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Intelligent Time-Aware Query Translation for Text Sources

机译:文本源的智能时间感知查询翻译

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摘要

Time-stamped documents such as newswire articles, blog posts and other web-pages are often archived online. Since these archives cover long spans of time, the terminology in them could undergo significant evolution. In answering user queries over such text, it is desirable that the system be intelligent enough to incorporate historical information. For example, a query on Sri Lanka should automatically retrieve documents with its former name Ceylon. Hence, temporal terminology evolution needs to be taken into account to translate these queries. This has become vital today because users expect that computer systems have the intelligence to find all related information pertaining to their queries. In this research we attempt to discover such concepts that evolve over time and use those discovered concepts to provide time-aware responses to user queries. Our solution and evaluation are summarized in the paper.
机译:带时戳的文档(例如新闻专线文章,博客文章和其他网页)通常在线存储。由于这些档案的时间跨度很长,因此其中的术语可能会发生重大变化。在回答关于此类文本的用户查询时,希望系统足够智能以合并历史信息。例如,对斯里兰卡的查询应自动检索以前的名称为锡兰的文档。因此,需要考虑时间术语的演变来翻译这些查询。今天这已变得至关重要,因为用户希望计算机系统能够找到与他们的查询有关的所有相关信息。在这项研究中,我们尝试发现随着时间的推移而演变的概念,并使用这些发现的概念为用户查询提供时间感知的响应。本文总结了我们的解决方案和评估。

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