← 研踪 PaperTrailACL Anthology · ACL 2026:acl:2026.acl-demo.23 · 记录 #1
GovScape: A Public Multimodal Search System for 70 Million Pages of Government PDFs
来源日期（仅到月份） 2026-07
来源记录日期 2026-07
雷达观测 2026-11-01 22:08
摘要
Efforts over the past three decades have produced web archives containing billions of webpage snapshots and petabytes of data. The End of Term Web Archive alone contains millions of PDFs produced by the federal government. While preservation with web archives has been successful, significant challenges for access and discoverability remain. In this paper, we introduce GovScape, a public search system that supports multimodal searches across 10,015,993 federal government PDFs from the 2020 End of Term crawl (70,958,487 total PDF pages) – to our knowledge, all renderable PDFs in the 2020 crawl that are 50 pages or under. GovScape supports four primary forms of search: in addition to providing (1) filter conditions over metadata facets including domain and crawl date and (2) exact text search against the PDF text, we provide (3) semantic text search and (4) visual search against the PDFs across individual pages, enabling users to structure queries such as “redacted documents” or “pie charts.” We detail GovScape’s search affordances, embedding pipeline, system architecture, and open source codebase. Significantly, the total estimated compute cost for GovScape’s pre-processing pipeline for 10 million PDFs was approximately 1,500, equivalent to 47,000 PDF pages per dollar spent on compute, demonstrating the potential for immediate scalability. We evaluate GovScape by (1) analyzing 1,679 search queries and (2) benchmarking vector and keyword index efficiency using these queries. GovScape can be found at https://www.govscape.net.
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观测到的版本
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记录 #1 · 2026-07 · 最新观测版本
GovScape: A Public Multimodal Search System for 70 Million Pages of Government PDFs
Efforts over the past three decades have produced web archives containing billions of webpage snapshots and petabytes of data. The End of Term Web Archive alone contains millions of PDFs produced by the federal government. While preservation with web archives has been successful, significant challenges for access and discoverability remain. In this paper, we introduce GovScape, a public search system that supports multimodal searches across 10,015,993 federal government PDFs from the 2020 End of Term crawl (70,958,487 total PDF pages) – to our knowledge, all renderable PDFs in the 2020 crawl that are 50 pages or under. GovScape supports four primary forms of search: in addition to providing (1) filter conditions over metadata facets including domain and crawl date and (2) exact text search against the PDF text, we provide (3) semantic text search and (4) visual search against the PDFs across individual pages, enabling users to structure queries such as “redacted documents” or “pie charts.” We detail GovScape’s search affordances, embedding pipeline, system architecture, and open source codebase. Significantly, the total estimated compute cost for GovScape’s pre-processing pipeline for 10 million PDFs was approximately 1,500, equivalent to 47,000 PDF pages per dollar spent on compute, demonstrating the potential for immediate scalability. We evaluate GovScape by (1) analyzing 1,679 search queries and (2) benchmarking vector and keyword index efficiency using these queries. GovScape can be found at https://www.govscape.net.
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