Jaccard-compatible features, querying a Locality Sensitive Hashing forest of known samples with the MinHash of the unknown sample to identify a first subset of known samples that are similar to the unknown sample, receiving for each individual known sample in the first subset, a feature vector including non-Jaccard distance-compatible features, computing a first sub-distance and a second sub-distance between the unknown sample and the known samples in the first subset, calculating a total distance for each known sample in the first subset by combining the first and the second sub-distances, identifying, based on the calculated total distances, a second subset of known samples that are most similar to the unknown sample, and classifying the unknown sample based on the second subset.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a predictive system that obtains and processes data describing terms for different medical concepts to generate commands from a user query. An entity module of the system determines whether a term describes a medical entity associated with a healthcare condition affecting an individual. When the term describes the medical entity an encoding module links the medical entity with a specified category based on an encoding scheme. The system receives the user query. A parsing engine of the system uses the received query to generate a machine-readable command by parsing the query against terms that describe the medical entity and based on the encoding scheme for linking the medical entity to the specified category. The system uses the command to query different databases to obtain data for generating a response to the received query.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for responding to a query. In some implementations, a computer obtains a query. The computer determines a meaning for each term in the query. The computer determines user data for the user that submitted the query. The computer identifies one or more ontologies based on the meanings for at least some of the terms. The computer identifies a knowledge graph based on the identified ontologies and the user data. The computer generates a response to the query by traversing a path of the identified knowledge graph to identify items in the knowledge graph based on the determined meaning for each of the terms. The computer generates path data that represents the path taken by the computer through the identified knowledge graph. The computer provides the generated response and the path data to the client device.

Abstract: Various embodiments provide methods, systems, apparatus, computer program products, and/or the like for managing, ingesting, monitoring, updating, and/or extracting/retrieving information/data associated with an electronic record (ER) stored in an ER data store and/or accessing information/data from the ER data store, wherein the ERs are generated, updated/modified, and/or accessed via a graph-based domain ontology.

Abstract: Various embodiments provide methods, systems, apparatus, computer program products, and/or the like for managing, ingesting, monitoring, updating, and/or extracting/retrieving information/data associated with an electronic record (ER) stored in an ER data store and/or accessing information/data from the ER data store, wherein the ERs are generated, updated/modified, and/or accessed via a graph-based domain ontology.

Abstract: A method, a device, and a non-transitory storage medium are described in which a network performance optimization service is provided. A load balancer device may receive, from an end device, an application service request for an application service that is available from multiple server devices of an application layer network. The load balancer device may determine, from a source identifier associated with the end device and obtained from the application service request, that the source identifier does not map to a network traffic forwarding rule of a set of stored network traffic forwarding rules. In response, the load balancer device may map the source identifier to an application service profile of a set of stored application service profiles; select, based on the application service profile, a first server device of the multiple server devices and establish the first server device to be the destination of the application service request.

Abstract: A system and method for the estimation of the cardinality of large sets of transaction trace data is disclosed. The estimation is based on HyperLogLog data sketches that are capable to store cardinality relevant data of large sets with low and fixed memory requirements. The disclosure contains improvements to the known analysis methods for HyperLogLog data sketches that provide improved relative error behavior by eliminating a cardinality range dependent bias of the relative error. A new analysis method for HyperLogLog data structures is shown that uses maximum likelihood analysis methods on a Poisson based approximated probability model. In addition, a variant of the new analysis model is disclosed that uses multiple HyperLogLog data structured to directly provide estimation results for set operations like intersections or relative complement directly from the HyperLogLog input data.

Abstract: A system for document extraction and targeted dissection, the system comprising: a memory device; a communication device; and a processing device configured to: receive a first document via communication channel over the network; extract user information from a first data field of the first document, wherein the first data field has a first data type and a first data format; store the user information and the first document in a document database; identify a second document comprising a second data field, wherein the second data field has the first data type; populate, automatically, the second data field of the second document with the extracted user information; display the second document in an electronic presentation via a user interface of a user device; and augment the electronic presentation of the second document in the user interface with supplemental data associated with the second document.

Abstract: System, device, and method for generating and utilizing content-aware metadata, particularly for playback of video and other content items. A method includes: receiving a video file, and receiving content-aware metadata about visual objects that are depicted in said video file; and dynamically adjusting or modifying playback of that video file, on a video playback device, based on the content-aware metadata. The modifications include content-aware cropping, summarizing, watermarking, overlaying of other content elements, modifying playback speed, adding user-selectable indicators or areas around or near visual objects to cause a pre-defined action upon user selection, or other adjustments or modification. Optionally, a modified and content-aware version of the video file is automatically generated or stored. Optionally, the content-aware metadata is stored internally or integrally within the video file, in its header or as a private channel; or is stored in an accompanying file.

