Technical assessment of metadata and OCR quality in Google Books corpus
Technical assessment of metadata and OCR quality in Google Books corpus The document details internal quality metrics and filtering thresholds for Google Books metadata and OCR. It contains no references to influential actors, financial flows, or misconduct, offering no actionable investigative leads. Key insights: Metadata date errors reduced from 27% to 6.2% after filtering.; OCR quality scores assigned per volume (0‑100) using a PPM‑based model.; Different OCR quality thresholds applied by language (e.g., 80% for Latin alphabets).
Summary
Technical assessment of metadata and OCR quality in Google Books corpus The document details internal quality metrics and filtering thresholds for Google Books metadata and OCR. It contains no references to influential actors, financial flows, or misconduct, offering no actionable investigative leads. Key insights: Metadata date errors reduced from 27% to 6.2% after filtering.; OCR quality scores assigned per volume (0‑100) using a PPM‑based model.; Different OCR quality thresholds applied by language (e.g., 80% for Latin alphabets).
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