Technologies and the development of the Automated Metadata Indexing and Analysis (AMIA) system
| Autor: | Pei-Ying Chiang, Jeff Lund, May-chen Kuo, C.-C. Jay Kuo, Todd Richmond, Jessy Lee, Milton Rosenberg, Lindsay Armstrong, Kip Haynes |
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| Rok vydání: | 2010 |
| Předmět: |
Information retrieval
Computer science Search engine indexing Text segmentation Digital asset management Metadata World Wide Web Signal Processing Digital asset Media Technology Computer Vision and Pattern Recognition Electrical and Electronic Engineering Content based retrieval Dependency (project management) |
| Zdroj: | Journal of Visual Communication and Image Representation. 21:200-209 |
| ISSN: | 1047-3203 |
| DOI: | 10.1016/j.jvcir.2009.12.001 |
| Popis: | The Automated Metadata Indexing and Analysis (AMIA) project aims to provide an effective digital asset management (DAM) tool for large digital asset databases. We began with text-based indexing since it is still the most reliable approach as compared with other content-based media features. AMIA not only searches for the text of the file name, but also utilizes embedded information such as the metadata in Maya files. The AMIA system builds a linked map between all dependency files. We present an approach of preserving previously established metadata created by the old DAM tools, such as AlienBrain, and integrating them into the new system. Findings indicate that AMIA has significantly improved search performance comparing to previous DAM tools. Finally, the ongoing and future work in the AMIA project is described. |
| Databáze: | OpenAIRE |
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