Abstract: A system and a method are disclosed for receiving, from a source of a plurality of candidate sources, a payload comprising content and metadata. The system selects a destination to which to route the payload based on the source and the content, and generates an entry at the destination based on the content. The system inputs the metadata into a classification engine, and receives, as output from the classification engine, one or more classifications for the payload. The system applies a metadata tag to the entry, the metadata tag indicating the one or more classifications. The system receives a search request from a client device specifying at least one of the one or more classifications, and, in response to receiving the search request, provides the entry to the client device based on a matching classification.

Abstract: According to one implementation, a system includes a computing platform having processing hardware, a system memory storing a software code; and a machine learning model based classifier. The processing hardware is configured to execute the software code to receive tagging quality assurance (QA) data including multiple terms applied as tags and corrections to those tags, to identify, using the tagging QA data, a first problematic term, and to classify, using the machine learning model based classifier, the first problematic term as one of confusing or flawed. The processing hardware is further configured to execute the software code to obtain, when the first problematic term is classified as confusing, a comparative sample for clarifying use of the first problematic term, and to obtain, when the first problematic term is classified as flawed, modification data for editing a predetermined annotation taxonomy including the first problematic term.

Abstract: A method, software, database and system for attribute partner identification and social network based attribute analysis are presented in which attribute profiles associated with individuals can be compared and potential partners identified. Connections can be formed within social networks based on analysis of genetic and non-genetic data. Degrees of attribute separation (genetic and non-genetic) can be utilized to analyze relationships and to identify individuals who might benefit from being connected.

Abstract: A computer implemented method for classifying at least one source dataset of a computer system. The method may include providing a plurality of associated reference tables organized and associated in accordance with a reference storage model in the computer system. The method may also include calculating, by a data classifier application of the computer system, a first similarity score between the source dataset and a first reference table of the reference tables based on common attributes in the source dataset and a join of the first reference table with at least one further reference table of the reference tables having a relationship with the first reference table. The method may further include classifying, by the data classifier application, the source dataset by determining using at least the calculated first similarity score whether the source dataset is organized as the first reference table in accordance to the reference storage model.

Abstract: A client device operates by: extracting a set of deletion candidate data from application data stored in memory, wherein the deletion candidate data corresponds to a plurality of photographs; generating feature detection data for each of the plurality of photographs by performing a computer vision function on the each of the plurality of photographs; generating a subset of the set of deletion candidate data for deletion by selecting ones of the set of deletion candidate data that compare favorably to deletion criteria data, wherein the deletion criteria data indicates at least one unfavorable feature and wherein the subset of the set of deletion candidate data is generated by selecting ones of the plurality of photographs with feature detection data that indicates the at least one unfavorable feature is included in the ones of the plurality of photographs; and facilitating deletion of at least a portion of the subset of the set of deletion candidate data from the memory.

Abstract: A system and methods for generating and applying learning agents in simulated environments, in which an agent simulation is selected, one or more agent goals are received, and agents are created which are individual instances of the agent simulation with each agent having at least one of the agent goals, wherein the agents are used in the execution of an environment simulation which dynamically changes based on the collective behavior of the agents.

Abstract: The present disclosure relates to methods and systems for querying data in a data repository. According to a first aspect, this disclosure describes a method of querying a database, comprising: receiving, at a computing device, a plurality of keywords; determining, by the computer device, a plurality of datasets relating to the keywords; identifying, by the computer device, metadata for the plurality of datasets indicating a relationship between the datasets by examining an ontology associated with the datasets; providing, by the computer device, one or more suggested database queries in natural language form, the one or more suggested database queries constructed based on the plurality of keywords and the metadata; receiving, by the computing device, a selection of the one or more suggested database queries; and constructing, by the computer device, an object view for the plurality of datasets based on the selected query and the metadata.

Abstract: A method for assisting selection of an accommodation by an accommodation search system includes receiving user credentials from a user device; receiving trip parameters from the user device; determining a basic list of accommodations that correspond with the trip parameters; determining one or more factors that apply to each individual accommodation of the basic list of accommodations; applying a weight value to each of the one or more factors that apply to each individual accommodation of the basic list of accommodations; aggregating the weight values of the one or more factors that apply to each individual accommodation to determine an aggregate weighted score for each individual accommodation of the basic list of accommodations; sorting the basic list of accommodations into a sorted list of accommodations based on the aggregate weighted score for each individual accommodation; and providing the sorted list of accommodations to the user device for viewing by a user.

Abstract: Techniques and technologies for providing a fully managed datastore for clients to securely store, discover, retrieve, remove, and share curated data, or features, to develop machine learning (ML) models in an efficient manner. The feature store service may provide clients with the ability to create and store feature groups that include features and associated metadata providing clients with a quick understanding of features so that they may determine which features are suitable for training ML models and/or use with ML models. The feature store service may provide first a data store configured to store the most recent values associated with a feature group, such that client can access the features and utilize ML models to make real-time predictions with low latency and high throughput, and a second datastore configured to store historical values associated with a feature group, such that a client can utilize the features to train ML models.

Abstract: In one embodiment, a method includes receiving a request to access a first record in a plurality of records, where the first record describes a first set of attributes of a first entity, determining the first record is linked to a globally unique entity identifier, identifying one or more second records linked to the unique entity identifier, where the one or more second records describe one or more second sets of attributes of the first entity, generating a fused record comprising descriptions of attributes of the first entity from the first set and second sets of attributes, where the fused record is generated by deduping the plurality of records to associated the first record and the one or more second record with the unique entity identifier and compiling the first set and one or more second sets of attributes, and sending, in response responsive to the request to access the first record, instructions for presenting the fused record.

