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Fuji Ren
Researcher at University of Tokushima
Publications - 622
Citations - 6519
Fuji Ren is an academic researcher from University of Tokushima. The author has contributed to research in topics: Sentence & Machine translation. The author has an hindex of 30, co-authored 579 publications receiving 4966 citations. Previous affiliations of Fuji Ren include Hiroshima City University & Beijing University of Posts and Telecommunications.
Papers
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Journal Article
Automatic Text Summarization
Mohamed Abdel Fattah,Fuji Ren +1 more
TL;DR: This work proposes a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentenceclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries.
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GA, MR, FFNN, PNN and GMM based models for automatic text summarization
Mohamed Abdel Fattah,Fuji Ren +1 more
TL;DR: This work proposes an approach to address the problem of improving content selection in automatic text summarization by using some statistical tools, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentenceclusion of name entity, sentence inclusion of numerical data, sentence relative length and aggregated similarity.
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The Evolution of Sink Mobility Management in Wireless Sensor Networks: A Survey
Yu Gu,Fuji Ren,Yusheng Ji,Jie Li +3 more
TL;DR: An up-to-date survey on the sink mobility issue is presented and several representative solutions are described following the proposed taxonomy, to help readers comprehend the development flow within a category.
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A blog emotion corpus for emotional expression analysis in Chinese
Changqin Quan,Fuji Ren +1 more
TL;DR: This work uses blogs as object and data source for Chinese emotional expression analysis, and based on this model, a relatively fine-grained annotation scheme is proposed for manual annotation of an emotion corpus.
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Class-indexing-based term weighting for automatic text classification
Fuji Ren,Mohammad Golam Sohrab +1 more
TL;DR: The experimental results show that the proposed class-indexing-based TF.IDF.ICS"@dFterm weighting approach is promising over the compared well-known baseline term weighting approaches.