信息检索中的两个数据融合方法比较

Comparison of two data fusion methods for information retrieval

讨论一种常见的集成方法——距离平方和最小准则,指出该准则下由线性加权原理所得融合结果的优良性以及信息检索文献中的一个错误。然后通过分析基于距离之和最小准则所得融合结果的检索性能,发现由基于距离之和最小准则得到的融合结果距离原始检索结果最近。最后,通过实例验证了该方法的结果。

Data fusion technology was initiated in the field of information retrieval around the 1990s. By using different strategies in a variety of ways to study the retrieval fusion, it can be found that the integration strategy can greatly improve the efficiency of information retrieval. In this paper, the authors focused on a common search strategy, the minimum distance square sum principle, and pointed out the optimality of the results under the linear integration principle and a mistake in information retrieval literatures. Then they analyzed the performance of fusion results based on the minimum distance stun. It is concluded that the fusion results weighted by the minimum distance sum are most approximate to the original retrieval results. Finally, the conclusion was demonstrated by some experiments.