17383284. SEMANTICALLY-AUGMENTED CONTEXT REPRESENTATION GENERATION simplified abstract (QUALCOMM Incorporated)
SEMANTICALLY-AUGMENTED CONTEXT REPRESENTATION GENERATION
Organization Name
Inventor(s)
Arvind Krishna Sridhar of San Diego CA (US)
Ravi Choudhary of San Diego CA (US)
Lae-Hoon Kim of San Diego CA (US)
Erik Visser of San Diego CA (US)
SEMANTICALLY-AUGMENTED CONTEXT REPRESENTATION GENERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 17383284 titled 'SEMANTICALLY-AUGMENTED CONTEXT REPRESENTATION GENERATION
Simplified Explanation
The patent application describes a device that uses memory and processors to generate a semantically-augmented representation of context.
- The device stores instructions in memory and uses processors to execute these instructions.
- The processors provide context and items of interest to a dependency network encoder, which generates a semantic-based representation of the context.
- The processors also provide the context to a data dependent encoder, which generates a context-based representation.
- The semantic-based representation and the context-based representation are combined to generate a semantically-augmented representation of the context.
Potential Applications
This technology has potential applications in various fields, including:
- Natural language processing: The device can be used to enhance language understanding and generation systems by providing a semantically-augmented representation of context.
- Information retrieval: The semantically-augmented representation can improve the accuracy and relevance of search results by considering the context of the query.
- Machine learning: The device can be used to improve the performance of machine learning models by providing a richer representation of context.
Problems Solved
The technology addresses the following problems:
- Lack of context-awareness: By combining semantic-based and context-based representations, the device can better understand and represent the context in which information is presented.
- Insufficient representation: The device provides a more comprehensive representation of context, which can lead to improved performance in various applications.
- Information overload: The semantically-augmented representation helps filter and prioritize information, making it easier to process and understand large amounts of data.
Benefits
The technology offers several benefits:
- Enhanced understanding: The semantically-augmented representation improves the device's ability to understand and interpret context, leading to more accurate and relevant results.
- Improved performance: By considering both semantic and context-based representations, the device can achieve better performance in tasks such as language processing, information retrieval, and machine learning.
- Efficient information processing: The technology helps filter and prioritize information, making it easier to process and extract meaningful insights from large datasets.
Original Abstract Submitted
A device includes a memory configured to store instructions. The device also includes one or more processors configured to execute the instructions to provide context and one or more items of interest corresponding to the context to a dependency network encoder to generate a semantic-based representation of the context. The one or more processors are also configured to provide the context to a data dependent encoder to generate a context-based representation. The one or more processors are further configured to combine the semantic-based representation and the context-based representation to generate a semantically-augmented representation of the context.
