Automatic Metadata Generation Using Associative Networks
Automatic Metadata Generation Using Associative Networks
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DOI：
10.1145/1462198.1462199
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发表时间：
2009-01-01
影响因子：
5.6
通讯作者：
De Sompel, Herbert Van
中科院分区：
文献类型：
--
作者：
Rodriguez, Marko A.;Bollen, Johan;De Sompel, Herbert Van
尽管元数据具有巨大的价值，但它通常是稀疏和不完整的，从而妨碍了数字信息服务的有效性。用于自动创建元数据的许多现有机制主要依赖于内容分析，这可能是昂贵且低效的。本文中提出的自动元数据生成系统利用从现有元数据生成的资源关系作为从元数据丰富的资源传播到元数据贫乏的资源的媒介。由于其独立于内容分析，它可以应用于各种各样的资源媒体类型，并被证明是计算成本低廉。所提出的方法通过两个不同的阶段进行操作。出现和共现算法首先利用现有的存储库元数据生成存储库资源的关联网络。其次，使用关联网络作为基底，与元数据丰富的资源相关联的元数据通过离散形式的扩散激活算法传播到元数据贫乏的资源。本文讨论了建立关联网络的一般框架，通过这种网络传播元数据的算法，以及使用标准书目数据集的实验和验证所提出的方法的结果。
In spite of its tremendous value, metadata is generally sparse and incomplete, thereby hampering the effectiveness of digital information services. Many of the existing mechanisms for the automated creation of metadata rely primarily on content analysis which can be costly and inefficient. The automatic metadata generation system proposed in this article leverages resource relationships generated from existing metadata as a medium for propagation from metadata-rich to metadata-poor resources. Because of its independence from content analysis, it can be applied to a wide variety of resource media types and is shown to be computationally inexpensive. The proposed method operates through two distinct phases. Occurrence and cooccurrence algorithms first generate an associative network of repository resources leveraging existing repository metadata. Second, using the associative network as a substrate, metadata associated with metadata-rich resources is propagated to metadata-poor resources by means of a discrete-form spreading activation algorithm. This article discusses the general framework for building associative networks, an algorithm for disseminating metadata through such networks, and the results of an experiment and validation of the proposed method using a standard bibliographic dataset.