Embodiments of the present disclosure provide to a method and a device for acquiring a data model in a knowledge graph, an apparatus and a storage medium. The method includes: receiving a knowledge entry describing a relationship between an entity and an object; determining a plurality of candidate object types of the object according to at least one of the entity, the relationship and the object; determining an object type for generating a data model that matches the knowledge entry from the plurality of candidate object types based on a preset rule; and generating the data model based at least on the object type.

A method of propagating annotations of content items to a search query is disclosed. A strength of a correspondence between a search query and a listing of an item on a network-based publication system is determined. The strength of the correspondence is based on an analysis of a set of actions by a set of users who submitted the search query. A set of annotations is generated. The set of annotations is propagated to a search engine and used to enhance search results.

The cloud hybrid application storage management system spans local data center and cloud-based storage and provides a unified view of content and administration throughout an enterprise. The system manages synchronization of storage locations, ensuring that files are replicated, uniquely identified, and protected against corruption. The system ingests digital media assets and creates instances of the assets with their own identification and rights and houses the identification and relationships in a CAR (Central Asset Registry). The system tracks the different instances of the assets in multiple storage locations using the CAR, which is a central asset registry that ties together disparate digital asset management repository systems (DAMs) and cloud-based storage archives in which the instances reside. While the invention treats and manages multiple files/instances independently, the CAR identifies them as related to each other.

A method of identifying relationships between data collections is disclosed. Each data collection comprises a plurality of data records made up of data fields. The method comprises performing a relationship search process based on a first seed value and a second seed value. A first set of records from the data collections is identified based on the first seed value. A second set of records from the data collections is identified based on the second seed value. The process then searches for a common value across the first and second record sets, wherein the common value is a value which appears in a first field in a first record of the first record set and in a second field in a second record of the second record set, wherein the first record is from a first data collection and the second record is from a second data collection. In response to identifying the common value, an indication is output identifying a candidate relationship between the first field of the first data collection and the second field of the second data collection.

Systems and methods for controlling record relationship changes in a content management system. The content management system may have several layers of access controls, which may include a layer of access control at the object level, a layer of access control at the row level and a layer of access control at the field level. Access may be controlled at the object level by a user's security profile, at the object record level (or row level) by the user's role, and/or at the object field level by the user's role or a state in a document lifecycle. A secure inbound relationship attribute may be used to control record relationship changes. Actions for creating, deleting and reassigning are permitted only when the inbound relationship is editable according to the secure inbound relationship attribute.

Some embodiments of the invention provide a method for defining code-based policies. The method generates a policy-builder first view of a policy for display in a graphical user interface (GUI) by processing a syntax tree that is generated from a code second view of the policy. The method receives, through the policy-builder first view, a modification to a portion of the policy. To reflect the modification, the method updates a portion of the syntax tree that corresponds to the portion of the policy that is affected by the modification. Based on the updating of the syntax tree, the method updates the code second view by modifying a portion of the code second view that corresponds to the updated portion of the syntax tree.

In an example, a computer-implemented method to group graphical objects includes displaying, on a display device, a graphical diagram with multiple graphical objects that represent data of a data source. The method includes receiving input to define one or more groups. The method includes, in response to the input, generating one or more containers, each of the one or more containers representing a different one of the one or more groups; and graphically depicting membership of the graphical objects in the one or more groups by relative arrangement of the graphical objects and the one or more containers according to group membership of each of the graphical objects.

In one or more embodiments, a system generates a navigable interface for traversing sets of content based on system-determined relationships between the sets of content. The system uses a trained machine learning model to determine characteristics, such as layout, for sets of content. The characteristics are mapped to a content type. The system organizes the sets of content, based on respective content type, into a set of pages of a multipage navigable interface. Furthermore, the system selects navigational relationships between the sets of content based on respective content type. The navigational relationships are implemented via interface elements that allow for navigation between the pages of the navigable interface including corresponding sets of content.

Proposed are concepts for identifying data relationships from a spreadsheet. Such a concept may transform formulae by replacing the variables in each formula with descriptive labels. This may, for example, expressing the transformed formulae in terms that have more meaning to a user, the facilitating understanding and/or analysis that would otherwise not be possible with the existing tools.

In an approach to improve query optimization in a database management system, embodiments identify opportunities for improvement in a cardinality estimate using a workload feedback process using a query feedback performed during query compilation. Embodiments identify correlations and relationships based on the structure of the query feedback and the runtime feedback performed, and collects data from the execution of a query to identify errors in estimates of the query optimizer. Further, embodiments submit the query feedback and the runtime feedback to a machine learning engine to update a set of models. Additionally, embodiments update a set of models based on the submitted query feedback and runtime feedback, and output a new, updated, or re-trained model based on collected data from the execution of the query to identify the errors in estimates of the query optimizer, the submitted query feedback and the runtime feedback, or a trained generated mode.