Abstract: Methods and systems for representing data are disclosed. An example method can comprise providing a first representation of data and receiving a request to change resolution of the data. An example method can comprise, transforming, based on at least one wavelet function, the data to at least one of reduced data or expanded data. An example method can comprise providing a second representation of the data based on at least one of the reduced data or expanded data.

Abstract: A visual data operation method, system, and device, and a medium for one or more pieces of data, creating one or more corresponding value objects, and arranging the one or more value objects as a tree structure; and for the one or more value objects, creating corresponding database records, and defining fields of the database records by the one or more value objects. Data and database records correspond to each other and are mutually converted by using value objects. A developer only needs to arrange the value objects as a tree structure, and a system can automatically complete remaining data operations subsequently, including creating database records and synchronizing database records, and the like. A developer can quickly design a data storage format by taking a user as a unit, and the design presentation is intuitive and understandable to other developers.

Abstract: Techniques are described herein for routing queries to particular nodes of a multi-node database system based on the query. A database table is partitioned into a plurality of affinity groups. Each affinity group is assigned a particular node as the master node of the affinity group. A mapping is sent to a query router indicating the master node for each affinity group of the plurality of affinity groups. The query router determines, for a particular query, a target node to which to send the particular query based on the mapping and the particular query.

Abstract: Embodiments of the present disclosure relate to method, device and computer program product for data backup. The method comprises: in response to receiving from a backup server a data stream to be backed up, dividing the data stream into a plurality of data segments; distributing the plurality of data segments to at least one computing node; in response to receiving an index of a corresponding data segment from a first computing node of the at least one computing node, looking up the index in a global index cache, the index being generated by the first computing node to uniquely identify the data segment, the global index cache storing indexes of data in a backup storage device; in response to the missing index in the global index cache, adding the index into the global index cache; and sending to the first computing node an indication to store the data segment in the backup storage device.

Abstract: In an approach for dynamically selecting the application algorithm to be used for each change in a target database system, a processor provides at least two application algorithms for applying changes to a table in a target database system. A processor determines, for each application algorithm of the at least two application algorithms, a performance behavior of each application algorithm for sizes of changes that are applied to the table by the respective application algorithm. A processor receives a data change request for applying a change to the table. A processor determines a size of the change to the table. A processor selects one of the at least two application algorithms that provides a best performance for the size based on the performance behavior of each application algorithm. A processor applies the change to the table using the selected application algorithm that provides the best performance for the size.

Abstract: The present invention is a system and method for recording right transfer in blockchain. There are three types of tokens, each of which may include a definition of rights. The rights can also be split or merged during circulation of tokens. The blockchain system ensures totality of rights does not increase nor decrease before and after circulation.

Abstract: A selection device includes a storage unit and a selection unit. The storage unit stores the write time and the read time of each of a plurality of nodes. The selection unit selects a first response condition in response to a data write request on the basis of the write time of each of the plurality of nodes such that the response time for the data write request becomes shorter than a requirement value of the write time and the number of nodes in which writing has been completed increases. The selection unit selects a second response condition in response to a data read request on the basis of the first response condition and the read time of each of the plurality of nodes such that the response time for the data read request becomes shorter than a requirement value of the read time.

Abstract: In an example embodiment, a solution is used to provide container volume replication via a container storage replication log and volume buffer synchronization, which is built on top of a container cloud platform whose container metadata and replication runtime configuration are all managed by a storage manager (a service orchestrated by its job scheduler and service orchestrator). This container volume replication ensures the data security for a long-running service in the container. In the case of any disaster, the in-memory database and application data inside of the container can be recovered via volume replication. This provides container volume replication for long-running containerized applications whose states keep changing.

Abstract: A data processing method is disclosed, the method comprising: after data synchronization, obtaining data offset of synchronous data related to a data integration task to be performed, the data offset representing deviation of the synchronous data from corresponding source data; determining whether the synchronous data is complete based on the data offset; in response to the synchronous data being complete, performing the data integration task to the synchronous data.

Abstract: A follower system and a leader system store records for a plurality of users. Each of the follower system and the leader system stores at least a record for a user. Each of the follower system and the leader system stores a private log and a public log. The public log is periodically synchronized across the follower system and the leader system. The private log of each system is maintained independent of the other system. The follower system transmits information stored in the public logs to the leader system for synchronizing the public logs of the follower system and the leader system in response to updating the public logs with information describing the second set of transactions.

Abstract: Techniques for providing batch performance using a stream processor are described. In one technique, a method includes receiving an event that includes an event key and a timestamp. The method then generates a partition value and time bucket value, the partition value generated based on the event key and the time bucket value generated based on the timestamp. The event key, partition value, and time bucket value are then combined to form a database key and used in a command to a database.

