16 results about "Context property" patented technology

Certain aspects of the disclosure provide for information retrieval that exploits context derived from document structure. Source documents can be preprocessed to identify fields and determine context attributes related to each field based on the structural layout of a source document. Resource documents can also be preprocessed to segment a resource document into passages and determine context related to the passages based on structural layout. Queries pertaining to a field can be enhanced by adding context metadata associated with the field. A query embedding can be generated and compared with previously generated passage embeddings to locate candidate matches based on similarity. A machine learning model can be provided with the top-ranked passages and tasked with re-ranking the passages based on relevancy to the original query. The highest re-ranked passage or set of passages can be output in response to the query.

A contextual natural language query response system (contextual system) leverages contextual attribute-identifier mappings to improve large language model (LLM) responses to natural language queries. The contextual system replaces identifiers in natural language queries with attributes according to a contextual mapping table between identifiers and attributes to generate attribute-based natural language queries. The contextual system then uses retrieval-augmented generation with the attributes-based natural language queries to prompt an LLM to generate attribute-based database queries. The contextual system uses the mappings from the contextual mapping table to convert the attribute-based database queries to identifier-based database queries and queries a database with the identifier-based database queries. The contextual system responses to the natural language queries using results from querying the database.

An example operation may include at least one of storing first interaction content with a service provider; receiving second interaction content from a communication session between a source device and a service provider device of the service provider; identifying at least one contextual attribute associated with the source device; determining a response based on execution of at least one large language models (LLMs) on the second interaction content, the at least one contextual attribute associated with the source device, and the first interaction content with the service provider; and outputting the response to at least one of the source device and the service provider device during the communication session.

Some embodiments are directed to systems and methods that dynamically generate user interfaces according to a user's task, context, or current environment. In one aspect, a computer system includes one or more processors and memory. The computer system obtains a stream of sensor data from one or more sensors. The computer system generates a context attribute based on the stream of sensor data, the context attribute characterizing a condition of a physical environment or a user, The computer system, based on the context attribute, determines a layout configuration of a user interface to be presented to the user. The computer system dynamically renders the user interface for the user based on the layout configuration and displays the user interface on the display of the user interface.

A method for context-based insertion of a three-dimensional (3D) object into a photograph includes analyzing, by a machine-learning model, a scene of the photograph to determine contextual attributes of the scene. The method also includes selecting, based on the contextual attributes, a 3D asset from a set of 3D assets. The method further includes posing the 3D asset using geometric information determined from the scene such that the posed 3D asset conforms to one or more of perspective, orientation, or surface geometry of the photograph. The method also includes adding a 3D element contextually associated with the scene, the 3D element being selected and positioned in accordance with the contextual attributes. The method further includes generating an output photograph that comprises the posed 3D asset and the 3D elements integrated into the photograph.

Techniques are provided for access control using policy-based dynamic context evaluation. One method comprises obtaining an access request comprising a first attestation identifier that is based on an evaluation of a first set of context attributes, associated with the request and identified by evaluating a context policy. In response to obtaining the request: a second set of context attributes for evaluating the first attestation identifier may be dynamically determined by evaluating the context policy. Values for the second set of context attributes may be obtained to generate a second attestation identifier. The first attestation identifier and the second attestation identifier may be compared and access to the resource may be controlled based on a result of the comparison. The first attestation identifier may be generated by a context attestor and the comparison may be performed by a context enforcer.

The present application relates to the technical field of digital twinning, in particular to a low-code device information digital twinning model creation method, which builds a model framework by dragging and dropping predefined input, output and logic processing components from a component library to a canvas, flexibly configures component parameters using a context attribute panel, and establishes data flow between component ports using intuitive graphical connection operations, and performs real-time data type checking to ensure the correctness of the connection. Finally, by configuring the address binding of I / O components with external controllers or data sources, and supporting real-time data monitoring and input forced assignment during the simulation stage, a device information model is constructed that is complete in function and can directly interact with the real control system for data verification. The traditional code writing work is transformed into visual configuration and connection operation, greatly reducing the technical threshold and development workload, enabling domain experts to quickly build, modify and debug models without deep programming background.

This paper discloses the automated application of context-based image editing and personalized visual photograph preferences using artificial intelligence. A method for context-based insertion of three-dimensional (3D) objects into a photograph includes: analyzing the scene of the photograph using a machine learning model to determine the scene's contextual properties. The method also includes: selecting 3D assets from a set of 3D assets based on the contextual properties. The method further includes: posing the 3D assets using geometric information determined from the scene such that the posed 3D assets conform to one or more of the photograph's viewpoint, orientation, or surface geometry. The method also includes: adding 3D elements associated with the scene context, which are selected and positioned according to the contextual properties. The method further includes: generating an output photograph that includes the posed 3D assets and the 3D elements integrated into the photograph.

