Multi-Engine Search and Language Translation
Multi-Engine Search and Language Translation
复制标题
多引擎搜索和语言翻译
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Georgia Koutrika
中科院分区：
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作者：
S. Simske;Igor M. Boyko;Georgia Koutrika
用户与数据库交互的两个最重要的元素是搜索和语言翻译。搜索用于通过查询访问数据库系统，响应的准确性和完整性是关键挑战。语言翻译将内容重新用于不同的受众，并且可以使用搜索输出相似度直接评估翻译文本的准确性。在本文中，我们总结了以前未发表的方法，以提高搜索和翻译的质量，目的是提高这两个任务的准确性。具体来说，多引擎和相关的元算法方法被证明是有前途的手段，提高搜索和翻译的性能。然后，我们描述了搜索和翻译如何结合起来，以创建一个更强大的整体文本挖掘项目的愿景。
Two of the most important elements in user interaction with a database are search and language translation. Search is used to access a database system through queries, for which the accuracy and completeness of response are key challenges. Language translation re-purposes content for a different audience, and the accuracy of translated text can be directly evaluated using search output similarity. In this paper, we summarize previously unpublished approaches to improving the quality of both search and translation, with an aim of improving the accuracy of both of these tasks. Specifically, multi-engine and related metaalgorithmic approaches are shown to be promising means of improving the performance of both search and translation. We then describe the vision of how search and translation can be combined to create a more robust overall text mining project.