Abstract
This paper provides a new model enhancing the Arabic OCR degraded text retrieval effectiveness. The proposed model based on simulating the Arabic OCR recognition mistakes on a word based approach. Then the model expands the user search query using the expected OCR errors. The resulting expanded search query gives higher precision and recall in searching Arabic OCR-Degraded text rather than the original query. The proposed new model showed a significant increase in the degraded text retrieval effectiveness over the previous models. The retrieval effectiveness of the new model is %97, while the best effectiveness published for word based approach was %84 and the best effectiveness for character based approach was %56. In addition, the new model overcomes several limitations of the current two existing models.
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Ezzat, M., ElGhazaly, T., Gheith, M. (2013). An Enhanced Arabic OCR Degraded Text Retrieval Model. In: Castro, F., Gelbukh, A., González, M. (eds) Advances in Artificial Intelligence and Its Applications. MICAI 2013. Lecture Notes in Computer Science(), vol 8265. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45114-0_31
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DOI: https://doi.org/10.1007/978-3-642-45114-0_31
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