Assessment of Name Based Algorithms for Land Administration Ontology Matching

Abstract

The purpose of this paper is to tackle semantic heterogeneity problem between land administration domain ontologies using name based ontology matching approach. The majority of ontology matching solutions use one or more string similarity measures to determine how similar two concepts are. Due to wide variety of available general purpose techniques it is not always clear which ones to use for a specific domain. The goal of this research is to evaluate several most applicable string similarity measures for use in land administration domain ontology matching. To support the research ontology matching tool prototype is developed, where the proposed algorithms are implemented. The practical results of ontology matching for State Land Service of Latvia are presented and analyzed. Matching of Land Administration Domain Model international standard, present Latvian Land Administration ontology is conducted.

Reusability ontology in business processes with similarity matching

“…The SPARQL query gives a value of 40% of the entire component on the ontology to be reused. Jaro-Winkler distance has a value of matching process of 0.67, the matching process performed gives maximum results if the value is above 0.5 and close to 1 [17]. In the matching process will be obtained similarity between ontology can be reused to make more optimal ontology again in accordance with SOP.…”

“…This algorithm is used in matching the same string. At Jaro-Winkler distance approaches 1 for string matching the string is almost the same, and if the Jaro-Winkler value is close to 0 then there is no similarity between strings [16] [17]. Graph 1 provides information that Jaro-Winkler shows matching results between strings with a resemblance of 0.5 -0.6 [17].…”

“…At Jaro-Winkler distance approaches 1 for string matching the string is almost the same, and if the Jaro-Winkler value is close to 0 then there is no similarity between strings [16] [17]. Graph 1 provides information that Jaro-Winkler shows matching results between strings with a resemblance of 0.5 -0.6 [17]. The Jaro-Winkler distance algorithm has an effective quadratic runtime complexity time complexity on string and maximum [18].…”

Plagiarsm Checker pada Sistem Manajemen Data Tugas Akhir

“…Setelah dilakukan penelitian, maka dapat disimpulkan bahwa algoritma Jaro Winkler memiliki nilai MAP 0,87 dan dapat dikatakan merupakan algoritma terbaik. Studi kasus yang sedikit berbeda dilakukan pada penelitian Imants Zarembo, dkk [8] pada tahun 2015. Tujuan dari penelitian ini adalah untuk mengevaluasi beberapa pendekatan pencocokan ontologi yang dapat digunakan dalam domain administrasi pertanahan.…”

Automatic Transformation of Relational Database Schema into OWL Ontologies

“…The third part is designed for manual and automatic ontology matching. Ontology matcher consists of several name based ontology matching algorithms [15] that can be used automatically [18].…”