TY - GEN
T1 - A comparison of whitespace normalization methods in a text art extraction method with run length encoding
AU - Suzuki, Tetsuya
PY - 2011/10/19
Y1 - 2011/10/19
N2 - Text based pictures called text art or ASCII art can be noise in text processing and display of text, though they enrich expression in Web pages, email text and so on. With text art extraction methods, which detect text art areas in a given text data, we can ignore text arts in a given text data or replace them with other strings. We proposed a text art extraction method with Run Length Encoding in our previous work. We, however, have not considered how to deal with whitespaces in text arts. In this paper, we propose three whitespace normalization methods in our text art extraction method, and compare them by an experiment. According to the results of the experiment, the best method in the three is a method which replaces each wide width whitespace with two narrow width whitespaces. It improves the average of F-measure of the precision and the recall by about 4%.
AB - Text based pictures called text art or ASCII art can be noise in text processing and display of text, though they enrich expression in Web pages, email text and so on. With text art extraction methods, which detect text art areas in a given text data, we can ignore text arts in a given text data or replace them with other strings. We proposed a text art extraction method with Run Length Encoding in our previous work. We, however, have not considered how to deal with whitespaces in text arts. In this paper, we propose three whitespace normalization methods in our text art extraction method, and compare them by an experiment. According to the results of the experiment, the best method in the three is a method which replaces each wide width whitespace with two narrow width whitespaces. It improves the average of F-measure of the precision and the recall by about 4%.
KW - Information Extraction
KW - Natural Language Processing
KW - Pattern Recognition
UR - http://www.scopus.com/inward/record.url?scp=80054079604&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-23896-3_16
DO - 10.1007/978-3-642-23896-3_16
M3 - Conference contribution
AN - SCOPUS:80054079604
SN - 9783642238956
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 135
EP - 142
BT - Artificial Intelligence and Computational Intelligence - Third International Conference, AICI 2011, Proceedings
T2 - 3rd International Conference on Artificial Intelligence and Computational Intelligence, AICI 2011
Y2 - 24 September 2011 through 25 September 2011
ER -