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A new semantic similarity approach for improving the results of an Arabic search engine

机译:一种新的语义相似性方法,用于改善阿拉伯搜索引擎的结果

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Determining semantic similarity between documents is crucial to many tasks such as plagiarism detection, automatic technical survey and semantic search. In this paper, we have mainly focused on detecting the semantic similarity between documents in large documents collection and queries based on an Arabic search engine, we investigated MapReduce as a specific framework for managing distributed processing in dataset pattern and semantic similarity measures of documents. Then we study the state of the art of different approaches for computing the similarity of documents. We propose an approach based on parallel algorithm of semantic similarity measures using MapReduce and WordNet after translation phase to detect the relevant documents in the face of the Arabic query. The numerical results obtained and presented showed the efficiency and the performance of the technique adopted.
机译:确定文档之间的语义相似性对于许多任务至关重要,例如gi窃检测,自动技术调查和语义搜索。在本文中,我们主要集中在基于阿拉伯搜索引擎的大型文档集合和查询中检测文档之间的语义相似性,我们研究了MapReduce作为管理分布式数据集模式和文档语义相似性度量的特定框架。然后,我们研究了用于计算文档相似度的不同方法的最新水平。我们提出一种基于语义相似性度量的并行算法的方法,该方法在翻译阶段之后使用MapReduce和WordNet来检测面对阿拉伯查询的相关文档。获得并给出的数值结果表明所采用技术的效率和性能。

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