论文标题
使用BIO INSIM INSIMER集群检索Web服务检索的框架
A Framework for Web Services Retrieval Using Bio Inspired Clustering
论文作者
论文摘要
由于Web技术领域的不可思议的增长，有效地发现有关特定用户查询的相关Web服务已成为越来越多的挑战。在以前的工作中，已使用不同的聚类模型来解决这些问题。但是，大多数传统的聚类技术在计算上都是密集的，无法解决所涉及的所有问题。此外，当前的标准无法在聚类和检索过程中纳入Web服务的语义相关性，从而导致性能下降。在本文中，我们为Web服务检索提出了一个框架，该框架使用自下而上，分散和自组织的方法用于群集可用服务。它还提供了群集的在线动态计算，从而克服了传统聚类方法的缺点。我们还将Web服务之间的语义相似性用于聚类过程，以提高精度并降低召回率。
Efficiently discovering relevant Web services with respect to a specific user query has become a growing challenge owing to the incredible growth in the field of web technologies. In previous works, different clustering models have been used to address these issues. But, most of the traditional clustering techniques are computationally intensive and fail to address all the problems involved. Also, the current standards fail to incorporate the semantic relatedness of Web services during clustering and retrieval resulting in decreased performance. In this paper, we propose a framework for web services retrieval that uses a bottom-up, decentralized and self organising approach to cluster available services. It also provides online, dynamic computation of clusters thus overcoming the drawbacks of traditional clustering methods. We also use the semantic similarity between Web services for the clustering process to enhance the precision and lower the recall.
