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A Concept Lattice for Semantic Integration of Geo-Ontologies Based on Weight of Inclusion Degree Importance and Information Entropy

School of Resources and Environment Science, Wuhan University, No.129 Luoyu Road, Wuhan 430079, China
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Academic Editor: Adom Giffin
Entropy 2016, 18(11), 399; https://doi.org/10.3390/e18110399
Received: 23 August 2016 / Revised: 1 October 2016 / Accepted: 10 November 2016 / Published: 15 November 2016
Constructing a merged concept lattice with formal concept analysis (FCA) is an important research direction in the field of integrating multi-source geo-ontologies. Extracting essential geographical properties and reducing the concept lattice are two key points of previous research. A formal integration method is proposed to address the challenges in these two areas. We first extract essential properties from multi-source geo-ontologies and use FCA to build a merged formal context. Second, the combined importance weight of each single attribute of the formal context is calculated by introducing the inclusion degree importance from rough set theory and information entropy; then a weighted formal context is built from the merged formal context. Third, a combined weighted concept lattice is established from the weighted formal context with FCA and the importance weight value of every concept is defined as the sum of weight of attributes belonging to the concept’s intent. Finally, semantic granularity of concept is defined by its importance weight; we, then gradually reduce the weighted concept lattice by setting up diminishing threshold of semantic granularity. Additionally, all of those reduced lattices are organized into a regular hierarchy structure based on the threshold of semantic granularity. A workflow is designed to demonstrate this procedure. A case study is conducted to show feasibility and validity of this method and the procedure to integrate multi-source geo-ontologies. View Full-Text
Keywords: geo-ontologies integration; semantic granularity; formal concept analysis; weighted concept lattice; inclusion degree; information entropy geo-ontologies integration; semantic granularity; formal concept analysis; weighted concept lattice; inclusion degree; information entropy
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Xiao, J.; He, Z. A Concept Lattice for Semantic Integration of Geo-Ontologies Based on Weight of Inclusion Degree Importance and Information Entropy. Entropy 2016, 18, 399.

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