利用遗传算法求解悬挂相关性

2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering Pub Date : 2012-10-04 DOI:10.1109/URKE.2012.6319593

Ashutosh Kumar Singh, K. P. Ravi, A. G. K. Leng

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引用次数: 2

摘要

随着Web页面的不断增加，信息检索中的排名问题日益突出。在排名计算中排除这些页面可能会给出有偏差/不一致的结果。另一方面，包含这些页面将显著降低速度。然而，大多数IR排名算法都排除了挂页。但由于计算量和时间的复杂性，网络上存在着一些重要的相关挂页，不容忽视。在我们提出的方法中，我们将相关的挂页包含在排名中。应用遗传算法实现挂页的相关性和非相关性。

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Solving hanging relevancy using genetic algorithm

Continuous growth of hanging pages with Web makes a significant problem for ranking in the information retrieval. Exclusion of these pages in ranking calculation can give biased/inconsistent result. On the other hand inclusion of these pages will reduce the speed significantly. However most of the IR ranking algorithms exclude the hanging pages. But there are relevant and important hanging pages on the Web and they cannot be ignored because of the complexity in computation and time. In our proposed method, we include the relevant hanging pages in the ranking. Relevancy or non-relevancy of hanging pages is achieved by application of Genetic Algorithm (GA).

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2012 2nd International Conference on Uncertainty Reasoning and Knowledge Engineering

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