TY - Jour A2 - Hwang，Feng-Jang Au - 薛，Xingsi Au - Lu，Jiawei Au - Jiang，Chengcai Au - Huang，Yikun Py - 2020 DA - 2020/11/25 Ti - 传感器本体代表异质性测量SP -6666228 VL - 2020 AB - 不同传感器本体中的异质性问题会阻碍信息的交互。本体匹配是通过确定异构概念对来解决这个问题的有效方法。在匹配过程中，相似度测量用作内核技术，其计算两个概念的相似性值。由于相似性措施没有任何相似度措施，通常情况下，通常情况下，若干措施将组合在一起以增强结果的信心。如何找到各种相似度措施的合适的聚合权重，即本体代码匹配问题，是一个开放的挑战。本文提出了一种新的本体类别代理方法来提高传感器本体对齐的质量，它利用两个本体上的异质性特征来调整聚集重量集。In particular, three ontology heterogeneity measures are firstly proposed to, respectively, evaluate the heterogeneity values in terms of syntax, linguistics, and structure, and then, a semiautomatically learning approach is presented to construct the conversion functions that map any two ontologies’ heterogeneity values to the weights for aggregating the similarity measures. To the best of our knowledge, this is the first time that heterogeneity features are proposed and used to solve the sensor ontology metamatching problem. The effectiveness of the proposal is verified by comparing with using state-of-the-art ontology matching techniques on Ontology Alignment Evaluation Initiative (OAEI)’s testing cases and two pairs of real sensor ontologies. SN - 1530-8669 UR - https://doi.org/10.1155/2020/6666228 DO - 10.1155/2020/6666228 JF - Wireless Communications and Mobile Computing PB - Hindawi KW - ER -