Shiva: A Framework for Graph Based Ontology Matching
@article{Mathur2014ShivaAF, title={Shiva: A Framework for Graph Based Ontology Matching}, author={Iti Mathur and Nisheeth Joshi and Hemant Darbari and Ajai Kumar}, journal={ArXiv}, year={2014}, volume={abs/1403.7465} }
Since long, corporations are looking for knowledge sources which can provide structured description of data and can focus on meaning and shared understanding. Structures which can facilitate open world assumptions and can be flexible enough to incorporate and recognize more than one name for an entity. A source whose major purpose is to facilitate human communication and interoperability. Clearly, databases fail to provide these features and ontologies have emerged as an alternative choice, but…
13 Citations
Shiva++: An Enhanced Graph based Ontology Matcher
- Computer ScienceArXiv
- 2014
The development of one such matcher which merges the concepts available in two ontologies at two levels; 1) at string level and 2) at semantic level; thus producing better merged ontologies.
Shiva++_CL: An Enhanced Graph based Cross Lingual Ontology Matcher
- Computer Science
- 2020
This paper shows the development of cross lingual ontology matcher at two levels:1) at String level and 2) Semantic level.
A framework to aggregate multiple ontology matchers
- Computer ScienceInt. J. Web Inf. Syst.
- 2020
A computational solution for ontology meta-matching (OMM) and a framework designed for developers to make use of alignment techniques in their applications that is able to adapt to different test cases.
A weighted graph-oriented ontology matching algorithm for enhancing ontology mapping and alignment in Semantic Web
- Computer ScienceSoft Comput.
- 2019
The pragmatic nature of this matching solution is an advantage which approaches the task in a simplistic and efficient manner and provides some room for the manual decision making which can be efficient in deciding matching levels in certain hesitant matches.
CROSS LINGUAL ONTOLOGY MATCHING BASED ON FUZZY SYNTACTIC MATCHING
- Computer ScienceInternational Journal of Advanced Research in Computer Science
- 2020
A way to deal with take care of the issue of multilingualism on the semantic web, in view of Syntactic matching is presented.
Enriching user model ontology for handicraft domain by FOAF
- Computer Science2015 IEEE/ACIS 14th International Conference on Computer and Information Science (ICIS)
- 2015
This paper proposes an approach for user model ontology construction, and proposes two algorithms for matching and merging ontologies so as to achieve the enrichment with FOAF.
Ontology Matching Using BabelNet Dictionary and Word Sense Disambiguation Algorithms
- Computer Science
- 2017
Overall, the most effective methods are Wu & Palmer and Adapted Lesk, which is widely used for Word Sense Disambiguation (WSD) in the field of Automatic Natural Language Processing (NLP).
Comparison of Ontology Alignment Systems Across Single Matching Task Via the McNemar’s Test
- Computer ScienceACM Trans. Knowl. Discov. Data
- 2018
The statistical procedures that enable us to theoretically favor one system over one another are proposed and applied to the systems participated in the OAEI 2016 anatomy track, and also compares several well-known similarity metrics for the same matching problem.
Comparison of ontology alignment algorithms across single matching task via the McNemar test
- Computer ScienceArXiv
- 2017
Investigation on the methods participated in the anatomy track of OAEI 2016 demonstrates that AML and CroMatcher are the top two methods and DKP-AOM and Alin are the boom two ones.
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