Abstract: Techniques for implementing user interfaces, systems, and processes for multidimensional clustering and analysis are described herein. In one aspect, an application or cloud service receives a request to cluster a set of records where the request identifies a first set of one or more dimensions to use for clustering and a second set of one or more dimensions to analyze for correlation patterns. Responsive to receiving the request to cluster the set of records, the system generates clusters based at least in part on variances in the first set of one or more dimensions, wherein each cluster includes at least one record from the set of records. The system may generate, for each respective cluster, an analytic result that identifies how strongly the second set of one or more dimensions correlate to the respective cluster. The system may present the clusters and analytic results for further processing.

Abstract: Computer-implemented methods and systems are disclosed for receiving and indexing a plurality of files for later querying, for dynamically generating scripts to be executed during a query of a data store, and for horizontally distributing a query and aggregating results of the distributed query.

Abstract: A method is provided for classifying a maintenance record for a machine. The method includes receiving the maintenance record including maintenance event information expressed as a collection of terms of interest, and normalizing the terms of interest to their non-abbreviated, dictionary form. The method includes accessing a database of authoritative engineering information from electronic documents, expressed textually and indexed by class of a plurality of classes. The method includes weighted scoring the authoritative engineering information that uses one or more of the terms of interest represented in the weighted scoring by uniqueness scores. Matching authoritative engineering information is determined for the maintenance event information based on the weighted scoring, and the maintenance record is labeled with the class to which the matching authoritative engineering information is indexed.

Abstract: A company may implement automated workflows for convenience of users or to reduce support costs. For example, allowing a user to change an address using an automated workflow may be faster or less expensive than with a human agent. In some instances, a first communications session may be started between a first user and a second user. During the first communications session, one or more communications may be processed to select an intent of the first user and a value of an information item communicated by the first user. An automated workflow may be selected to continue assisting the first user, and the first user may be transferred to a second communications session with the automated workflow. The automated workflow may be initialized with the value of the information item that was provided during the first communications session so that the first user does not need to repeat information.

Abstract: A method and a system for clustering executable files are provided. The method comprises: obtaining a plurality of executable files; for each executable file: (i) detecting repeat sequences of commands of a predetermined length in a given executable file; (ii) determining at least one frequently occurring sequence of the repeat sequences in the given executable file; and based on the at least one frequently occurring sequence of commands, attributing the given executable file to a respective family; iteratively executing the detecting, the determining, and the attributing until one of: all of the plurality of executable files are attributed to at least one respective family, and until un-attributed files of the plurality of executable files do not contain any repeat sequences of commands; and responsive to presence of un-attributed files, attributing each of the un-attributed files of the plurality of executable files to a separate family.

Abstract: A computer-implemented method, computer system, and computer program product for managing a database are disclosed. Features thereof include selecting data lines for analytics, each data line including original data, and adding, to each of the selected data lines, a set of additional bytes to represent metadata about a corresponding one of the data lines. The features further include receiving a request to receive a first data line, and reading a first set of additional bytes corresponding to the first data line.

Abstract: A system and a method for contextual categorization of data comprises a server having a processor and a non-transitory computer-readable storage medium in electronic communication with the processor and comprising program instructions executable by the processor to access an initial inventory of data set and metadata associated with the initial inventory of data set. The system is then configured to classify the initial inventory of data set by using the metadata into (a) reduced set of data comprising high level sensitivity classification and (b) a remainder data set.

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 system may include an atomized workflow loader configured to receive an atomized dataset to load into a data store, and to determine resource requirements data to describe at least one resource requirement. The atomized workflow loader may be further configured to select a data store type based on a resource requirement, and perform a load operation of the atomized dataset as a function of the data store type.

Abstract: A method comprises receiving, by an elevation application communicatively coupled to a geospatial database, a request comprising a start location and an end location from a workstation, wherein the geospatial database stores elevation data describing ground elevations and clutter elevations at a plurality of different geographic locations, segmenting, by the elevation application, a path between the start location and the end location into a plurality of segments having an incremental distance, for each of the plurality of segments, constructing a segment vector comprising the ground elevation and clutter elevation of the segment, and constructing an elevation data structure comprising the segment vector for each of the plurality of segments.

