Cross - Language based Multi-Document Summarization Model using Machine Learning Technique
نویسندگان
چکیده
منابع مشابه
Multi-Document Summarization Using Cross-Language Texts
Without a summarization system in source language, we try to generate a summary in source language, using translated documents by a machine translator and a summarization system in target language. For summarizing multiple documents translated by a machine translator, we extract important sentences, and remove redundant sentences using an improved term-weighting method. It assigns weights to wo...
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Cross-language document summarization is a task of producing a summary in one language for a document set in a different language. Existing methods simply use machine translation for document translation or summary translation. However, current machine translation services are far from satisfactory, which results in that the quality of the cross-language summary is usually very poor, both in re...
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Cross-language summarization is the task of generating a summary in a language different from the language of the source documents. In this paper, we propose a graph-based approach to multi-document summarization that integrates machine translation quality scores in the sentence extraction process. We evaluate our method on a manually translated subset of the DUC 2004 evaluation campaign. Resul...
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Text Summarization is compressing the source text into a shorter version preserving its information content and overall meaning. It is very complicated for human beings to manually summarize large documents of text. Text summarization plays an important role in the area of natural language processing and text mining. Many approaches use statistics and machine learning techniques to extract sent...
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ژورنال
عنوان ژورنال: Turkish Journal of Computer and Mathematics Education (TURCOMAT)
سال: 2021
ISSN: 1309-4653
DOI: 10.17762/turcomat.v12i6.1393