一种结合一阶逻辑和语义相似度的异构数据匹配算法

2014 International Conference on Information Science & Applications (ICISA) Pub Date : 2014-05-06 DOI:10.1109/ICISA.2014.6847329

Gang Liu, Caixia Lu, Shaobin Huang, Suyan Sun

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引用次数: 1

摘要

本文研究了一种基于神经网络的信息匹配方法，该方法结合一阶逻辑和语义相似度完成表匹配，利用SOM+生成反馈神经网络完成字段匹配。该方法可以有效降低匹配时间复杂度。通过历史匹配，有效地减少了神经网络的训练时间，提高了匹配的准确性。

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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A Heterogeneous Data Matching Algorithm with Combining First-Order Logic and Semantic Similarity

In this paper studies a kind of information matching method based on neural network, and the method combines first-order logic and semantic similarity to complete the table matching, using SOM+ to generate feedback neural network to complete the field matching. The method can effectively reduce the matching time complexity. And by using history match, it effectively reduces the training time of neural network, improving the accuracy of matching.

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2014 International Conference on Information Science & Applications (ICISA)

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