Abstract: A method is provided to reduce the number of duplicates of each document that is stored within entity databases. The method may include creating discrete links and/or pointers to the location of the document already stored within an entity. The method may also include separating the document into different classification levels. The method may include storing the different parts of the documents in different locations within the entity.

Abstract: A method includes determining, by a computing system, a probability of whether at least a threshold portion of a particular advertisement will be presented on a particular content presentation device, and a cost associated with presentation of the particular advertisement on the particular content presentation device. The computing system calculates an expected revenue associated with presentation of the particular advertisement based on the probability and the cost. When the expected revenue exceeds a threshold revenue, the computing system communicates the particular advertisement to the particular content presentation device.

Abstract: Methods and systems for generating and using a dynamic asset inventory are disclosed. According to an implementation, a dynamic inventory can be generated by a function included in a security agent that provides security for a network environment. First computing asset information can be collected from first data sources, and the first computing asset information can be supplemented with second computing asset information. The supplemented computing asset information can be used to generate log files for computing assets. The log files can be used to generate an asset search index that supports rapid search of the dynamic asset inventory.

Abstract: A method comprises receiving an input specifying one or more rules in connection with archiving one or more of a plurality of files from a source storage location to a target storage location. The one or more rules specify one or more constraints for retention of the one or more of the plurality of the files. In the method, the one or more of the plurality of files are retrieved from the source storage location for migration to the target storage location. A request is sent to the target storage location that the target storage location invoke the one or more rules to retain the one or more of the plurality of files in the target storage location. The target storage location comprises a cloud storage platform.

Abstract: A cluster generation system identifies data elements, from a first binary record, that each have a particular value and correspond to respective binary traits. A candidate description function describing the binary traits is generated, the candidate description function including a model factor that describes the data elements. Responsive to determining that a second record has additional data elements having the particular value and corresponding to the respective binary traits, the candidate description function is modified to indicate that the model factor describes the additional elements. The candidate description function is also modified to include a correction factor describing an additional binary trait excluded from the respective binary traits. Based on the modified candidate description function, the cluster generation system generates a data summary cluster, which includes a compact representation of the binary traits of the data elements and additional data elements.

Abstract: A method includes determining, by a computing system, a probability of whether at least a threshold portion of a particular advertisement will be presented on a particular content presentation device, and a cost associated with presentation of the particular advertisement on the particular content presentation device. The computing system calculates an expected revenue associated with presentation of the particular advertisement based on the probability and the cost. When the expected revenue exceeds a threshold revenue, the computing system communicates the particular advertisement to the particular content presentation device.

Abstract: Techniques are disclosed for data management in an information processing system. For example, a method comprises analyzing one or more data sources, wherein each of the one or more data sources comprise a set of metadata and usage information associated with the set of metadata. The method then determines at least one of data definitions and data classifications for the one or more sets of metadata across the one or more data sources, and stores the at least one of data definitions and data classifications for the one or more sets of metadata in a repository.

Abstract: A method for starting a vehicle and a related device are provided. The method includes: a server sends first security information and second security information to a mobile terminal and a telematics box respectively through an encrypted secure transmission channel or an encrypted secure transmission protocol, so that the telematics box can verify, by using the first security information and the second security information, a vehicle start instruction sent by the mobile terminal. When the verification succeeds, the telematics box controls the vehicle to start. According to the application, plaintext transmission of the security information between the mobile terminal and the telematics box is avoided, thereby avoiding leakage of the security information, and reducing a risk that the vehicle is maliciously started. In addition, a transmission process of the security information may not be restricted by a distance between the vehicle and the mobile terminal.

Abstract: Techniques for data lifecycle discovery and management are presented. Data lifecycle discovery platform (DLDP) can identify data of users, data type, and language of data stored in data stores (DSs) of entities based on scanning of data from databases. DLDP determines compliance of DLDP and DSs with obligations relating to data protection arising out of jurisdictional laws or agreements. DLDP generates rules to facilitate complying with and enforcing laws and agreements. DLDP can determine, and present to authorized users, risk scores relating to levels of compliance of the DLDP, associated platforms, or entities, risk indicator metrics, or a privacy health index of the organization associated with DLDP. DLDP can manage user rights regarding data, and access to data in DSs and information relating thereto stored in secure data store of DLDP. DLDP can remediate issues involving anomalies indicating non-compliance. DLDP can utilize machine learning to enhance various functions of DLDP.

