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        <title>Fine-grained Coordinated Cross-lingual Text Stream Alignment for Endless Language Knowledge Acquisition</title>
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        <namePart type="given">Baobao</namePart>
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        <dateIssued>2018-oct&quot;-&quot;nov</dateIssued>
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    <abstract>This paper proposes to study fine-grained coordinated cross-lingual text stream alignment through a novel information network decipherment paradigm. We use Burst Information Networks as media to represent text streams and present a simple yet effective network decipherment algorithm with diverse clues to decipher the networks for accurate text stream alignment. Experiments on Chinese-English news streams show our approach not only outperforms previous approaches on bilingual lexicon extraction from coordinated text streams but also can harvest high-quality alignments from large amounts of streaming data for endless language knowledge mining, which makes it promising to be a new paradigm for automatic language knowledge acquisition.</abstract>
    <identifier type="citekey">ge-etal-2018-fine</identifier>
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%0 Conference Proceedings
%T Fine-grained Coordinated Cross-lingual Text Stream Alignment for Endless Language Knowledge Acquisition
%A Ge, Tao
%A Dou, Qing
%A Ji, Heng
%A Cui, Lei
%A Chang, Baobao
%A Sui, Zhifang
%A Wei, Furu
%A Zhou, Ming
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct" "nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F ge-etal-2018-fine
%X This paper proposes to study fine-grained coordinated cross-lingual text stream alignment through a novel information network decipherment paradigm. We use Burst Information Networks as media to represent text streams and present a simple yet effective network decipherment algorithm with diverse clues to decipher the networks for accurate text stream alignment. Experiments on Chinese-English news streams show our approach not only outperforms previous approaches on bilingual lexicon extraction from coordinated text streams but also can harvest high-quality alignments from large amounts of streaming data for endless language knowledge mining, which makes it promising to be a new paradigm for automatic language knowledge acquisition.
%R 10.18653/v1/D18-1271
%U https://aclanthology.org/D18-1271
%U https://doi.org/10.18653/v1/D18-1271
%P 2496-2506

Markdown (Informal)

[Fine-grained Coordinated Cross-lingual Text Stream Alignment for Endless Language Knowledge Acquisition](https://aclanthology.org/D18-1271) (Ge et al., EMNLP 2018)

• Fine-grained Coordinated Cross-lingual Text Stream Alignment for Endless Language Knowledge Acquisition (Ge et al., EMNLP 2018)

ACL

• Tao Ge, Qing Dou, Heng Ji, Lei Cui, Baobao Chang, Zhifang Sui, Furu Wei, and Ming Zhou. 2018. Fine-grained Coordinated Cross-lingual Text Stream Alignment for Endless Language Knowledge Acquisition. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2496–2506, Brussels, Belgium. Association for Computational Linguistics.