This research proposes and implements an Arabic Sub-Words Recognition System （ASWR）. The system focuses on employing a combination of statistical and structural features to provide complete pattern＇s description an...This research proposes and implements an Arabic Sub-Words Recognition System （ASWR）. The system focuses on employing a combination of statistical and structural features to provide complete pattern＇s description and enhances the recognition rate. Support Vector Machines （SVMs） is utilized as a promising pattern recognition tool. In addition to that, the problems of dots and holes are solved in a completely different way from the ones previously employed. The proposed system proceeds in several phases as follows： （1） image acquisition, （2） binarisation, （3） morphological processing, （4） feature extraction, which includes statistical features, i.e., moment invariants, and structural features, i.e., dot number, dot position, and number of holes, features, and （5） classification, using multi-class SVMs and applying a one-against-all technique. The proposed system has been tested using different sets of words and subwords and has achieved a nearly 98.90% recogiaition rate. Comparative results with NNs are also presented.展开更多
This paper presents a project aimed at developing a trilingual visual dictionary for aircraft maintenance professionals and students.The project addresses the growing demand for accurate communication and technical te...This paper presents a project aimed at developing a trilingual visual dictionary for aircraft maintenance professionals and students.The project addresses the growing demand for accurate communication and technical terminology in the aviation industry,particularly in Brazil and China.The study employs a corpus-driven approach,analyzing a large corpus of aircraft maintenance manuals to extract key technical terms and their collocates.Using specialized subcorpora and a comparative analysis,this paper demonstrates challenges and solutions into the identification of high-frequency keywords and explores their contextual use in aviation documentation,emphasizing the need for clear and accurate technical communication.By incorporating these findings into a trilingual visual dictionary,the project aims to enhance the understanding and usage of aviation terminology.展开更多
Semantic lexical chains have been regarded as important in textural cohesion, although traditionally, the classification of these chains has been limited to repetition, synonymy, hyponymy, and collocates. The cases of...Semantic lexical chains have been regarded as important in textural cohesion, although traditionally, the classification of these chains has been limited to repetition, synonymy, hyponymy, and collocates. The cases of automatic extraction of lexical chains have found that the contextual synonyms can not be recognized, nor extracted automatically. This study took the data-based technology to extract the contextually co-occurring lexical chains through thematic lexical items. It found that these contextually co-occurring lexical chains can include the semantic lexical chains and contextual synonyms. It also found that, in extraction of collocates of the co-occurring lexical items, these collocates form secondary lexical chains, which contribute to textual cohesion. The vertical lexical chains made of contextually cooccurring lexical items and the horizontal chains made of collocational lexical items work together in making the text into a coherent whole.展开更多
文摘This research proposes and implements an Arabic Sub-Words Recognition System （ASWR）. The system focuses on employing a combination of statistical and structural features to provide complete pattern＇s description and enhances the recognition rate. Support Vector Machines （SVMs） is utilized as a promising pattern recognition tool. In addition to that, the problems of dots and holes are solved in a completely different way from the ones previously employed. The proposed system proceeds in several phases as follows： （1） image acquisition, （2） binarisation, （3） morphological processing, （4） feature extraction, which includes statistical features, i.e., moment invariants, and structural features, i.e., dot number, dot position, and number of holes, features, and （5） classification, using multi-class SVMs and applying a one-against-all technique. The proposed system has been tested using different sets of words and subwords and has achieved a nearly 98.90% recogiaition rate. Comparative results with NNs are also presented.
文摘This paper presents a project aimed at developing a trilingual visual dictionary for aircraft maintenance professionals and students.The project addresses the growing demand for accurate communication and technical terminology in the aviation industry,particularly in Brazil and China.The study employs a corpus-driven approach,analyzing a large corpus of aircraft maintenance manuals to extract key technical terms and their collocates.Using specialized subcorpora and a comparative analysis,this paper demonstrates challenges and solutions into the identification of high-frequency keywords and explores their contextual use in aviation documentation,emphasizing the need for clear and accurate technical communication.By incorporating these findings into a trilingual visual dictionary,the project aims to enhance the understanding and usage of aviation terminology.
文摘Semantic lexical chains have been regarded as important in textural cohesion, although traditionally, the classification of these chains has been limited to repetition, synonymy, hyponymy, and collocates. The cases of automatic extraction of lexical chains have found that the contextual synonyms can not be recognized, nor extracted automatically. This study took the data-based technology to extract the contextually co-occurring lexical chains through thematic lexical items. It found that these contextually co-occurring lexical chains can include the semantic lexical chains and contextual synonyms. It also found that, in extraction of collocates of the co-occurring lexical items, these collocates form secondary lexical chains, which contribute to textual cohesion. The vertical lexical chains made of contextually cooccurring lexical items and the horizontal chains made of collocational lexical items work together in making the text into a coherent whole.