Abstract: Systems and methods for pattern-based multi-stage deterministic data classification that may reduce processing and memory overhead while providing more accurate data classifications.

Abstract: The present embodiments relate to data processing model recommendation and simulation. A model catalog executing on a cloud infrastructure (CI) system can parse data from an obtained dataset identifying aspects of the dataset. The parsed data from the dataset can be compared with a plurality of potential models stored in a domain ontology store of the model catalog to identify one or more recommended models. A simulation of any of the recommended models can be executed using a portion of the dataset to provide insights into output data resulting from executing the recommended model. The output data resulting from the simulation of the recommended model can be provided to the client for the client to either accept or reject the model.

Abstract: Methods and systems are configured to determine a semantic meaning for data and generate data processing rules based on the semantic meaning of the data. The semantic meaning includes syntactical or contextual meaning for the data that is determined, for example, by profiling, by the data processing system, values stored in a field included in data records of one or more datasets; applying, by the data processing system, one or more classifiers to the profiled values; identifying, based on applying the one or more classifiers, one or more attributes indicative of a logical or syntactical characteristic for the values of the field, with each of the one or more attributes having a respective confidence level that is based on an output of each of the one or more classifiers. The attributes are associated with the fields and are used for generating data processing rules and processing the data.

Abstract: A device may provide a verification indicator to a device associated with a website. The verification indicator may be associated with verifying access to the website. The device may detect that the verification indicator has been associated with code associated with the website based on processing the code. The device may provide a script to the device. The script may be included in the code. The script may be associated with monitoring operations of the website. The device may receive data related to the operations. The device may analyze the data using a model. The model may be associated with making a prediction related to at least one of: a value to be received via the website, or traffic associated with the website. The device may perform one or more actions related to the website based on a result of the analyzing.

Abstract: In an aspect, an apparatus for generating an ingredient chain is presented. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor. A memory contains instructions configuring at least a processor receive recipe data from a suer. At least a processor is configured to extract a plurality of ingredients from recipe data. At least a processor is configured to classify, utilizing an ingredient classifier, a plurality of ingredients to a plurality of impact factors. At least a processor is configured to generate, as a function of impact factors, an ingredient chain for a user.

Abstract: A graph-based data cataloging system, product and method that structures expert knowledge and statistically driven data analytics into a system-based framework for finding and relating enhanced metadata on subject-relevant, curated datasets from disparate, externally held data sources is shown. Displayed across a knowledge graph of nodes of datasets linked by their metadata attributes, the system simplifies the search and retrieval of multiple datasets of relevance to a user's technical, content, and resource-driven needs.

Abstract: In some examples, a system performs data deduplication using a deduplication fingerprint index in a hash data structure comprising a plurality of blocks, wherein a block of the plurality of blocks comprises fingerprints computed based on content of respective data values. The system merges, in a merge operation, updates for the deduplication fingerprint index to the hash data structure stored in a persistent storage. As part of the merge operation, the system mirrors the updates to a cached copy of the hash data structure in a cache memory, and updates, in an indirect block, information regarding locations of blocks in the cached copy of the hash data structure.

Abstract: A computer-implemented technique is described herein for assisting a user in advancing a task objective. The technique uses a suggestion-generating system (SGS) to provide one or more suggestions to a user in response to at least a last-submitted query provided by the user. The SGS may correspond to a classification-type or generative-type neural network. The SGS uses a machine-trained model that is trained using a multi-task training framework based on plural groups of training examples, which, in turn, are produced using different respective example-generating methods. One such example-generating method constructs a training example from queries in a search session. It operates by identifying the task-related intent the queries, and then identifying at least one sequence of queries in the search session that exhibits a coherent task-related intent. A training example is constructed based on queries in such a sequence.

