Multi-Document Summarization Using Cross-Language Texts
By Jung-Min Lim, In-Su Kang, Jong-Hyeok Lee. 2004
12 citations recorded by the source corpus.
Subfields: Natural Language Processing, Evaluation & Benchmarks
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Citations in the corpus
- WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization (2020, methodology): “Although translate-then-summarize (Leuski et al., 2003) and summarize-then-translate (Lim et al., 2004; Or˘asan and Chiorean, 2008; Wan et al., 2010) are widely used approaches in prior studies, they are prone to error propagation.”
- NCLS: Neural Cross-Lingual Summarization (2019, background): “…which either first translates the original document into target language and then summarizes the translated document (Leuski et al., 2003) or first summarizes the original document and then translates the summary into target language (Lim et al., 2004; Orasan and Chiorean, 2008; Wan et al., 2010).”
- Cross-Language Document Summarization Based on Machine Translation Quality Prediction (2010, methodology): “Lim et al. (2004) propose to generate a Japanese summary without using a Japanese summarization system, by first translating Japanese documents into Korean documents, and then extracting summary sentences by using Korean summarizer, and finally mapping Korean summary sentences to Japanese summary…”