基于本体的汇总视图图形可视化

Xin Huang, Byron Choi, Jianliang Xu, W. K. Cheung, Yanchun Zhang, Jiming Liu
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引用次数: 5

摘要

将数据集的一个小子集呈现给用户的数据摘要已经广泛应用于许多应用程序和系统中。许多数据集用分层术语编码,例如,国际疾病分类-9,医学主题标题和基因本体,仅举几例。在本文中,我们研究了选择不同的k个元素集合来总结具有层次术语的输入数据集的问题,并在本体结构中可视化总结。我们提出了一种有效的贪心算法来解决具有(1-1/e)≈62%近似保证的问题。在实际数据集上的初步实验结果表明了该算法的有效性和高效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ontology-based Graph Visualization for Summarized View
Data summarization that presents a small subset of a dataset to users has been widely applied in numerous applications and systems. Many datasets are coded with hierarchical terminologies, e.g., the international classification of Diseases-9, Medical Subject Heading, and Gene Ontology, to name a few. In this paper, we study the problem of selecting a diverse set of k elements to summarize an input dataset with hierarchical terminologies, and visualize the summary in an ontology structure. We propose an efficient greedy algorithm to solve the problem with (1-1/e)≈ 62%-approximation guarantee. Preliminary experimental results on real-world datasets show the effectiveness and efficiency of the proposed algorithm for data summarization.
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