Abstract: An adaptive multi-model item selection method, comprising: receiving, from one of a plurality of client devices, a request including a client-side feature vector representing a state of the client device; determining, by an advocate model, a probability distribution of a plurality of specialist cluster models from the client-side feature vector; choosing, by a use case selector, a cluster corresponding to a use case from the probability distribution; and obtaining, by the use case selector based on the cluster (i.e., the cluster that was sampled by the user case selector), a specialist cluster model from the plurality of specialist cluster models.

Abstract: A system can a divide database into a group of shards distributed among a group of data centers, wherein the group of shards comprises respective leader replicas. The system can determine respective correlation values between pairs of shards of the group of shards. The system can examine the pairs of shards in a descending order of respective correlation values, comprising, in response to determining that a respective pair of shards of the pairs of shards has a first correlation value greater than a predetermined threshold value, and that at least one shard of the respective pair of shards is unlocked, reassigning leader replicas of the respective pair of shards to be stored in a same data center of the group of data centers, and locking the leader replicas of the respective pair of shards from being reassigned to another data center of the group of data centers during the examining.

Abstract: A computer system and method for verifying a data lineage of a data element is provided. The system comprises at least processor and a memory storing instructions which when executed by the processor cause the processor to perform the method. The method comprises extracting data transformation code from programming logic, extracting and describing data transformation semantics from the code using a data transformation ontology, filtering out non-business-significant transformations, and determining that remaining business-significant transformations match a business ontology.

Abstract: A data management platform for intelligently managing data is provided. The data management platform includes an ETL module configured to extract, cleanse, transform, or load data; a data lake configured to store a first group of data formed by extracting raw data from a plurality of data sources by the ETL module; a data warehouse configured to store a second group of data formed by cleansing and standardizing on the first group of data; a general data layer configured to store a third group of data formed by subjecting the second group of data to data fusion; and a data mart configured to store a fourth group of data formed by transforming the third group of data by the ETL module. The general data layer is a distributed data storage storing information available for querying. The data mart is a database of NoSQL type storing information available for computational processing.

Abstract: Provided is a method of extracting a mediator variable and a mediation influence from a multivariate set. The method includes: receiving a database in which a set of N multiple variables (N is a natural number) including at least one of discrete time series data or continuous time series data is stored; selecting a test variable set including an independent variable, a dependent variable, and a mediator variable from the database in which the multivariate set is stored; determining the mediator variable using transfer entropy and conditional transfer entropy for the selected test variable set; and calculating a mediation influence of the determined mediator variable, wherein the mediation influence is separately calculated as an individual causal influence of the mediator variable and a group causal influence of mediator variables.

Abstract: Methods and systems are provided for improved access to rows of data in a distributed data system. Each data row is associated with a partition. Data rows are distributed in one or more files and an impure file includes data rows associated multiple partitions. A clustering set is generated from a plurality of impure files by selecting a candidate impure file based on file access activity metrics and one or more neighbor impure files. Data rows of the impure files included in the clustering set are sorted according to their respective associated partitions. A set of disjoint partition range files are generated based on the sorted data rows of the impure files included in the clustering set. Each file of the set of disjoint partition range files is transferred to a respective target partition.

Abstract: Apparatus and methods are disclosed for using machine learning models with private and public domains. Operations can be applied to transform input to a machine learning model in a private domain that is kept secret or otherwise made unavailable to third parties. In one example of the disclosed technology, a method includes applying a private transform to produce transformed input, providing the transformed input to a machine learning model that was trained using a training set modified by the private transform, and generating inferences with the machine learning model using the transformed input. Examples of suitable transforms that can be employed include matrix multiplication, time or spatial domain to frequency domains, and partitioning a neural network model such that an input and at least one hidden layer form part of the private domain, while the remaining layers form part of the public domain.

Abstract: A method includes, for each key of a plurality of keys, identifying from a set of buckets a first bucket for the key based on a first hash function, and identifying from the set of buckets a second bucket for the key based on a second hash function. An entry for the key is stored in a bucket selected from one of the first bucket and the second bucket. The entry is inserted in a sequence of entries in a memory block. A position of the entry in the sequence of entries corresponds to the selected bucket. For each bucket in the set of buckets, an indication of a number of entries in the bucket is recorded.

