Many algorithms have been implemented for the problem of document categorization. The majority work in this area was achieved for English text, while a very few approaches have been introduced for the Arabic text. The...Many algorithms have been implemented for the problem of document categorization. The majority work in this area was achieved for English text, while a very few approaches have been introduced for the Arabic text. The nature of Arabic text is different from that of the English text and the preprocessing of the Arabic text is more challenging. This is due to Arabic language is a highly inflectional and derivational language that makes document mining a hard and complex task. In this paper, we present an Automatic Arabic documents classification system based on kNN algorithm. Also, we develop an approach to solve keywords extraction and reduction problems by using Document Frequency (DF) threshold method. The results indicate that the ability of the kNN to deal with Arabic text outperforms the other existing systems. The proposed system reached 0.95 micro-recall scores with 850 Arabic texts in 6 different categories.展开更多
Although the corporate relationship manager seems to be the key enabler in commercial banking,the personal relationship sales model is not a sustainable model for the paradigm shift in digital financial markets.In thi...Although the corporate relationship manager seems to be the key enabler in commercial banking,the personal relationship sales model is not a sustainable model for the paradigm shift in digital financial markets.In this research,we propose a knowledge-driven decision analytics approach to improve the decision process.However,most of the corporate client documents processed in banks are not well-structured and the traditional analysis approach does not consider the document structure,which carries rich semantic information.We propose a document structure-based text representation approach with incorporating auxiliary information in the predictive analytics of unstructured data to improve the performance in the document classification task.The proposed approach significantly outperforms the traditional whole document approach which does not take into considerations of the document structure.With the proposed approach,knowledge can be effectively and efficiently used for business decisions and planning to improve the competitive advantage and substantiality of banks.展开更多
文摘Many algorithms have been implemented for the problem of document categorization. The majority work in this area was achieved for English text, while a very few approaches have been introduced for the Arabic text. The nature of Arabic text is different from that of the English text and the preprocessing of the Arabic text is more challenging. This is due to Arabic language is a highly inflectional and derivational language that makes document mining a hard and complex task. In this paper, we present an Automatic Arabic documents classification system based on kNN algorithm. Also, we develop an approach to solve keywords extraction and reduction problems by using Document Frequency (DF) threshold method. The results indicate that the ability of the kNN to deal with Arabic text outperforms the other existing systems. The proposed system reached 0.95 micro-recall scores with 850 Arabic texts in 6 different categories.
文摘Although the corporate relationship manager seems to be the key enabler in commercial banking,the personal relationship sales model is not a sustainable model for the paradigm shift in digital financial markets.In this research,we propose a knowledge-driven decision analytics approach to improve the decision process.However,most of the corporate client documents processed in banks are not well-structured and the traditional analysis approach does not consider the document structure,which carries rich semantic information.We propose a document structure-based text representation approach with incorporating auxiliary information in the predictive analytics of unstructured data to improve the performance in the document classification task.The proposed approach significantly outperforms the traditional whole document approach which does not take into considerations of the document structure.With the proposed approach,knowledge can be effectively and efficiently used for business decisions and planning to improve the competitive advantage and substantiality of banks.