Abstract: The present disclosure relates to systems and methods for carrying out predictive analysis where a plurality of data sets may be ingested from a data lake. A data analyzer may tag the ingested data sets, detect redundant occurrence of multiple attributes such as, a row, a column, and a list in the tagged data set. The data analyzer may eliminate the detected redundant multiple attributes. Further, a model selector and evaluator may execute a machine learning (ML) model to conduct predictive analysis on the data set. The execution may be done based on a predefined set of instructions stored in a database. The executed ML model may be validated upon determining that the predictive analysis yields a positive response for the transformed data set.

Abstract: Systems and methods are disclosed for associating summarizations of visualizations of a data set based on affinities between the summarizations. For a data set, a number of summarizations may be created that summarizes the data set in different ways. The summarizations may be linked, such that selecting a data element of a first summarization causes display of a second summarization. To assist in linking of summarizations, suggested linkings between summarizations can be determined based on affinities of the two summarizations. Affinities can reflect similarities in the data content of the two summarizations, such as an output of a first summarization being a valid input to the second summarization.

Abstract: Methods, systems, and apparatuses for generating notifications corresponding to queries submitted for execution by virtual warehouses are described herein. A request to execute a query may be received. An execution plan, for the query, may be identified. A processing complexity for the query may be predicted based on the query and the execution plan. A notification may be generated based on the processing complexity meeting an alert threshold. A user device may display the notification. A response to the notification comprising a selection of a first virtual warehouse, of a plurality of virtual warehouses, to execute the query may be received.

Abstract: The present invention relates to a system and a method for updating data models. Input data received from a data source and/or prediction data obtained from a data model is reduced based on baseline reference data to obtain a plurality of representative points. The plurality of representative points are clustered to generate a plurality of clusters. An outlier cluster is detected from the plurality of clusters based on a maximum distance of the plurality of clusters from a highest density cluster and/or comparison of quantity and values of the plurality of representative points with predefined rules. Data drift is identified based on changes in densities of the plurality of clusters. The data model is updated using information corresponding to the outlier cluster and the data drift.

Abstract: A logical graph is generated using at least a portion of log data received from a set of agents executing on one or more nodes in one or more data centers. The logical graph is augmented using data obtained from one or more agents executing in containerized environments, including by representing communications between pods within the logical graph. The augmented logical graph is used to detect an anomaly.

Abstract: A time-series data processing apparatus according to the present invention includes: a generating unit configured to generate a generator having learned so as to generate state information representing a state of time-series data having a predetermined time width in accordance with a label given to the time-series data; a state information generating unit configured to generate, by using the generator, state information representing a state of division time-series data obtained by dividing the time-series data by a shorter time width than the predetermined time width; and a classifying unit configured to classify a plurality of division time-series data based on state information of the plurality of division time-series data.

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 method and apparatus for managing and controlling a resource based on a time series database. The method includes: acquiring metadata of a resource; aggregating the metadata according to an aggregation strategy to obtain aggregated metadata; and managing and controlling the resource in the time series database based on the aggregated metadata. The aggregated metadata may be multiple data sets, each of which may be a type of metadata, so that massive metadata may be aggregated into the multiple sets, thereby realizing categorized storage of the metadata. In addition, the method for managing and controlling the resource is applied to the time series database.

Abstract: A computer-implemented method can create a node-link model from a hierarchy table, which includes a plurality of records associated with a plurality of objects organized in segments. A record includes a unique identifier, a parent reference, and a value distribution for the associated object. The parent reference is the unique identifier of a parent object directing the value distribution to the associated object. The node-link model includes a plurality of nodes representing the objects and links connecting the nodes and representing value distributions between the objects. The method can generate a visual representation of the node-link model in a user interface and receive an input from the user interface. Responsive to the input, the method can change the visual representation to depict a portion of the node-link model based on a viewable scope of the node-link model and one or more viewable fields specified in the input.

Abstract: A method for intelligent editing of legal documents is described. The method may include receiving a rule, accessing a plurality of documents, and generating a list of tokens as a function of the rule and the plurality of documents. The method may also include ranking each token of the list of tokens, wherein a ranking of each token is a function of a frequency of occurrence in the plurality of documents, accessing a user inputted legal text, and suggesting one or more alterations to the user inputted legal text as a function of the ranked list of tokens. An apparatus for intelligent editing of legal documents is also described.

