Abstract: Performance of a collection of machines, arranged in a linear sequence of machines that form a linear communication orbit (LCO), is monitored. Multiple machines in the LCO receive, via the LCO, a set of rules (or various subsets of the same set of rules), each rule specifying one or a combination of conditions (e.g., a performance metric and corresponding criterion) for satisfying the rule, evaluate those rules with respect to locally occurring events and local processes, and stores results of those evaluations in a local database. In response to a performance query sent to the machines via the LCO, each of the machines returns a report, including information identifying processes whose performance during the specified time period satisfies at least one rule in the set of one or more rules. Those reports are aggregated and used to present performance information to a user.

Abstract: A bidirectional mapping is established between network content and application programs, based on declarations at both the network content and at the application. Additionally, bidirectional mapping can provide for deep links, which can associate specific network content with a specific presentation of data in an application program. The identification format for such deep links can conform to a predetermined standard or it can be custom implemented according to a format declared either as part of the network content or the application program. The bidirectional mapping is then utilized by a lookup service to provide functionality to a third-party entity. The lookup service can identify, to the entity, application programs associated with network content specified by that entity and network content associated with application programs specified by that entity.

Abstract: Embodiments are directed to managing data in a file system. A source bucket that contains a plurality of objects on a cloud computing environment may be determined. The source bucket may be associated with a target directory in the file system based on an integration relationship. Object keys from the object store may be provided based on a query and filter rules such that each object key corresponds to an object in the source bucket that conforms to the filter rules. Source objects in the source bucket may be determined based on the object keys such that each source object corresponds to one of the object keys. Target files that correspond to the source objects may be determined based on the integration relationship. In response to determining changed target files or changed source objects, copying the changed source objects or the changed target files to the target directory.

Abstract: One embodiment comprises a method in which an integrated multi-user analytics server platform is integrated with a dynamic runtime ETL tool to allow dataflows created or developed in a dynamic runtime environment provided by the ETL tool to be saved in a novel dataflow file container. The method includes: presenting a user interface for an analytics server platform; receiving user input via this user interface indicating an action to be performed as to a first dataflow; the analytics server platform accessing a first file container corresponding to the first dataflow, where the first file container is stored in a data store connected to the analytics server platform; in response to receiving the user input, the analytics server platform accessing APIs of the dynamic runtime ETL tool to initiate the ETL tool, which then performs the action with respect to the first dataflow.

Abstract: An event processing system for processing events in an event stream is disclosed. The system is configured for determining a stage for a continuous query language (CQL) query being processed by an event processing system and/or determining a stage type associated with the stage. The system is also configured for determining a transformation to be computed for the stage based at least in part on the stage type and/or determining a classification for the CQL query based at least in part on a plurality of rules. The system can also be configured for generating a transformation in a Directly Acyclic Graph (DAG) of a data transformation pipeline for the stage based at least in part on the partitioning criteria for the stage. In some examples, the system can also be configured for determining a partitioning of the stage based at least in part on the transformation.

Abstract: A schema for a dataset is identified by identifying a dataset comprising data and relationships between data pairs. An original schema is identified for the dataset. This original schema comprises an organizational structure. An initial fit between the dataset and the original schema is determined. The initial fit quantifying a conformity of the data in the dataset to the organizational structure of the original schema. A plurality of additional schemas are identified. Each additional schema is a distinct organizational schema. The dataset is partitioned into a plurality of subsets. Each subset comprises a modified fit quantifying a modified conformity of subset data in each subset to one of the original schema and the additional schemas. The modified fit is greater than the original fit.

Abstract: Methods, systems, and computer-readable media for query language interoperability in a graph database are disclosed. Data elements are inserted into a graph database using one or more of a plurality of graph database query languages. The graph database query languages comprise a first graph database query language associated with a first data model and a second graph database query language associated with a second data model. The data elements are stored in the graph database using an internal data model that differs from the first and second data models. One or more of the data elements are retrieved from the graph database based at least in part on a query. The query is expressed using a different graph database query language than the graph database query language used to insert the one or more retrieved data elements.

Abstract: The present disclosure relates to systems and methods for an intelligent assistant (e.g., a chatbot) that can be used to enable a user to generate a machine learning system. Techniques can be used to automatically generate a machine learning system to assist a user. In some cases, the user may not be a software developer and may have little or no experience in either machine learning techniques or software programming. In some embodiments, a user can interact with an intelligent assistant. The interaction can be aural, textual, or through a graphical user interface. The chatbot can translate natural language inputs into a structural representation of a machine learning solution using an ontology. In this way, a user can work with artificial intelligence without being a data scientist to develop, train, refine, and compile machine learning models as stand-alone executable code.

Abstract: In a database environment including a plurality of logical object definitions having relationships defined according to a schema, and logical object instances following the logical object definitions include attribute names and respective attribute values indicating status of an enterprise in an enterprise resource planning system, the method can receive a starting exception definition specifying a first query against the logical object instances and derive a new exception definition based on the starting exception definition and one or more stored, acted-upon exception definition proposals. The first query can include one or more initial situational trigger conditions. The new exception definition can specify a second query against the logical object instances and the second query can include one or more modified situational trigger conditions.

Abstract: The present disclosure is generally directed to the generation of domain-specific, voice-activated systems in interconnected networks. The system can receive input signals that are detected at a client device. The input signals can be voice-based input signals, text-based input signals, image-based input signals, or other type of input signals. Based on the input signals, the system can select domain-specific knowledge graphs and generate responses based on the selected knowledge graph.

