  In the shipping industry, document classification plays a crucial role in
ensuring that the necessary documents are properly identified and processed for
customs clearance. OCR technology is being used to automate the process of
document classification, which involves identifying important documents such as
Commercial Invoices, Packing Lists, Export/Import Customs Declarations, Bills
of Lading, Sea Waybills, Certificates, Air or Rail Waybills, Arrival Notices,
Certificate of Origin, Importer Security Filings, and Letters of Credit. By
using OCR technology, the shipping industry can improve accuracy and efficiency
in document classification and streamline the customs clearance process. The
aim of this study is to build a robust document classification system based on
keyword frequencies. The research is carried out by analyzing Contract-Breach
law documents available with IN-D. The documents were collected by scraping the
Singapore Government Judiciary website. The database developed has 250
Contract-Breach documents. These documents are splitted to generate 200
training documents and 50 test documents. A semi-automatic approach is used to
select keyword vectors for document classification. The accuracy of the
reported model is 92.00 %.