Abstract: In some aspects, a content-extraction system can receive a query from a client device and generate a result set of digital content responsive to the query. For instance, the content-extraction system can obtain, from a search system, a set of digital content matching one or more keywords. The content-extraction system can exclude digital content items lacking core content, digital content items with duplicative content, or both. In some aspects, the content-extraction system can determine, for one or more remaining digital content items, a content attribute score. The content-extraction system can select, as the result set of digital content, a subset of digital content based on the content attribute scores. The content-extraction system can output the result set to the client device.

Abstract: The present disclosure relates to a method of loading data. The method includes checking a topic corresponding to a search word among a plurality of topics in response to acquiring a search word for a topic of a distributed messaging system from a user, checking a data format including one or more fields of a message loaded into a topic, and then loading data generated based on the checked data format and the read message into a data lake.

Abstract: A method for faceted search comprises generating a search user interface comprising a facet hierarchy interface configured to display a representation of a facet hierarchy in conjunction with results displayed in a search results display, updating the search results display to display faceted search results and updating the facet hierarchy interface to display, in conjunction with the faceted search results displayed in the updated search results display, a control to allow a user to select a search facet topic where the search facet topic is a facet topic from the facet hierarchy that is not represented in the faceted search results.

Abstract: Described are computer-based methods and apparatuses, including computer program products, comprising the steps of, or structure for, storing a plurality of expert profiles in a database, each of the plurality of expert profiles comprising information associated with a person having knowledge in a particular category, subject or topic; receiving search criteria over a network from a query source; selecting at least one of the plurality of expert profiles comprising information that satisfy the search criteria; and transmitting expert profile data for each of the selected expert profiles to the remote search engine, the expert profile data comprising data that defines a displayable representation of a corresponding expert profile, the expert profile data further comprising data that facilitates a client-initiated, real-time communication session over the network with a person associated with the corresponding expert profile.

Abstract: By the abovementioned technical solutions, the present disclosure provides optimizing a vector autoregressive model conforming to structural constraints of sparsity and acyclicity. A regularization term is introduced to the model to impose the sparsity structural constraint such that most off-diagonal coefficients of an autoregressive coefficient matrix are forced to zero values. One or more penalty terms are introduced to the model to impose the acyclicity structural constraint such that coefficients of the main diagonal are not causally self-related. The resulting model is then reformulated for computation as an augmented Lagrangian function, and further computed for different parameters in alternating iterations to make the computations tractable and within magnitude and precision limits of digital computers.

Abstract: A computer-implemented system or process is programmed or configured to use a configuration file to specify one or more tasks to apply to raw ingested data. A task may be a sequence of instructions programmed or configured to format raw ingested data into a dataset in a CSV format. Examples of tasks may include: a parser to parse Cobol data into a CSV, a parser to parse XML into a CSV, a parser to parse text using fixed-width fields to a CSV, a parser to parse files in a zip archive into a CSV, a regular expression search/replace function, or formatting logic to remove lines or blank lines from raw ingested data. In one embodiment, the configuration file may specify a schema definition for a task to use for generating a dataset. In one embodiment, the configuration file may also include one or more access control list (ACL) definitions for the generated dataset. In one embodiment, the building of datasets using the configuration file is automated, for example, on a nightly basis.

Abstract: Techniques for implementing user interfaces, systems, and processes for multidimensional clustering and analysis are described herein. In one aspect, an application or cloud service receives a request to cluster a set of records where the request identifies a first set of one or more dimensions to use for clustering and a second set of one or more dimensions to analyze for correlation patterns. Responsive to receiving the request to cluster the set of records, the system generates clusters based at least in part on variances in the first set of one or more dimensions, wherein each cluster includes at least one record from the set of records. The system may generate, for each respective cluster, an analytic result that identifies how strongly the second set of one or more dimensions correlate to the respective cluster. The system may present the clusters and analytic results for further processing.

Abstract: An information handling system for managing detection of objects includes a storage and a processor. The storage is for storing an encoder; a critical class classifier; a general classifier; and a decoder. The processor obtains data that may include one or more of the objects; encodes the data using the encoder to obtain encoded data; obtains a critical class classification for the encoded data using the critical class classifier; obtains a general classification for the encoded data using the general classifier; conditions the encoded data to obtain conditioned encoded data; decodes the conditioned encoded data using the decoder to obtain reconstructed data; makes a determination that the reconstructed data and the critical class classification indicate that the data is an unknown classification; classifies the data as being an unknown classification based on the determination; and performs an action set based on the unknown classification of the data.

