Abstract: A computer-implemented method for increasing a recognition rate of an optical character recognition (OCR) system is provided. The method includes preprocessing by receiving an image, and extracting all vertical lines from the image. The method includes adding vertical lines at character areas of the image, extracting all horizontal lines from the image, and creating an unlined image removing all the vertical/horizontal lines from the image. The method further includes determining a border of a vertical direction of the unlined image based on the total of pixels of rows in each column, and adding vertical/horizontal auxiliary lines between characters of the unlined image. The method also includes postprocessing by receiving garbled words of OCR output, removing noise after morphologically analyzing, replacing garbled letters with correct ones based on a frequent edit operation, and outputting the correct word, weighting results of image distance calculations based on machine learning.

Abstract: A computer-implemented method for increasing a recognition rate of an optical character recognition (OCR) system is provided. The method includes preprocessing by receiving an image, and extracting all vertical lines from the image. The method includes adding vertical lines at character areas of the image, extracting all horizontal lines from the image, and creating an unlined image removing all the vertical/horizontal lines from the image. The method further includes determining a border of a vertical direction of the unlined image based on the total of pixels of rows in each column, and adding vertical/horizontal auxiliary lines between characters of the unlined image. The method also includes postprocessing by receiving garbled words of OCR output, removing noise after morphologically analyzing, replacing garbled letters with correct ones based on a frequent edit operation, and outputting the correct word, weighting results of image distance calculations based on machine learning.

Abstract: To dynamically classify and sort search results according to a natural language query and output the results conveniently, the invention includes an input unit for accepting entry of a natural language query, a natural language processing unit for performing natural language analysis of the query, a search unit for retrieving information using at least one keyword obtained through the natural language analysis, a search result processing unit for analyzing the keyword obtained through the natural language analysis of the query and its modifier, based on semantic content defined in an ontology, and processing the search results of the information retrieval by the search unit, such as sorting and classifying the results, and an output unit.