Abstract: The present invention discloses a method and control system for monitoring plurality of equipment in industrial plant connected over SNMP based network. Each of plurality of equipment is associated with a server which is communicatively connected with client. One or more equipment which are capable of reporting monitoring objects are identified using a configuration file. Further, polling for monitoring objects based on capability data associated with one or more equipment is performed. Secure configuration of plurality of equipment in SNMP based network is achieved. Management of network traffic is performed. Unauthorized extraction of monitoring objects is reduced in the network.

Abstract: The subject matter described herein relates to table detection in a spreadsheet. According to implementations of the subject matter described herein, there is proposed a solution for determining a table in a spreadsheet. In the solution, respective multiple attributes of multiple cells comprised in the spreadsheet may be extracted. Respective features of the multiple cells may be determined based on the extracted multiple attributes. The multiple cells may be divided into at least one candidate area based on the features. At least one candidate table in the spreadsheet may be determined based on the at least one candidate area. By means of the solution, respective features of the multiple cells comprised in the spreadsheet may be determined based on the respective attributes of the multiple cells, and further, a candidate region where a table might exist may be determined based on the respective features of the multiple cells.

Abstract: Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising receiving, at a stream processor, an event, the stream processor including a plurality of processing stages; generating, by the stream processor, an augmented event based on the event, the augmented event including at least one additional field not appearing in the event, the additional field generated by an operation selected from the group consisting of a join or dimensional annotation operation; and emitting, by the stream processor, the augmented event to downstream consumer.

Abstract: Embodiments of the present application provide a video recording method and device. The method includes: receiving, by an application of a mobile terminal, a video recording instruction of a user; generating, according to a photographing scene, a video stream that can be edited according to segments, the video stream including at least one frame sequence segment; and uploading the edited video stream to a server. According to the present application, by generating a video stream consisting of at least one frame sequence segment during video recording, where the generated video stream can be edited according to segments, the error tolerance of video capture is improved, and the costs of later video editing are reduced.

Abstract: An example module includes: a radio to communicate with a sensor; a communication interface to communicate with a second module; a chassis to mate with the second module; and a processor connected to the radio, the communication interface, and a memory, the processor to execute instructions stored in the memory. The instructions are to: receive, via the radio, sensor data from the sensor; process the sensor data to generate processed sensor data; and transmit the processed sensor data to a remote device.

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system provides a programmatic interface, referred to herein in some embodiments as a foreign function interface, by which a user or third-party can define a service, functional and business types, semantic actions, and patterns or predefined complex data flows based on functional and business types, in a declarative manner, to extend the functionality of the system.

Abstract: Provided are techniques for generating and customizing summarized notes. A template is selected from a plurality of templates based on a context using a machine learning model. The template includes one or more translatable string resources with variables to represent key attributes extracted from historical notes. A summarized note is generated using values of the key attributes for the variables in the translatable string resources of the template.

Abstract: Techniques for generating and searching semantic flow graphs are provided that include creating, by a system operatively coupled to a processor employing a semantic flow graph creation process, a semantic flow graph based on an ontology associated with a set of subjects and a raw flow graph determined from an analysis of a data set relating to the set of subjects and searching, by the system, the semantic flow graph to determine a subset of information of the semantic flow graph that is responsive to a query based on the query and information of the semantic flow graph.

Abstract: The present teaching relates to a system and method for providing a response to a query related to a data sketch. A local data sketch is obtained in response to a synchronization parameter being set to a first value. The data sketch is updated based on the obtained local data sketch. The synchronization parameter is set to a second value that is different than the first value and thereafter propagated. A response to a query is generated based on the updated data sketch.

Abstract: The present teaching relates to a method and system generating a data sketch. A plurality of local data sketches are generated, wherein for each local data sketch, it is determined whether a propagation condition is satisfied. In response to the condition being satisfied, the local data sketch is processed when a synchronization parameter satisfies a criterion. The synchronization parameter is set to a predetermined value to enable propagation of the local data sketch to the data sketch. Upon the local data sketch being propagated to the data sketch, the above steps are repeated.

Abstract: The present invention relates to execution optimization of database queries. Herein are techniques for optimal execution based on query interpretation by translation to a domain specific language (DSL), with optimizations such as partial evaluation, abstract syntax tree (AST) rewriting, just in time (JIT) compilation, dynamic profiling, speculative logic, and Futamura projection. In an embodiment, a database management system (DBMS) that is hosted on a computer generates a query tree that represents a database query that contains an expression that is represented by a subtree of the query tree. The DBMS generates a sequence of DSL instructions that represents the subtree. The sequence of DSL instructions is executed to evaluate the expression during execution of the database query. In an embodiment, an AST is generated from the sequence of DSL instructions. In an embodiment, the DSL AST is optimally rewritten based on a runtime feedback loop that includes dynamic profiling information.

