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Электронный каталог: Slavin, O.A. - Optimizing the performance of a server-based classification for a large business document flow
Slavin, O.A. - Optimizing the performance of a server-based classification for a large business document flow
Статья
Автор: Slavin, O.A.
Системный анализ и прикладная информатика: Optimizing the performance of a server-based classification for a large business document flow
P. 60-64. г.
ISBN отсутствует
Автор: Slavin, O.A.
Системный анализ и прикладная информатика: Optimizing the performance of a server-based classification for a large business document flow
P. 60-64. г.
ISBN отсутствует
На полку
Статья
Slavin, O.A.
Optimizing the performance of a server-based classification for a large business document flow / O. A. Slavin. – P. 60-64. – DOI 10.21122/2309-4923-2022-4-60-64 // Системный анализ и прикладная информатика. – 2022. – № 4. – Режим доступа : https://rep.bntu.by/handle/data/126534. - Пер. загл.: [Оптимизация производительности серверной классификации для большого потока бизнес-документов]. – На англ. яз.
The document categorization problem in the case of a large business document flow is considered. Textual and visual embeddings were employed for classification. Textual embeddings were extracted via OCR Tesseract. The Viola and Jones method was applied to generate visual embeddings. This paper describes the performance optimization technology for the implemented classification algorithm. Servers with Intel CPUs were used for the algorithm execution. For single-threaded implementation, high-level and low-level optimizations were performed. High-level optimization was based on the parametrization of the recognition algorithms and the employment of intermediate data. Low-level optimization was carried out via compiler tools allowing for an extended set of SIMD instructions. The implementation of parallelization with several multithreaded applications on multiple servers was also described. The proposed solution was tested using own test data sets of business documents. The proposed method can be applied in modern information systems to analyze the content of a large flow of digital document images.
004.93
общий = БД Техника
общий = МНОГОКРИТЕРИАЛЬНАЯ ОПТИМИЗАЦИЯ
общий = КАТЕГОРИЗАЦИЯ
общий = ДОКУМЕНТООБОРОТ
общий = ПАРАМЕТРИЗАЦИИ МЕТОД
Slavin, O.A.
Optimizing the performance of a server-based classification for a large business document flow / O. A. Slavin. – P. 60-64. – DOI 10.21122/2309-4923-2022-4-60-64 // Системный анализ и прикладная информатика. – 2022. – № 4. – Режим доступа : https://rep.bntu.by/handle/data/126534. - Пер. загл.: [Оптимизация производительности серверной классификации для большого потока бизнес-документов]. – На англ. яз.
The document categorization problem in the case of a large business document flow is considered. Textual and visual embeddings were employed for classification. Textual embeddings were extracted via OCR Tesseract. The Viola and Jones method was applied to generate visual embeddings. This paper describes the performance optimization technology for the implemented classification algorithm. Servers with Intel CPUs were used for the algorithm execution. For single-threaded implementation, high-level and low-level optimizations were performed. High-level optimization was based on the parametrization of the recognition algorithms and the employment of intermediate data. Low-level optimization was carried out via compiler tools allowing for an extended set of SIMD instructions. The implementation of parallelization with several multithreaded applications on multiple servers was also described. The proposed solution was tested using own test data sets of business documents. The proposed method can be applied in modern information systems to analyze the content of a large flow of digital document images.
004.93
общий = БД Техника
общий = МНОГОКРИТЕРИАЛЬНАЯ ОПТИМИЗАЦИЯ
общий = КАТЕГОРИЗАЦИЯ
общий = ДОКУМЕНТООБОРОТ
общий = ПАРАМЕТРИЗАЦИИ МЕТОД
