JSON Statistical Tree Encoding for Repeated Key Compression
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Solution Overview
Problem
JSON documents are large due to text-based encoding and repeated key names, and existing compression methods do not effectively utilize the inherent structure of JSON data, leading to suboptimal compression.
Innovation Solution
A method using a statistical tree representing a JSON Schema to encode and decode JSON documents, optimizing the tree to reduce the number of bits required for encoding and decoding, thereby compressing the data efficiently by leveraging the structure of the JSON document.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If JSON data is encoded using text-based format with repeated key names, then the data is human-readable and language-independent, but the document size becomes large
Solution Approach 1:
The JSON document is segmented into structural components (keys, values, paths) that can be independently encoded. The statistical tree segments the document hierarchy into nodes and edges, allowing selective compression of repeated elements while preserving readability through controlled decoding
Solution Approach 2:
Instead of repeatedly copying full key names in text format, the patent creates a statistical tree model that copies the structural pattern once and references it throughout the document. The tree nodes represent repeated key-value patterns, eliminating redundancy while maintaining the ability to reconstruct the original readable format
2Quantity of substance
If existing compression methods are used on JSON data, then some size reduction is achieved, but the inherent structure of JSON is not effectively utilized
Solution Approach 1:
The patent changes the encoding parameter from text-based representation to a statistical tree-based binary representation. By transforming the data into a different parameter space (tree structures with statistical properties), the compression achieves superior ratios by exploiting the hierarchical and repetitive nature of JSON structures that text-based methods cannot capture
Solution Approach 2:
The statistical tree acts as an intermediary between the original JSON data and the compressed representation. Instead of directly compressing text, the patent introduces the tree structure as a intermediate model that captures statistical patterns, enabling more effective compression while preserving the ability to reconstruct the original data
3Reliability
If JSON Schema is used to define data structure, then validation and documentation are improved, but the encoding complexity increases
Solution Approach 1:
The JSON Schema is applied in advance to build the statistical tree structure before compression occurs. By performing the schema-based structural analysis preliminarily, the patent creates an optimized tree model that captures all validation rules and patterns upfront, simplifying the subsequent compression process rather than adding complexity during encoding
Solution Approach 2:
The statistical tree serves multiple functions simultaneously: it validates data against the schema, compresses the representation, and enables efficient querying. By creating a structure that fulfills multiple roles (validation, compression, analysis), the patent reduces overall system complexity despite the presence of schema requirements
Data Source
AI summary
A method for encoding and decoding a javascript object notation (JSON) document utilizing a statistical tree representing a JSON Schema. The encoded statistical tree may be optimized.