scholarly journals Ontology Knowledge Mining for Ontology Alignment

2016 ◽  
Vol 9 (5) ◽  
pp. 876-887 ◽  
Author(s):  
Rihab Idoudi ◽  
Karim Saheb Ettabaa ◽  
Basel Solaiman ◽  
Kamel Hamrouni
Keyword(s):  
Ontology Alignment ◽  
Knowledge Mining

scholarly journals Knowledge Mining in Spreading Pattern of COVID-19 and Its Impact on India Economy

2021 ◽  
Vol 1797 (1) ◽  
pp. 012013
Author(s):  
Rohit Shaw ◽  
Madhusmita Mishra ◽  
Amrut Ranjan Jena
Keyword(s):  
Knowledge Mining ◽  
Spreading Pattern

A faster and less aggressive algorithm for correcting conservativity violations in ontology alignments

2021 ◽  
pp. 1-20
Author(s):  
Cauã Roca Antunes ◽  
Alexandre Rademaker ◽  
Mara Abel
Keyword(s):  
State Of The Art ◽  
Time Algorithm ◽  
The State ◽  
Ontology Alignment ◽  
Ontology Alignment Evaluation Initiative ◽  
Multiple Ontologies

Ontologies are computational artifacts that model consensual aspects of reality. In distributed contexts, applications often need to utilize information from several distinct ontologies. In order to integrate multiple ontologies, entities modeled in each ontology must be matched through an ontology alignment. However, imperfect alignments may introduce inconsistencies. One kind of inconsistency, which is often introduced, is the violation of the conservativity principle, that states that the alignment should not introduce new subsumption relations between entities from the same source ontology. We propose a two-step quadratic-time algorithm for automatically correcting such violations, and evaluate it against datasets from the Ontology Alignment Evaluation Initiative 2019, comparing the results to a state-of-the-art approach. The proposed algorithm was significantly faster and less aggressive; that is, it performed fewer modifications over the original alignment when compared to the state-of-the-art algorithm.

INSTANCE MIGRATION BETWEEN ONTOLOGIES HAVING STRUCTURAL DIFFERENCES

2011 ◽  
Vol 20 (06) ◽  
pp. 1127-1156 ◽  
Author(s):  
MAXIM DAVIDOVSKY ◽  
VADIM ERMOLAYEV ◽  
VYACHESLAV TOLOK
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Structural Changes ◽  
Software Framework ◽  
Ontology Alignment ◽  
Transformation Rules ◽  
Structural Differences ◽  
Prototype Software ◽  
Descriptive Theories ◽  
Future Work

Ontology instance migration is one of the complex and not fully solved problems in knowledge management. A solution is required when the ontology schema evolves in the life cycle and the assertions have to be transferred to the newer version. The problem may become more complex in distributed settings when, for example, several autonomous software entities use and exchange partial assertional knowledge in a domain that is formalized by different though semantically overlapping descriptive theories. Such an exchange is essentially the migration of the assertional part of an ontology to other ontologies belonging to or used by different entities. The paper presents our method and tool for migrating instances between the ontologies that have structurally different but semantically overlapping schemas. The approach is based on the use of the manually coded transformation rules describing the changes between the input and the output ontologies. The tool is implemented as a plug-in for the ProjectNavigator prototype software framework. The article also reports the results of our three evaluation experiments. In these experiments we evaluated the degree of complexity in the structural changes to which our approach remains valid. We also chose the ontology sets in one of the experiments to make the results comparable with the ontology alignment software. Finally we checked how well our approach scales with the increase of the quantity of the migrated ontology instances to the numbers that are characteristic to industrial ontologies. In our opinion the evaluation results are satisfactory and suggest some directions for the future work.

A mixed approach for automated spatial ontology alignment

2010 ◽  
Vol 55 (2) ◽  
pp. 237-255 ◽  
Author(s):  
Reza Khatami ◽  
Ali Asghar Alesheikh ◽  
Majid Hamrah
Keyword(s):  
Ontology Alignment ◽  
Mixed Approach

An Integer Linear Programming-Based Method for the Extraction of Ontology Alignment

2021 ◽  
Vol 16 (2) ◽  
pp. 25-44
Author(s):  
Naima El Ghandour ◽  
Moussa Benaissa ◽  
Yahia Lebbah
Keyword(s):  
Linear Programming ◽  
Semantic Web ◽  
Integer Linear Programming ◽  
New Method ◽  
Ontology Matching ◽  
Ontology Alignment ◽  
Programming Techniques ◽  
Data Heterogeneity ◽  
Series Of Experiments

The Semantic Web uses ontologies to cope with the data heterogeneity problem. However, ontologies become themselves heterogeneous; this heterogeneity may occur at the syntactic, terminological, conceptual, and semantic levels. To solve this problem, alignments between entities of ontologies must be identified. This process is called ontology matching. In this paper, the authors propose a new method to extract alignment with multiple cardinalities using integer linear programming techniques. The authors conducted a series of experiments and compared them with currently used methods. The obtained results show the efficiency of the proposed method.

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