Abstract: The application aids users by providing supplemental audio content. For example, the application determines a subject of content provided to user equipment during a first time period of the content. The application retrieves a profile associated with the user equipment and retrieves supplemental audio related to the profile and related to the subject of the content. The application detects a supplementation point in the content corresponding with audio content similar to a supplementation signature and transmits the supplemental audio to the user equipment for output at the supplementation point.

Abstract: A computer system is provided that stores reference data records and event data records that each correspond to one of the reference data records. Tokens are generated from the reference data records and sorted into subsets. Each reference data record that has a given token is included in the corresponding subset. A correlation value is calculated between members (e.g., the reference data records) of the subsets. The correlation values are calculated by determining a common time, calculating a reference value, calculating a percentage difference from the reference value, and then determining a correlation value (e.g., a correlation coefficient) using the percentage difference.

Abstract: A computer-implemented method for targeted sweep of a key-value data storage is provided. The method comprises before a write transaction to a database having a key value store commits, and before each of one or more write commands of the write transaction are persisted to the key value store, writing an entry for each of the one or more write commands to an end of a targeted sweep queue, the entry comprising metadata including: data identifying a cell to which the write command relates, a start timestamp of the write transaction, and information identifying a type of the write transaction.

Abstract: A data catalog system that is configured to automatically generate synthetic datasets based upon original datasets cataloged by the data catalog system, wherein each synthetic dataset comprises synthetic data that is generated using one or more data generation techniques. The data catalog system may access an original dataset and harvest associated metadata information and generate catalog information for the original dataset. The data catalog system may then generate a synthetic dataset based upon the original dataset and its harvested metadata information. The data catalog system may also generate catalog information for the generated synthetic dataset. The catalog information generated for the original dataset may be updated to refer to the newly generated synthetic dataset and its catalog information. The catalog information generated for the synthetic dataset may include references to the original dataset and its catalog information to inform a user of the original dataset about the synthetic dataset.

Abstract: Various embodiments of the present application set forth a computer-implemented method that includes receiving at a mobile device from a first data source, a plurality of live data snapshots, each live data snapshot included in the plurality of live data snapshots being associated with a different point in time, generating, based on a presentation template and a first live data snapshot included in the plurality of live data snapshots, a first presentation data snapshot, receiving, at the mobile device from a wearable device, a plurality of data requests, wherein each data request included in the plurality of data requests comprises a different request for data to be presented by the wearable device and is received at a different point in time, and a first rate of receiving the plurality of data requests by the mobile device is lower than a second rate of receiving the plurality of live data snapshots by the mobile device, and in response to receiving a first data request included in the plurality of data req

Abstract: Described herein are methods, systems, and computer-readable storage media for automatic and efficient updating of databases and database schemas. Techniques include generating an identification of a task of an application associated with a database through a machine learning process for monitoring database activity. Further, patterns of the application's access to data stored in the database may be observed and provided along with the identified task to a feedback loop to identify changes in the application's access to data in a database. Techniques further include automatically updating a schema of the database based on the identified changes in the application's access to data stored in the database.

Abstract: Methods, apparatuses, and computer program products are disclosed for synthetic data generation and dynamic processing model selection. An example method includes receiving a request for synthetic data generation where the request for synthetic data generation includes one or more configuration data parameters. The method further includes selecting at least one processing model from amongst a plurality of processing models based upon the one or more configuration data parameters. The method also includes generating one or more synthetic datasets that include one or more synthetic data values via the selected at least one processing model. The method further includes providing, to a user via a user interface, the one or more generated synthetic datasets.

Abstract: Systems and methods are described for training a machine learning (ML) model to group notable events reflecting operation of a computing system into episodes of related events reflecting an incident on the computing system, such as to enable root cause analysis of the incident. The ML model is trained using pairwise binary similarity labels (PBSLs) indicating that two events must or must not be grouped together. An interface is provided that facilitates rapid generating of PBSLs by relocating one or more events from a first episode to a second episode. The relocation input is translated into PBSLs that are then used to train the ML model.

Abstract: Embodiments of the present invention relate to a Lookup and Decision Engine (LDE) for generating lookup keys for input tokens and modifying the input tokens based on contents of lookup results. The input tokens are parsed from network packet headers by a Parser, and the tokens are then modified by the LDE. The modified tokens guide how corresponding network packets will be modified or forwarded by other components in a software-defined networking (SDN) system. The design of the LDE is highly flexible and protocol independent. Conditions and rules for generating lookup keys and for modifying tokens are fully programmable such that the LDE can perform a wide variety of reconfigurable network features and protocols in the SDN system.

Abstract: Described herein are various techniques for managing media related to a construction project, which may relate to one or more buildings to be built and/or renovated as part of the construction project. In accordance with techniques described herein, the media may be managed according to information regarding the construction project that is stored by one or more other systems separate from a media management system. The other systems may be construction information management systems that each store information regarding a construction project, including information relating to planning and/or execution of the construction project. For example, the media management system may generate tags based on the information regarding the construction project, may be trained to recognize features in the media that relate to the tags, and add the appropriate tags to the media based on the recognized features.