TY - GEN
T1 - A post-processing approach to Chinese address recognition
AU - Yao, Xinyu
AU - Lu, Yue
PY - 2011
Y1 - 2011
N2 - In recent years, it has become a focus to make use of the address recognition technology to improve the performance of mail sorting machines. The research in the postal address recognition, which extends the context relation from words to sentences with the use of the address information in post-processing, can effectively improve the recognition performance. In this paper, we propose a divide-and-rule method. The address is divided into high level address and low level address. For high level address, the similarity method with HLA database is presented. For low level address, the Syllable-based language model which applies to Pinyin is discussed. Then a new similarity method in multi-mode is introduced. After post-processing, for high level address, the hit rate rises from 87.63% to 95.12% while the accuracy rate declines by 2.67%, and for low level address, the hit rate increases from 58.16% to 91.81% while the accuracy rate decreases by 9.40%.
AB - In recent years, it has become a focus to make use of the address recognition technology to improve the performance of mail sorting machines. The research in the postal address recognition, which extends the context relation from words to sentences with the use of the address information in post-processing, can effectively improve the recognition performance. In this paper, we propose a divide-and-rule method. The address is divided into high level address and low level address. For high level address, the similarity method with HLA database is presented. For low level address, the Syllable-based language model which applies to Pinyin is discussed. Then a new similarity method in multi-mode is introduced. After post-processing, for high level address, the hit rate rises from 87.63% to 95.12% while the accuracy rate declines by 2.67%, and for low level address, the hit rate increases from 58.16% to 91.81% while the accuracy rate decreases by 9.40%.
KW - OCR
KW - fuzzy match
KW - post-processing
KW - similarity
UR - https://www.scopus.com/pages/publications/80053413091
U2 - 10.1109/FSKD.2011.6019901
DO - 10.1109/FSKD.2011.6019901
M3 - 会议稿件
AN - SCOPUS:80053413091
SN - 9781612841816
T3 - Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011
SP - 1906
EP - 1910
BT - Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011
T2 - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11
Y2 - 26 July 2011 through 28 July 2011
ER -