Comparisons of diagnosis in mapping repair systems

Husein, Inne Gartina; Sitohang, Benhard; Akbar, Saiful; Azizah, Fazat Nur

doi:10.1109/icodse.2016.7936150

Cited by 6 publications

(5 citation statements)

References 3 publications

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“…In this work, we use the commercial linear programming tool Cplex which is an optimization software developed by IBM ILOG. 3…”

Section: A Model For Resolving Logical Contradictionsmentioning

confidence: 99%

“…In the algorithm, all distinct axioms in the conflicts are obtained each of which is associated with a binary variable 3 https://www.ibm.com/analytics/cplex-optimizer (see lines 3 and 4). To construct the objective function, all axioms are regarded as the same important and thus 1 is assigned to the coefficients in the function (see Line 5).…”

Section: ) Ilp-based Algorithm For Resolving Logical Contradictions mentioning

confidence: 99%

“…In the Semantic Web, ontologies provide shared and precisely defined terms and play a key role in the formal representation of knowledge [1], [2]. Since building ontologies is an error-prone effort and ontologies often evolve over time, logical contradictions are always unavoidable in many application scenarios like ontology construction, ontology revision and ontology mapping [3]- [6]. Generally, logical contradictions consist of inconsistency and incoherence.…”

Section: Introductionmentioning

confidence: 99%

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Resolving Logical Contradictions in Description Logic Ontologies Based on Integer Linear Programming

Khaoula

2019

IEEE Access

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When resolving logical contradictions in ontologies, Reiter's hitting set tree algorithm is often applied to satisfy the minimal change principle. To improve the efficiency, the researchers have proposed various algorithms by using a scoring function, defining new semantics or applying some heuristic strategies. However, these algorithms either sacrifice minimal change or are designed for less expressive ontologies like DL-Lite. In this paper, we propose a mathematic approach based on integer linear programming, which is an optimization problem of maximizing or minimizing a linear objective function, to deal with DL ontologies. Specifically, we define the integer linear programming-based model to resolve logical contradictions. To realize the model, we propose one algorithm to find a cardinality-minimal solution and two algorithms dealing with weighted ontologies. Our experiments are conducted over 70 real-life and artificial ontologies to compare our algorithms with those hitting set tree-based ones. Through the experiments, the prominent efficiency and effectiveness have been exhibited by our algorithms. They usually take about 0.4 s to find a solution while others spend more than 100 s in many cases. The experimental results also show that the first two algorithms could find the cardinality-minimal solutions and those with a minimal sum of weights, respectively. INDEX TERMS Logical contradictions, inconsistency handling, ontology repair, semantic web, integer linear programming.

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“…In this work, we use the commercial linear programming tool Cplex which is an optimization software developed by IBM ILOG. 3…”

Section: A Model For Resolving Logical Contradictionsmentioning

confidence: 99%

Section: ) Ilp-based Algorithm For Resolving Logical Contradictions mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Resolving Logical Contradictions in Description Logic Ontologies Based on Integer Linear Programming

Khaoula

2019

IEEE Access

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“…It meant local technique was better in minimizing the total amount of confidence value of deleted mappings, which was minimal focus one. Another study about new global technique explained the possibility to achieve two focuses minimal in one repair technique [13]. This new technique combined two focuses minimal of local and global, which were (1) minimal in the number of deleted mappings; and (2) minimal in the total amount of confidence values of deleted mappings.…”

Section: A Repair Comparisonmentioning

confidence: 99%

“…Mapping Deletion in Local Technique[13] Mapping Deletion in Global Technique[13] Intersection Searching in Global Technique…”

mentioning

confidence: 99%

Minimizing the Estimated Solution Cost with A* Search to Support Minimal Mapping Repair

Husein¹,

Sitohang²,

Akbar³

2017

EECSI

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Incoherent alignment has been the main focus in the matching process since 2010. Incoherent means that there is semantic or logic conflict in the alignment. This condition encouraged researches in ontology matching field to improve the alignment by repairing the incoherent alignment. Repair mapping will restore the incoherent to coherent mapping, by deleting unwanted mappings from the alignment. In order to minimize the impacts in the input alignment, repair process should be done as as minimal as possible. Definition of minimal could be (1) reducing the number of deleted mappings, or (2) reducing the total amount of deleted mappings' confidence values. Repair process with new global technique conducted the repair with both minimal definitions. This technique could reduce the number of deleted mappings and total amount of confidence values at the same time. We proposed A * Search method to implement new global technique. This search method was capable to search the shortest path which representing the fewest number of deleted mappings, and also search the cheapest cost which representing the smallest total amount of deleted mappings' confidence value. A* Search was both complete and optimal to minimize mapping repair size.

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Minimizing the estimated solution cost with A* search to support minimal mapping repair

Husein

Sitohang

Akbar

2017

2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)

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Comparisons of diagnosis in mapping repair systems

Cited by 6 publications

References 3 publications

Resolving Logical Contradictions in Description Logic Ontologies Based on Integer Linear Programming

Resolving Logical Contradictions in Description Logic Ontologies Based on Integer Linear Programming

Minimizing the Estimated Solution Cost with A* Search to Support Minimal Mapping Repair

Minimizing the estimated solution cost with A* search to support minimal mapping repair

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