Abstract: Techniques for identifying images that are representative of items of inventory are described herein. A service provider may receive a description of an item of inventory from a merchant. The service provider may search one or more databases for images representative of the item. The images may include a merchant-facing image used to represent the item on a user interface of a merchant computing device and a customer-facing image used to represent the item to a customer on a user interface of a merchant computing device and/or a customer computing device. The customer-facing image may include an image that is more detailed, accurate, and/or aesthetically pleasing than the merchant-facing image. The service provider may associate the merchant-facing and customer-facing images with the item and may cause the merchant-facing and the customer-facing images to render on displays of the merchant and customer computing devices to represent the item.

Abstract: Computer-implemented methods and systems are disclosed for receiving and indexing a plurality of files for later querying, for dynamically generating scripts to be executed during a query of a data store, and for horizontally distributing a query and aggregating results of the distributed query.

Abstract: Pairwise entity matching systems and methods are disclosed herein. A deep learning model may be used to match entities from separate data tables. Entities may be preprocessed to fuse textual and numeric data early in the neural network architecture. Numeric data may be represented as a vector of a geometrically progressing function. By fusing textual and numeric data, including dates, early in the neural network architecture the neural network may better learn the relationships between the numeric and textual data. Once preprocessed, the paired entities may be scored and matched using a neural network.

Abstract: A method of generating matching metadata vectors for identifying content items in a store searchable by input vectors, the method comprising: receiving multiple training inputs, each training input comprising a content identifier indicative of a content item, and at least one natural language description of the content item; for each training input: converting the natural language description into at least one text component; generating at least one vector, each vector corresponding to one text component; generating a set of component parts for each vector, each component part corresponding to a coordinate initialized with a random value; adjusting each random coordinate based on the relationship of each component part to other vectors; determining a weighting for each vector with respect to the item; and defining a metadata vector for each item comprising the vectors containing the adjusted coordinates for that item and the weighting for each vector.

Abstract: In some examples, a system performs data deduplication using a deduplication fingerprint index in a hash data structure comprising a plurality of blocks, wherein a block of the plurality of blocks comprises fingerprints computed based on content of respective data values. The system merges, in a merge operation, updates for the deduplication fingerprint index to the hash data structure stored in a persistent storage. As part of the merge operation, the system mirrors the updates to a cached copy of the hash data structure in a cache memory, and updates, in an indirect block, information regarding locations of blocks in the cached copy of the hash data structure.

Abstract: A method of storing a data object includes dividing data of a data object into a first part of data and a second part of data, in response to receiving a writing request for a data object, the first part of data including a data field of the data object, the second part of data including a meta data of the data object; writing the first part of data into a first data file stored in a first external storage device; and writing, into a second data file stored in a second external storage device, first location information, and the second part of data, the first location information including location information of the first part of data within the first external storage device.

Abstract: Provided is a method, computer program product, and system for classifying a set of data items based on format organizations. A processor may determine at least one format organization of a set of data items. The format organization of a data item indicates a symbol type of at least one continuous symbol in the data item and a number of the at least one continuous symbol. The processor may determine at least one candidate data class for the set of data items from a plurality of predetermined data classes based on the at least one format organization. The processor may classify the set of data items into at least one target data class selected from the at least one candidate data class. In this way, the set of data items can be efficiently classified.

Abstract: This application relates to a client-server architecture that enables search queries to be applied to transcription information for multimedia files. A server device implements a service configured to query a search platform to retrieve results associated with a plurality of multimedia files stored in a content database. The results are ordered according to a plurality of heuristic values calculated based on a text relevance analysis. The service is configured to modify the heuristic values to adjust an order of the results, and generate a response to a search request that includes a representation of at least a portion of the transcription information of the multimedia files referenced by the results. The heuristic values are modified based on at least one of a popularity score for a corresponding multimedia file, a weight associated with a particular field, or a relevance score based on feedback signals.