Abstract: A method of training a model for query generation, the method performed by at least one processor and including receiving a training instance query corresponding to a dialogue history. The method further including generating a first static view of the model based on a number of common words between the training instance query and the dialogue history. The method further including generating a second static view of the model based on one or more tokens not covered by the dialogue history, the one or more tokens corresponding to one or more query words. The method further including generating a dynamic view of the model based on a score operation that compares a candidate query generated from the model with a target query. The method further including training the model based at least on the first static view, the second static view, and the dynamic view.

Abstract: A data generation device according to an embodiment includes one or more processors. The one or more processors classify each of a plurality of users having attributes similar to one another into any one of a plurality of clusters based on user information representing the respective attributes of the users. The one or more processors estimate whether a search result is useful to each of the users based on a similarity between information included in the search result and information representing attributes of the clusters, and output learning data of a ranking model for determining an order of a plurality of the search results, the learning data being data including the search results and estimation information representing whether the search results are useful.

Abstract: A processor may transcribe an electronic representation of a dialogue. The processor may identify one or more question-answer pairs from the electronic representation. The processor may generate based upon the one or more identified question-answer pairs a summary of the dialogue. The processor may display the summary of the dialogue to a user.

Abstract: A document processing system processes documents including typewritten and/or handwritten data by converting them to document images for entity extraction. A received document is initially processed to generate a deep document data structured and for classification as one of a structured or an unstructured document. If the document is classified as a structured document, it is processed for entity extraction based on a matching template and image alignment of the document image with the matching template. If the document is classified as an unstructured document, entities are extracted by obtaining nodes and providing the nodes to a self-supervised masked visual language model.

Abstract: By formulizing a specific company's internal knowledge and terminology, the ontology programming accounts for linguistic meaning to surface relevant and important content for analysis. The ontology is built on the premise that meaningful terms are detected in the corpus and then classified according to specific semantic concepts, or entities. Once the main terms are defined, direct relations or linkages can be formed between these terms and their associated entities. Then, the relations are grouped into themes, which are groups or abstracts that contain synonymous relations. The disclosed ontology programming adapts to the language used in a specific domain, including linguistic patterns and properties, such as word order, relationships between terms, and syntactical variations. The ontology programming automatically trains itself to understand the domain or environment of the communication data by processing and analyzing a defined corpus of communication data.

Abstract: Event detection may be carried out to determine one or more content items associated with an event type. A server may determine one or more visually relevant labels, of a plurality of labels, associated with the event type. The server may determine one or more textually relevant labels, of the plurality of labels, associated with the event type. The server may determine an event label distribution based on a correlation of the visually relevant event labels and the textually relevant labels, wherein the event label distribution comprises a plurality of labels. The server may determine a content item label distribution associated with a content item, wherein the content item label distribution comprises a plurality of second labels. The server may send, based on comparing the event label distribution with the content item label distribution, the content item to a computing device.

Abstract: A method and a system for producing a story video are provided. A method for producing a story video, according to one embodiment, can produce a specific story video by determining a theme of a story that is suitable for collected videos and selecting and arranging an appropriate video for each frame of a template associated with the theme.

Abstract: Systems and methods are provided for obtaining and managing remote sensing data (e.g. Earth observation data). A remote sensing platform obtains imagery and other remote sensing data of the Earth and other planetary objects. The remote sensing platform includes the International Space Station, or manned and unmanned spacecraft or aircraft. A sensor captures observation data and transmits the data to ground stations on the Earth. A ground segment receives and stores the data. Users use an order management system to place orders for the observation data, which specify processing parameters for the remote sensing data. The remote sensing data is retrieved from storage is processed according to the parameters to generate a data product. This system provides tools for searching and analyzing the data, and for interacting with the system through an API. The system combines data that is produced by the remote sensing platform and by third parties.

Abstract: An example system includes a processor to receive, a randomly generated alpha-map, a pair of training images, and a pair of training texts associated with the pair of training images. The processor is to generate a blended image based on the randomly generated alpha-map and the pair of training images. The processor is to train a visual language grounding model to separate the blended image into a pair of heatmaps identifying portions of the blended image corresponding to each of the training images using a separation loss.

Abstract: Methods, systems, and media for image searching are described. Images comprising one query image and a plurality of candidate images are received. For each candidate image, a first model similarity measure from an output of a first model configured for scene classification to perceive scenes in the images is determined. Further, for each candidate image of the plurality of candidate images, a second model similarity measure from the output of a second model configured for attribute classification to perceive attributes in the images is determined. For each candidate image of the plurality of candidate images, a similarity agglomerate index of a weighted aggregate of the first model similarity measure and the second model similarity measure is computed. The plurality of candidate images based on the respective similarity agglomerate index of each candidate image are ranked and a first ranked candidate images corresponding to the searched images are generated.

