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Based on semantic web ontology mapping model and its implementation

Author: ZhaoZhongCheng
Tutor: WangPu;ZuoJianZhuo;FangLiYing
School: Beijing University of Technology
Course: Control Science and Control Engineering
Keywords: Semantic Web Ontology Ontology mapping Sniper-OM
CLC: TP311.52
Type: Master's thesis
Year: 2010
Downloads: 104
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Abstract


With the development of the World Wide Web, more network information resources. In order to realize the Internet information resources sharing and reuse, the Semantic Web is proposed and received wide attention from domestic and foreign research institutions, and is listed as 2008-1012 Gartner, Inc. 10 years transformative technologies. Semantic Web aims marking information and allow the computer can understand, so that the entire World Wide Web as a structured knowledge base. Semantic Web ontology as the core network for the expression of semantic information. However, due to different ontology modeling tools and methods, the researchers knowledge structure different levels, as well as differences in the impact of research areas, leading to the generation of heterogeneous body, affecting the further development of the Semantic Web, ontology mapping technology emerges . This paper introduces the ontology mapping status and significance, the prototype system for ontology mapping and the use of technical methods for comparison and analysis, drawing OLA mapping system proposed Sniper-OM ontology mapping framework. Sniper-OM from the entity name, description and other elements of the content level and the body structure of the data hierarchy level two aspects of discussion and research. Sniper-OM compared to other system has the following characteristics: (1) using an external dictionary WordNet, consider \determine the measure of the purity of the sample cluster algorithm; (3) to consider different edge weights, the use of graph matching strategy generation ontology matching diagram calculation similarity. Conceptual information element level mainly consider the impact on the similarity is proposed based on the external dictionary WordNet's OHIIC algorithms and text-based vectors CV algorithms. OHIIC using WordNet hierarchy information, find the shortest path in the traditional method \degree of influence. Analytical concepts and concepts associated with all labeling information, generate text vector, the use of improved TF / IDF similarity is calculated. Finally take OHIIC and CV calculations the maximum similarity value as two entities. Structural level ontology graph structure mainly consider the impact on the similarity, except the usual method using the classes, attributes and hierarchy information, but also taking into account the structural information attribute instance exists, examples of the concept of similarity calculation method is proposed judgment clusters measure within the sample purity - purity of information entropy, clusters formed by clustering analysis of information entropy purity has a collection of instances of ontology concept similarity. Experimental results show that ontology mapping method showed high performance. Also consider the relationship between the impact of the main body, between the introduction of different types of hardware description different weights matrix regeneration costs, the introduction of graph theory algorithm to generate the ontology matching diagram (MGO). Based on the aforementioned studies, this paper implements Sniper-OM prototype system, and use the OAEI 2008 test set to test the system performance, from the recall, precision and F-Measure3 respects with the other 15 mapping system experimental comparison, results show that the Sniper- OM system came in fourth place, stronger than the OLA mapping system, indicating that the system considering the classes, properties and instances stronger than the OLA single calculation method using the edit distance method. As multi-strategy combined method is relatively simple and based on structural similarity between weights settings require more human involvement, the method inferior Lily, ASMOV, RiMOM mapping system. Finally, the research work carried out summary and outlook. The research on ontology mapping technology has a certain significance. Find the shortest path to consider \Mapping prototype realization of this study further research work group have some help.

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