Papers are solicited in, but not limited to, the following areas.

Document Recognition

  1. Text recognition: machine-printed, handwritten documents; paper, tablet, camera, and video sources
  2. Writer/style identification, verification, and adaptation
  3. Graphics recognition: vectorization (e.g. for line-art, maps and technical drawings), signature, logo and graphical symbol recognition, figure, chart and graph recognition, and diagrammatic notations (e.g. music, mathematical notation)
  4. Document layout analysis and understanding: document and page region segmentation, form and table recognition, and document understanding through combined modalities (e.g. speech and images)
  5. Evaluation: performance metrics, and document degradation models
  6. Additional topics: document image filtering, enhancement and compression, document clustering and classification, machine learning (e.g. integration and optimization of recognition modules), historical and degraded document images (e.g. fax), multilingual document recognition, and web page analysis (including wikis and blogs)

Document Retrieval

  1. Indexing and Summarization: text documents (messages, blogs, etc.), imaged documents, entity tagging from OCR output, and text categorization
  2. Query languages and modalities: Content-Based Image Retrieval (CBIR) for documents, keyword spotting, non-textual query-by-example (e.g. tables, figures, math), querying by document geometry and/or logical structure, approximate string matching algorithms for OCR output, retrieval of noisy text documents (messages, blogs, etc.), cross and multi-lingual retrieval
  3. Discovery and Browsing: Pattern discovery, trend mining, topic modeling and analysis, clustering
  4. Evaluation: relevance and performance metrics, evaluation protocols, and benchmarking
  5. Additional topics: relevance feedback, impact of recognition accuracy on retrieval performance, and digital libraries including systems engineering and quality assurance