Abstract: A method and system for providing a data analysis in the form of a customized geographic visualization on a graphical user interface (GUI) on a remote client computing device using only a web browser on the remote client device. The system receives a user's selected data analysis to be performed by the system for display on the remote client device. The system verifies the data access permissions of the user to render a data analysis solution customized to that particular user, and automatically prevents that user from gaining access to data analysis solutions to which that user is prohibited. The system is configured to respond to the user's data analysis request, perform the necessary computations on the server side on the fly, and send a dataset interpretable by the client device's web browser for display on the client device or on a device associated with the client device.

Abstract: Methods, systems, and media for tracking content items are provided.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to select reference sub-fingerprints for comparison to query sub-fingerprints based on a determination that a query sub-fingerprint is a match with a reference sub-fingerprint, generate a count vector that stores total counts of matches between the query sub-fingerprints and different subsets of the reference sub-fingerprints, each of the different subsets being aligned to the query sub-fingerprints at a different offset from a reference point, each of the different offsets being mapped by the count vector to a different total count, calculate a maximum count among the total counts, a median of the total counts, and a difference between the maximum count and the median of the total counts, and classify the reference sub-fingerprints as a match with the query sub-fingerprints based on the difference between the maximum count in the count vector and the median.

Abstract: Techniques of content unification are disclosed. In some example embodiments, a computer-implemented method comprises: determining clusters based a comparison of a plurality of audio content using a first matching criteria, each cluster of the plurality of clusters comprising at least two audio content from the plurality of audio content; for each cluster of the plurality of clusters, determining a representative audio content for the cluster from the at least two audio content of the cluster; loading the corresponding representative audio content of each cluster into an index; matching the query audio content to one of the representative audio contents using a first matching criteria; determining the corresponding cluster of the matched representative audio content; and identifying a match between the query audio content and at least one of the audio content of the cluster of the matched representative audio content based on a comparison using a second matching criteria.

Abstract: An artificial intelligence (AI) system utilizing a machine learning algorithm such as deep learning for controlling an electronic device when a video is reproduced and a user's voice instruction is received, to acquire a frame corresponding to the time point when the input of the user's voice instruction is received, and obtain a search result for information on objects in the frame using an AI model trained according to at least one of machine learning, a neural network or a deep learning algorithm.

Abstract: Embodiments are disclosed for using natural language processing (NLP) to manage security video data. A method of using NLP to search security video data includes receiving, by a surveillance video query system, a text query. A query embedding corresponding to the text query is obtained using a text query model. One or more matching frame embeddings that match the query embedding are identified in a vector database. Matching surveillance video data corresponding to the one or more matching frame embeddings is then obtained from a surveillance video data store. The matching surveillance video data is returned in response to receipt of the text query.

Abstract: The present specification discloses video matching. In a computer-implemented method, a plurality of feature vectors of a target video is obtained. A candidate video similar to the target video is retrieved from a video database based on the plurality of feature vectors of the target video. A time domain similarity matrix feature map is constructed between the target video and the candidate video based on the target video and the candidate video. Using the time domain similarity matrix feature map as an input into a deep learning detection model, a video segment matching the target video in the candidate video and a corresponding similarity is output.

Abstract: A computer-implemented method for storage of digital information data via at least one processing unit (110) operatively coupled to at least one database is proposed. In at least one embodiment, the method comprises: providing at least one portion of the digital information data; performing at least one syntactic and/or semantic search in the at least one database based upon the portion of the digital information data; providing one or more meta-data strings in response to the at least one syntactic and/or semantic search; receiving at least one relevant meta-data string; and storing the portion of digital information data and the at least one relevant meta-data string. In at least one embodiment, the at least one relevant meta-data string is usable for a future syntactic and/or semantic search.

Abstract: A building management system (BMS) includes memory devices having instructions stored thereon that, when executed by processors, cause the processors to perform operations including obtaining for each of a plurality of respective BMS objects respective semantic information for each of the plurality of the respective BMS objects, the respective semantic information being stored on the each of the respective BMS objects, identifying a plurality of predetermined classifications that pertain to the plurality of the respective BMS objects using the respective semantic information, classifying the plurality of BMS objects using the plurality of predetermined classifications, updating a semantic site model associated with the building site by including the respective semantic information associated with the plurality of the respective BMS objects and adjusting a plurality of parameters associated with the respective BMS objects using the semantic site model.

