Converting articles to JSON involves analyzing and structuring web content using advanced natural
language processing and content extraction techniques. The system processes various article formats and
sources to create standardized, machine-readable data structures.
Content Extraction
The system employs DOM analysis and content classification to identify main article content,
distinguishing it from navigation elements, advertisements, and other non-article components. Advanced
heuristics ensure accurate extraction of article text, images, and embedded media.
Metadata Processing
Article metadata including titles, authors, publication dates, and categories are extracted using
specialized entity recognition models. The system handles various metadata formats and schemas,
normalizing them into consistent JSON structures. This includes processing Open Graph tags, schema.org
markup, and RSS feed metadata.
Content Structure Analysis
The converter analyzes article structure, identifying sections, headings, paragraphs, and lists. This
hierarchical information is preserved in the JSON output, maintaining the logical organization of the
content. Special handling is provided for quotes, citations, and embedded content.
Multi-format Support
The system processes articles from various sources including HTML pages, RSS feeds, and content
management systems. Format-specific extractors handle different content structures while maintaining
consistent output schemas. This includes support for paywalled content and dynamic loading patterns.
Schema Validation
Extracted content undergoes schema validation to ensure compliance with specified JSON formats. The
system supports custom schema definitions, allowing flexible output structures while maintaining data
integrity. Validation includes type checking, required field verification, and format consistency.
Content Cleaning
Extracted content is cleaned and normalized, removing HTML artifacts, standardizing whitespace, and
handling special characters. The system preserves important formatting while ensuring clean, consistent
JSON output. This includes proper escaping of special characters and handling of Unicode content.
Error Handling
The system implements robust error handling for various content issues including malformed HTML, missing
metadata, and incomplete content. Extraction failures are gracefully handled with appropriate error
reporting and fallback mechanisms to ensure reliable processing.
Article to JSON conversion provides structured data essential for content analysis, aggregation, and
integration. The combination of advanced extraction techniques, flexible schema support, and robust
processing ensures reliable conversion of web content into machine-readable formats.