Some embodiments are directed to systems and methods that dynamically generate user interfaces according to a user's task, context, or current environment. In one aspect, a computer system includes one or more processors and memory. The computer system obtains a stream of sensor data from one or more sensors. The computer system generates a context attribute based on the stream of sensor data, the context attribute characterizing a condition of a physical environment or a user, The computer system, based on the context attribute, determines a layout configuration of a user interface to be presented to the user. The computer system dynamically renders the user interface for the user based on the layout configuration and displays the user interface on the display of the user interface.

A method for managing automation tasks for a subject entity is disclosed. The method includes identifying context parameters associated with the subject entity among a set of entities. The context parameters comprise a hierarchical context parameter, a parallel context parameter, or a self-context parameter. Further, the method includes inferring characteristics of the subject entity based on the identified context parameters and relationships between the subject entity and one or more other entities within the set of entities. The characteristics indicate an operational and contextual attributes of the subject entity. Furthermore, the method includes assigning entity tags to the subject entity based on the characteristics. The entity tags indicate a representation of the subject entity's contextual and operational attributes. Furthermore, the method includes triggering an automation task associated with the subject entity based on the assigned entity tags.

Systems for and methods of privacy-preserving metadata extraction from technical artifacts using machine-learning are disclosed. The system includes at least a processor and a memory communicatively connected to the at least a processor. The memory contains instructions configuring the at least a processor to: receive a technical artifact including textual content and graphical symbols, extract a plurality of feature instances from the technical artifact, generate, for each feature instance of the feature instances, at least one feature value, map the at least one feature value into a non-reversible feature representation, and determine, using a trained machine-learning classifier, at least one contextual attribute as a function of the non-reversible feature representation. The at least one feature value provides context to each feature instance of the plurality of feature instances.

A method of establishing trust between entities in a decentralized data processing environment implementing a credentials bridge middleware platform. The method including steps of: receiving input claims at a claim normalizer component, where the input claims are represented in a plurality of assertion formats, parsing the received input claims at the claim normalizer component using a parser extension, transforming the parsed input claims at the claim normalizer component into a common syntactic representation, receiving, at a claim evaluator component, the transformed parsed claims in the common syntactic representation, along with normalized attributes, from the claim normalizer component, fetching, by the claim evaluator component, context attributes from an attribute interface component, evaluating, at the claim evaluator component, a claim transformation policy using the normalized attributes and the context attributes and generating, at the claim evaluator component, obligatory actions that is used to generate Claims Execution Policies (CXP) for establishing trust between entities in the decentralized data processing environment.

The application provides a background permission management system and method of adaptive risk control. It includes a data acquisition module for collecting behavior data and environment data associated with an account and converting the data into an event stream; a context management module for associating a context attribute set with the event stream; a feature construction module for generating a multi-dimensional feature vector based on the event stream and the context attribute set; an adaptive risk assessment module for calling at least two heterogeneous models to perform parallel reasoning on the multi-dimensional feature vector; a decision engine module for mapping risk weights to access control instructions and audit instructions; an audit module for recording audit data according to the audit instructions; and a permission management module for calculating permission weights according to decay parameters and generating permission recovery instructions or maintenance instructions according to threshold judgments. The application can realize event stream unification and context binding, real-time risk assessment and strategy linkage, and permission adaptive recovery closed loop.

A contextual natural language query response system (contextual system) leverages contextual attribute-identifier mappings to improve large language model (LLM) responses to natural language queries. The contextual system replaces identifiers in natural language queries with attributes according to a contextual mapping table between identifiers and attributes to generate attribute-based natural language queries. The contextual system then uses retrieval-augmented generation with the attributes-based natural language queries to prompt an LLM to generate attribute-based database queries. The contextual system uses the mappings from the contextual mapping table to convert the attribute-based database queries to identifier-based database queries and queries a database with the identifier-based database queries. The contextual system responses to the natural language queries using results from querying the database.

A method includes extracting a set of frames from a video, detecting one or more contextual attributes in the extracted set of frames, wherein the one or more contextual attributes correspond to contextual attributes associated with a plurality of contextual groups, selecting sample frames from the extracted set of frames for each of the plurality of contextual groups for which the one or more detected contextual attributes correspond, generating at least one classification for the video based on at least a portion of the selected sample frames, and generating a context structure including the one or more detected contextual attributes and the at least one classification for the video.

An apparatus comprising a processor coupled to a memory, wherein the processor is to: receive at least one context attribute comprising one or more of: system and environmental attributes, user input, device information, and sensory information; select a security context in accordance with the received at least one context attribute; determine a protection action in accordance with the selected security context; determine one or more flow controls in accordance with the determined protection action and the at least one context attribute; send the one or more flow controls to one or more IoT devices, wherein the one or more flow controls are to cause the one or more IoT devices to perform the protection action.