Abstract: An information processing device according to the present application includes a generation unit and a providing unit. The generation unit uses a model that is trained to learn a relationship between a criterion for classifying users of a first company and a criterion for classifying users of a second company to generate a criterion (common key) for classifying the users of the second company into a first category, from the criterion for classifying the users of the first company into the first category. The providing unit provides a criterion generated by the generation unit.

Abstract: A computer-implemented method for template generation may include: receiving a first plurality of variables, each of the first plurality of variables specifying a feature to be implemented in a new template for document generation; for each of a plurality of existing templates for document generation, determining a degree of similarity between the first plurality of variables and a plurality of variables included in the respective existing template; upon determining that none of the degrees of similarity respectively determined for the plurality of existing templates satisfies a similarity threshold, determining that a combination of variables from two or more of the plurality of existing templates has a degree of similarity with the first plurality of variables satisfying the similarity threshold; and generating the new template based on the two or more of the plurality of existing templates.

Abstract: The present disclosure provides user-interface methods and systems for submitting search requests to search engines and presenting search results therefrom customized using content preferences learned about a user, comprising sending query information to at least two search engines, including a query identifying desired content, and user information, including context information describing the environment in which the query information is being sent, and a user signature representing content preferences learned about the user; receiving at least one set of a search result and auxiliary information from the at least one search engine in response to sending the query information, including information describing attributes of the search result that led to the search result being chosen by the at least one search engine; ordering the at least one search result based at least in part on the auxiliary information; and presenting the ordered search results to the user.

Abstract: A computing system generates, for each of a plurality of sessions, a session representation indicating the order through which a user navigated through a plurality of webpages during the session, and generates for each pair of session representations, a score indicating how similar the session representations in each pair are to each other. The computing system further generates a plurality of clusters by clustering the session representations based on the score for each pair of session representations, determines an optimal number of clusters based on key performance indicators corresponding to each cluster of the plurality of clusters, and generates a natural language description for each cluster of the optimal number of clusters based on the key performance indicators associated with each cluster.

Abstract: Systems, methods, and computer-readable storage media for building knowledge graphs which map the aspects of entities, then transforming the graphs into vectors for a similarity comparison. The resulting vectors can be used to identify skills and competencies of individuals, which the system uses to compare those individuals to others. The system can then quantify who would make for a good replacement for a given individual and make an associated recommendation.

Abstract: A system may deliver personalized content to a user. The system may create a user persona based on demographic information and stored clickstream data of the user. The system may learn which functionalities the user typically uses on a webpage, and the system may create a personalized version of the webpage for the user.

Abstract: Methods, systems, apparatuses, and computer program products are described for providing content recommendations to a requestor. In implementations, user event records associated with media items and content types may be stored, for instance, in an event catalog. A set of user scores may be generated based on a user-content score model and the user event records, where each generated user score represents an affinity between a user and a corresponding content type of the plurality of content types. A set of title scores may also be generated for a media item based on a title-content score model, where each generated title score represents an affinity between the media item and a corresponding content type. In response to a request, the sets of scores may be combined to generate a set of content recommendations to provide to the requestor.

Abstract: A client device can identify user data pertaining to use of the client device by a user. The client device can determine at least one persona trait of the user based on the user data pertaining to the use of the client device by the user. The client device can receive persona categorization data, the persona categorization data specifying a plurality of persona categories and, for each persona category, a plurality of persona traits. Based on the at least one determined persona trait, the client device can assign the user to a persona category selected from the plurality of persona categories. Based on the persona category to which the user is assigned, the client device can identify information to present to users who are assigned to the persona category to which the user is assigned. The client device can present to the user the identified information.

Abstract: In some implementations, a method is performed by a device including a non-transitory memory and one or more processors coupled with the non-transitory memory. In some implementations, the method includes obtaining, by the device, engagement data that indicates engagement of a plurality of devices with one or more content items of a plurality of content items. In some implementations, the method includes detecting, by the device, a first event associated with a first time that occurs after a current time. In some implementations, the method includes identifying, by the device, a first content item from the plurality of content items based on the engagement data. In some implementations, the first content item satisfies an engagement criterion associated with the first event. In some implementations, the method includes rendering, by the device, the first content item at a second time that occurs prior to the first time.

Abstract: Embodiments of the disclosed technologies receive a first signal from a user session and create a first ranked list of content items. Based on the first signal, a first subset of the first ranked list is assigned to a first set of slots of the user session. A second subset of the first ranked list is assigned to a second set of slots of the user session. Based on user activity data and position context data, a second ranked list of content items is created. The second ranked list is assigned instead of the second subset to the second plurality of slots.