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Discovering text databases on the Internet: neural net agent approach

机译:在Internet上发现文本数据库:神经网络代理方法

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The proliferation of readily available but rapidly increasing document databases on the Internet has led to the text database discovery problem: finding those text databases (out of many candidates) that provide documents that are relevant to the user query. In this paper, we present a neural net agent for text database discovery. Our agent, which is trained with sufficient training queries, discovers those text databases that contain the relevant documents for a given query and then retrieves those documents effectively. We first present a framework for the neural net agent, and then describe its training and document retrieval procedures. We also evaluate the performance of our neural net agent experimentally.
机译:Internet上现成但迅速增长的文档数据库的激增导致了文本数据库发现问题:从提供大量与用户查询相关的文档的文本数据库中找到许多候选数据库。在本文中,我们提出了一种用于文本数据库发现的神经网络代理。我们的代理人经过充分的训练查询培训,发现包含给定查询相关文档的文本数据库,然后有效地检索了这些文档。我们首先介绍神经网络代理的框架,然后描述其训练和文档检索程序。我们还将通过实验评估神经网络代理的性能。

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