Abstract: One or more computing devices, systems, and/or methods for content recommendation based upon continuity and grouping information of attributes are provided herein. User interaction data specifying whether users interacted with content items, user attributes of the users, and content attributes of the content items is obtained. A data structure is populated with the user interaction data. The data structure is modified by inserting a set of sub-fields into the data structure for a user attribute. A sub-field is populated with a value representing an option of the user attribute. The set of sub-fields are an encoding of continuity information and grouping information representing options for the user attribute. The data structure is processed using machine learning functionality to generate a model. The model is utilized to generate a prediction as to whether a user will interact with a content item.

Abstract: A method for updating cloud resource tags is provided. The tag associated with a cloud resource may assign the cloud resource to one or more categories to enable tracking of the cloud resource. The method may include determining, based on a synchronization profile, the scope of the update. For example, the scope of the update may encompass individual resources, groups of resources, and/or subscriptions. A metadata data store may be queried to retrieve mapping rules corresponding to tags of resources from one or more cloud service providers that are within the scope of the update. If the value of a tag does not match the value specified by the corresponding mapping rule, the value of the tag may be updated to match the value specified by the mapping rule. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: Various implementations of the invention store and retrieve data via a computing processor. The data is comprised of a plurality of data records with a sequentially changing data value and an other data value. For each data record in the plurality of data records, the computing processor causes the data record to be aggregated and stored with other data records in a first data storage container corresponding to a first data storage space based on the sequentially changing data value of the data record (i.e., sequential data space), and causes the data record to be aggregated and stored with other data records in a second data storage container corresponding to a second data storage space (i.e., finite data space). The data records in the second data storage container are stored based on the other data value. When a query is made against the data, the computing processor determines whether the query is best evaluated in the sequential data space or the finite data space.

Abstract: A computer system and method may be used to generate a product catalog from one or more websites. One or more product pages on the websites may be identified and parsed. Attribute information may be identified in each page. A learning engine may be utilized to predict at least one attribute value. The attribute information and the predicted attribute value may be stored in a database.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that creates a machine learning model with k-means clustering. In some implementations, an instruction to create a model is obtained. A data set including geographic data and non-geographic data is received. The data set includes multiple data entries. Geographic centroids are determined from the geographic data. The data set is analyzed to obtain statistics of the data set. Transformed data is generated from the data set, the statistics, and the geographic centroids. A model is generated with the transformed data, the model indicating multiple data groupings.

Abstract: Methods, apparatuses, and computer-readable products for selecting tracks. A plurality of request parameters are received from a client device. Based on those request parameters, plurality of bans, history track attributes, and artist identifiers are loaded from a database. A most recent discovery track is calculated based on the plurality of histories and the plurality of artist identifiers. An artist identifier is repeatedly selected from the plurality of artist identifiers along with a track type from a set of track types until a predetermined number of artist identifier and track type pairs have been selected. A plurality of candidate tracks for each selected artist identifier are loaded from a database. One track of the plurality of candidate tracks is repeatedly selected for each artist identifier and track type pair until one track has been selected for each pair of the predetermined number of artist identifier and track type pairs.

Abstract: A system and method for collecting and processing data over a communications network. A data mining marshaller module associates each plugin to a particular data source and manages the plugin to periodically retrieve unstructured data from the data source based on a plurality of data items to be monitored on behalf of a plurality of users. The plugins convert unstructured data received from the data sources to structured data and the data marshaller module stores the structured data in a database. This enables the system and method to aggregate and display the structured data in multiple graphical representations according to the user's preference.

Abstract: A machine-learning model may be previously trained with a supervised learning algorithm to identify whether a pair of labels provided as input are similar. A locality sensitive hashing forest (LSH) may be generated for the set of candidate labels. When a user later identifies an input label (e.g., by search query, by interface selection, etc.) the input label may be used to query the LSH forest to identify a subset of the candidate labels. This subset may be used to generate respective pairs comprising the input label, one of the subset candidate labels, and a corresponding feature set generated for the pair. This data may be provided to the model to identify a degree to which the pair of labels are similar. The user may be provided one or more recommendations including similar terms identified from the model's output.

Abstract: In an approach for a conversational search in a content management system, a processor trains a deep learning model to learn semantic analysis of a plurality of user queries to identify intents and entities in the user queries. A processor analyzes the content management system to extract content keywords to generate a domain ontology. A processor augments the domain ontology based on the identified intents and entities in the user queries by the deep learning model. A processor tags the content keywords with metadata based on the domain ontology. A processor maps the intents and entities extracted from a current user query of a user to the content keywords extracted from the content management system to form a metadata keyword. A processor searches the content management system for a content based on the metadata keyword. A processor returns a search result for the current user query.

Abstract: A device, system and process for controlling document access using hierarchical paths is provided. A query, received from a requesting device, comprises: a search string for searching a document database; and an identifier associated with a user. A security permissions database is accessed using the identifier to receive permissible hierarchical document access paths indicating document access permissions associated with the identifier. A modified query includes the permissible hierarchical document access paths. The modified query used to access an index of the document database, the index comprising: a searchable content portion, and corresponding hierarchical document access paths, of a document. Document identifiers are received that identify only the documents having: respective searchable content portions that include the search string of the modified query; and at least one respective corresponding hierarchical document access path encompassed by the permissible hierarchical document access paths.