Abstract: Managed access to file system objects enables an application to request access to a file system object via a file system transformer driver, which may extend the capabilities of a file system. The file system transformer driver may be configured to convert a data file format for the file system object to a data format requested by the application. The file system transformer driver may store the file system object in an internal data format using a file system on a storage device. The file system transformer driver may receive requests from applications via an operating system instruction.

Abstract: One or more processors store rules for performing rules-based cleaning operations on a plurality of datasets, wherein each rule comprises one or more functions to be executed against a dataset during the rules-based cleaning operations, the one or more functions each having one or more associated conditions and actions, wherein the one or more actions are performed on the dataset responsive to the one or more associated conditions being satisfied. The one or more processors further apply the rules to each of the plurality of datasets to perform the rules-based cleaning operations. To apply the rules to a given dataset, the one or more processors identify an ordered list of the one or more functions to be executed with respect to the given dataset during the rules-based cleaning operations and determine, for each of the one or more functions, whether the given dataset satisfies one or more conditions associated with a respective function of the one or more functions.

Abstract: Embodiments of the present disclosure relate to flattening hierarchal database records using inverted indexing. Other embodiments may be described and/or claimed.

Abstract: The present disclosure provides an experimentation framework for a computational environment in a distributed system. A machine-learning model may be created that predicts at least one output produced by the computational environment based on at least one input provided to the computational environment. During an evaluation time period that is subsequent to at least one modification being made to the computational environment, at least one modified output produced by the computational environment may be determined. The machine-learning model may be used to calculate at least one predicted output that would have been produced by the computational environment during the evaluation time period if the at least one modification had not been made. A determination may also be made about how the at least one modification affected the computational environment based on a comparison of the at least one modified output and the at least one predicted output.

Abstract: The present disclosure pertains to computer readable documents including structured data content for visualizing a structure with a plurality of structure elements and a plurality of relationships between the plurality of structure elements. The document includes the structured data content, a data type indicator, and a structure type indicator. The data type indicator is used to determine a parsing algorithm, The parsing algorithm and the structure type indicator are used to parse the structured data content to determine the structure elements and the relationships between the structure elements. The lexical structure of the structured data content reflects the relationships between the structure elements. A visualization of the structure can be automatically generated. The visualization can be linked to or embedded within visualizations of other structures.

Abstract: A method for controlling versions of a model file includes determining a format of a particular element of a plurality of elements of the model file. The model file defines a model of a system. The method also includes converting the particular element of the plurality of elements from a non-text format to a text-based format in response to the particular element including data in the non-text format. The method further includes writing the particular element converted to the text-based format to a model text file. The model text file is a text-based version of the model file and the model text file is used to detect changes in the model file and to control different versions of the model file.

Abstract: A vehicle data management device includes a data acquisition unit and a data conversion unit. The data acquisition unit is configured to acquire, from each of a plurality of in-vehicle devices mounted on a corresponding vehicle of a plurality of vehicles, a vehicle identification information that is set based on at least a model of the vehicle, and a first data that is contained in a communication frame and is indicative of a vehicle information. The data conversion unit is configured to convert the first data into a label and a second data based on a conversion map that contains a label identification information for identifying the label corresponding to the first data, and a conversion information for converting the first data into the second data. The conversion map contains at least one label identification information and at least one conversion information for each vehicle identification information.

Abstract: The present invention relates to a method for a digital assistant to generate output data, said method being implemented by a computer. Additionally, the invention also relates to a computer program and an electronic device.

Abstract: An image information processing apparatus includes a photoacoustic image acquisition unit configured to acquire an photoacoustic image generated based on a photoacoustic wave by irradiating a subject and a marker with light, an optical image acquisition unit configured to acquire an optical image generated by optically capturing an image of the subject and the marker; and an image processing unit configured to generate a superimposed image in which the photoacoustic image and the optical image are superimposed and display the superimposed image on a display unit. The image processing unit generates the superimposed image based on the marker in the photoacoustic image and the marker in the optical image.

Abstract: Techniques are disclosed relating to increasing the amount of training data available to machine learning algorithms. A computer system may access an initial set of training data that specifies a plurality of sequences, each of which may define a set of data values. The computer system may amplify the initial set of training data to create a revised set of training data. The amplifying may include identifying sub-sequences of data values in ones of the plurality of sequences in the initial set of training data and using an inheritance algorithm to create a set of additional sequences of data values, where each one of the set of additional sequences may include sub-sequences of data values from at least two different sequences in the initial set of training data. The computer system may process the set of additional sequences using the machine learning algorithm to train a machine learning model.

Abstract: Systems, methods, and non-transitory computer readable media are provided for customizing pipelines for integrating data. A file to be ingested into a data analysis platform may be determined. The file type of the file may be detected. The file may be transformed based on the file type. The transformation may include applying a set of operations to the file. The set of operations may correspond to a pipeline of operations associated with the file type.

