Automatic translation of Arabic queries for bilingual information retrieval

Souheyl Mallat, A. Zouaghi, Emna Hkiri, M. Zrigui
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Abstract

In this paper, we present an automatic query translation in Arabic for information retrieval. This system, implements a method for lexical disambiguation of terms in a query. To choose the best sense, each term of the query is projected on the French EuroWordNet and we extract his related concepts in order to form a semantic network. In a second time using the same type of network, but by integrating LSI (Latent Semantic Index), and extraction of contextual hidden links between the concepts of the list (listSRF). This list extracted by the automatic alignment by Mkalign tool's, from the knowledge base defined by the Monde Diplomatic parallel corpus. This tool will allow us to map between the relevant sentences in Arabic identified in our previous work with French sentences to build a listSRF. This list forms the basis of the lexical disambiguation method. Finally, we propose a mechanism for selecting the best sense of the ambiguous term of the query, based on the matching between each network corresponds to a word in the query with the network listSRF to extract an adequate sense with the highest degree of similarity. An evaluation and comparison are conducted to measure the quality of our translation system.
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用于双语信息检索的阿拉伯语查询自动翻译
本文提出了一种用于信息检索的阿拉伯语自动查询翻译系统。本系统实现了查询中词汇消歧的方法。为了选择最佳的语义,我们将查询的每个术语投影到法语EuroWordNet上,并提取其相关概念以形成语义网络。在第二次使用相同类型的网络,但通过集成LSI (Latent Semantic Index),并提取上下文隐藏链接之间的概念列表(listSRF)。该列表由Mkalign工具自动对齐,从世界外交平行语料库定义的知识库中提取。这个工具将允许我们在之前的工作中识别的阿拉伯语相关句子与法语句子之间进行映射,以建立一个listSRF。这个列表构成了词法消歧方法的基础。最后,我们提出了一种选择查询歧义项的最佳意义的机制,基于查询中每个网络对应的单词与网络listSRF之间的匹配,以提取具有最高相似度的适当意义。对翻译系统的质量进行了评价和比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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