Hierarchical Data Package Decoding for Fast Relevant Data Retrieval
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Solution Overview
Problem
Devices often struggle to quickly and efficiently identify relevant information from large data sets received over high-bandwidth networks, especially when processing power or memory is limited, leading to data being less or unusable.
Innovation Solution
A hierarchical multi-layer data package is encoded with summaries and metadata, allowing devices to quickly identify information of interest and decide whether to decode further, using a system with an information manager, encoder, and decoder to manage compression and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If large amounts of data are transmitted over high-bandwidth networks, then data transmission speed is improved, but the ability to quickly identify relevant information deteriorates due to device processing limitations
Solution Approach 1:
The patent segments the large data set into multiple hierarchical layers, where each layer contains summaries and metadata that enable quick scanning. The data is organized into coarse-grained groups at higher levels and finer-grained details at lower levels, allowing receivers to efficiently navigate and identify relevant information without processing the entire data set.
Solution Approach 2:
The patent applies preliminary action by pre-computing and embedding summaries, metadata, and organizational structures into the data package before transmission. This preprocessing enables the receiving device to quickly identify and retrieve relevant information without performing extensive real-time analysis, thus resolving the contradiction between fast transmission and efficient information identification.
2Loss of information
If comprehensive data is transmitted to ensure completeness, then data completeness is improved, but device memory requirements worsen
Solution Approach 1:
The patent implements a nested hierarchical structure where data is organized into multiple levels of abstraction. Higher layers contain summaries and metadata that provide overviews, while lower layers contain detailed information. This nesting allows the system to maintain complete data while enabling devices to load and process only the necessary portions at each level, reducing memory requirements.
Solution Approach 2:
The patent applies local quality by providing different levels of data detail in different hierarchical layers. Summary information at higher levels provides quick contextual understanding with minimal memory usage, while detailed information at lower levels is available on-demand. This allows receivers to allocate memory efficiently based on their specific information needs and device capabilities.
3Measurement precision
If detailed information is provided to ensure accuracy, then information precision is improved, but processing time worsens on resource-constrained devices
Solution Approach 1:
The patent implements a dynamic information retrieval approach where the level of detail processed is adjusted based on the receiver's needs and device capabilities. The hierarchical structure allows receivers to start with coarse summaries for quick assessment and dynamically drill down to more detailed levels only when necessary, optimizing the balance between information precision and processing time.
Solution Approach 2:
The patent applies partial action by enabling receivers to process only the portion of data necessary for their specific needs. The hierarchical organization with summaries and metadata allows devices to identify and retrieve only relevant subsets of the complete data set, avoiding the need to process all detailed information and thus reducing processing time while maintaining necessary precision.
4Stability of the object's composition
If data is organized from sender's perspective to maintain structure, then organizational consistency is improved, but receiver's ability to quickly identify relevant information deteriorates
Solution Approach 1:
The patent adds a new hierarchical dimension to the data organization by creating multiple levels of abstraction. The original sender-oriented structure is preserved at the foundational level, while additional hierarchical layers with summaries, metadata, and cross-references are superimposed. This multi-dimensional organization enables both structural consistency for the sender and efficient information retrieval for receivers by providing navigation paths through the hierarchical layers.
Data Source
AI summary
A hierarchical decoder is operable to decode a hierarchical multi-layer data package. The hierarchical multi-layer data package includes a plurality of layers and one or more subpackages in each layer. To decode the data package, an objective function is created based on parameters for identifying data in the data package most relevant to information of interest. Subpackages in one or more layers are evaluated using the objective function and a subpackage is selected. Information for the selected subpackage, which may include a summary and metadata, is used to determine whether the subpackage satisfies an information need. If the information need is not satisfied, a drill down procedure is performed to evaluate subpackages in a next lower layer of the data package.