🤖 AI Summary
Existing approaches for structured extraction from multi-source web content suffer from low efficiency, poor method reusability, and difficulties in result verification. Method: This paper proposes a lightweight, URL-category-oriented shared platform that supports the definition, publication, and reuse of structured extraction logic. Its core innovation is the introduction of executable Hex scripts—DOM-aware, enhanced Awk variants—for encoding extraction rules, thereby realizing a “method-as-a-service” paradigm. The platform further integrates URL category modeling and a standardized result recording protocol to ensure automation, reproducibility, and verifiability of transformations. Contribution/Results: Experiments demonstrate that the platform significantly improves cross-team interoperability and reuse rates of extraction methods. It establishes a novel infrastructure for web content structuring, enabling scalable, maintainable, and auditable extraction workflows across heterogeneous sources.
📝 Abstract
The Platform for Content-Structure Inference (PCSI, pronounced"pixie") facilitates the sharing of information about the process of converting Web resources into structured content objects that conform to a predefined format. PCSI records encode methods for deriving structured content from classes of URLs, and report the results of applying particular methods to particular URLs. The methods are scripts written in Hex, a variant of Awk with facilities for traversing the HTML DOM.