Abstract: Techniques, which provide visual representations, involve displaying, in a first display area, a plurality of first visual representations indicating a plurality of storage nodes in a storage system, the plurality of storage nodes in the storage system having data replication relations, and the data replication relations including: replication of first data at a first storage node to one or more second storage nodes, and/or replication of second data at one or more second storage nodes to the first storage node. The techniques further involve displaying, in the first display area, a plurality of second visual representations indicating a plurality of data replication relations between the plurality of storage nodes. Accordingly, respective storage nodes in the storage system in a topology view can be visualized, and data replication relations between the respective storage nodes can be clearly described.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving a dataset having a data format into a dataset ingestion controller configured to form a collaborative dataset, interpreting data of the dataset against data classifications at an inference engine to derive at least an inferred attribute, associating the data with annotative data identifying the inferred attribute, and converting the dataset at a format converter to form an atomized dataset.

Abstract: A schema-ontology is automatically constructed with reference to implicit sematic relationships of a database schema. An estimation of the meaning of the language input is determined based on the language input and the schema-ontology. The machine interpretation of the language input is generated based on the meaning and based on the estimation of the meaning including an estimation of an ambiguity of portions of the language input. A software action that is responsive to the machine interpretation of the language input is selected. The software action is implemented based on the machine interpretation of the language input.

Abstract: One or more instances in program code that references an identifier of the standard web object model program object property that is prevented by a web browser from being directly reassigned are identified. The one or more instances in the program code that references the identifier of the standard web object model program object property that is prevented by the web browser from being directly reassigned are modified with one or more corresponding replacement references that include a replacement identifier. The replacement identifier id defined in the program code as being associated with a new program object property defined to invoke the standard web object model program object property in addition to being defined to perform additional processing of a resource identifier associated with the invocation of the standard web object model program object property.

Abstract: The subject matter described herein relates to table detection in a spreadsheet. According to implementations of the subject matter described herein, there is proposed a solution for determining a table in a spreadsheet. In the solution, respective multiple attributes of multiple cells comprised in the spreadsheet may be extracted. Respective features of the multiple cells may be determined based on the extracted multiple attributes. The multiple cells may be divided into at least one candidate area based on the features. At least one candidate table in the spreadsheet may be determined based on the at least one candidate area. By means of the solution, respective features of the multiple cells comprised in the spreadsheet may be determined based on the respective attributes of the multiple cells, and further, a candidate region where a table might exist may be determined based on the respective features of the multiple cells.

Abstract: A transformation device installed in a vehicle includes a transformation section, a transmission section, a detection section and a control section. The transformation section transforms data transmitted from a first control device in a first communication protocol to data in a second communication protocol. The transmission section transmits the data transformed by the transformation section to a second control device. The detection section detects an update of one or more of the first control device and the second control device. In a case in which an update of at least one of the first control device or the second control device is detected by the detection section, the control section changes a mode of transformation by the transformation section.

Abstract: Automated content generation and delivery may include processing a request for story synthesis using specified content items. The request may, for example, be captured using a microphone of an electronic device and transmitted to a server device. The specified content items may be mapped to a story template. Based on the story template, other content items related to the specified content items may be retrieved from one or more content sources. The content sources may, for example, refer to websites, social media platforms, search engine results, or other data stores. A story may then be synthesized using the specified content items and the other content items, for example, by combining the specified content items and the other content items according to the story template. The synthesized story may then be output, for example, at the electronic device.

Abstract: Network attacks are detected by a protocol engine that works in conjunction with one or more streaming protocol analyzers. The protocol engine receives network packets over a computer network and generates metadata of the network packets. The metadata are placed in a transport envelope, which is streamed over the computer network. The transport envelope is received over the computer network. After receiving the transport envelope over the computer network, the metadata are extracted from the transport envelope and provided to the one or more streaming protocol analyzers, which analyze the metadata to detect network attacks.

Abstract: Various embodiments provide methods, systems, apparatus, computer program products, and/or the like for managing, ingesting, monitoring, updating, and/or extracting/retrieving information/data associated with an electronic record (ER) stored in an ER data store and/or accessing information/data from the ER data store, wherein the ERs are generated, updated/modified, and/or accessed via a graph-based domain ontology.

Abstract: A method may include accessing a ratings datastore, the rating datastore including ratings for users with respect to a feature of a software application; transmitting a request for generating a content unit with respect to the feature to a first user of the users based on the first user's ratings for the feature in the ratings datastore; receiving the content unit from the first user; selecting a set of users from a first class of users to review the received content unit based on the set of users' respective ratings for the feature in the ratings datastore; storing the received content unit in a content datastore as associated with a content rating for the feature based on ratings received from the set of users.