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Research on Cross-Language Retrieval Using Bilingual Word Vectors in Different Languages

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Data Science (ICPCSEE 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1058))

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Abstract

Bilingual word vectors have been exploited a lot in cross-language information retrieval research. However, most of the research is currently focused on similar language pairs. There are very few studies exploring the impact of using bilingual word vectors for cross-language information retrieval in long-distance language pairs. In this paper, it systematically analyzes the retrieval performance of various European languages (English, German, Italian, French, Finnish, Dutch) as well as Asian languages (Chinese, Japanese) in the adhoc task of CLEF 2002–2003 campaign. Genetic proximity was used to visually represent the relationships between languages and compare their cross-lingual retrieval performance in various settings. The results show that the differences in language vocabulary would dramatically affect the retrieval performance. At the same time, the term by term translation retrieval method performs slightly better than the simple vector addition retrieval methods. It proves that the translation-based retrieval model can still maintain its advantage under the new semantic scheme.

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Notes

  1. 1.

    http://www.wikipedia.org.

  2. 2.

    http://www.clef-initiative.eu/.

  3. 3.

    https://www.elinguistics.net/.

  4. 4.

    https://translate.google.com/.

  5. 5.

    https://github.com/taku910/mecab.

  6. 6.

    https://github.com/fxsjy/jieba.

  7. 7.

    https://fasttext.cc.

  8. 8.

    https://github.com/rlitschk/UnsupCLIR.

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Acknowledgement

The work described in this paper was supported by National Natural Science Foundation of China under Project No. 61876062, Scientific Research Fund of Hunan Provincial Education Department of China under Project No. 16K030, Hunan Provincial Natural Science Foundation of China under Project No. 2017JJ2101, Hunan Provincial Innovation Foundation for Postgraduate under Project No. CX2018B671.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China

    Yulong Li & Dong Zhou

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  1. Yulong Li
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  2. Dong Zhou
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Correspondence to Dong Zhou .

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Editors and Affiliations

  1. Guilin University of Technology, Guilin, China

    Xiaohui Cheng

  2. Northeast Forestry University, Harbin, China

    Weipeng Jing

  3. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

  4. National Academy of Guo Ding Institute of Data Science, Harbin, China

    Zeguang Lu

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Li, Y., Zhou, D. (2019). Research on Cross-Language Retrieval Using Bilingual Word Vectors in Different Languages. In: Cheng, X., Jing, W., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2019. Communications in Computer and Information Science, vol 1058. Springer, Singapore. https://doi.org/10.1007/978-981-15-0118-0_35

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  • DOI: https://doi.org/10.1007/978-981-15-0118-0_35

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  • Online ISBN: 978-981-15-0118-0

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