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首页> 外文会议>20th European conference on artificial intelligence >Using Learning to Rank Approach for Parallel Corpora Based Cross Language Information Retrieval
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Using Learning to Rank Approach for Parallel Corpora Based Cross Language Information Retrieval

机译：基于学习语料库的并行语料库跨语言信息检索方法

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摘要

Learning to Rank (LTR) refers to machine learning techniques for training a model in a ranking task. LTR has been shown to be useful in many applications in information retrieval (IR). Cross language information retrieval (CLIR) is one of the major IR tasks that can potentially benefit from LTR to improve the ranking accuracy. CLIR deals with the problem of expressing query in one language and retrieving the related documents in another language. One of the most important issues in CLIR is how to apply monolingual IR methods in cross lingual environments. In this paper, we propose a new method to exploit LTR for CLIR in which documents are represented as feature vectors. This method provides a mapping based on IR heuristics to employ monolingual IR features in parallel corpus based CLIR. These mapped features are considered as training data for LTR. We show that using LTR trained on mapped features can improve CLIR performance. A comprehensive evaluation on the English-Persian CLIR suggests that our method has significant improvements over parallel corpora based methods and dictionary based methods.
机译：学习排名（LTR）是指用于在排名任务中训练模型的机器学习技术。 LTR已被证明在信息检索（IR）的许多应用中很有用。跨语言信息检索（CLIR）是主要的IR任务之一，可以从LTR中受益以提高排名准确性。 CLIR处理以一种语言表示查询并以另一种语言检索相关文档的问题。 CLIR中最重要的问题之一是如何在跨语言环境中应用单语言IR方法。在本文中，我们提出了一种将LTR用于CLIR的新方法，该方法将文档表示为特征向量。此方法提供了基于IR启发式的映射，以在基于并行语料库的CLIR中使用单语IR功能。这些映射的特征被视为LTR的训练数据。我们表明，使用在映射特征上训练的LTR可以提高CLIR性能。对英语-波斯语CLIR的综合评估表明，与基于并行语料库的方法和基于字典的方法相比，我们的方法有了显着改进。

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  • 会议地点 Montpellier(FR)
  • 作者

    Hosein Azarbonyad; Azadeh Shakery; Heshaam Faili;

  • 作者单位

    Department of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran;

    Department of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran;

    Department of Electrical and Computer Engineering, College of Engineering, University of Tehran, Iran;

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  • 正文语种 eng
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