The Implementation of DSSim

2017 ◽  
Vol 8 (3) ◽  
pp. 34-53 ◽  
Author(s):  
Maria Vargas-Vera
Keyword(s):  
Ontology Mapping ◽  
Ontology Alignment ◽  
Alignment System ◽  
Mapping System ◽  
Multi Agent ◽  
Syntactic Similarity

This paper presents the decisions taken during the implementation of DSSim (DSSim stands for Similarity based on Dempster-Shafer) our multi-agent ontology mapping system. It describes several types of agents and their roles in the DSSim architecture. These agents are mapping agents which are able to perform either semantic or syntactic similarity. Our architecture is generic as no mappings need to be learned in advance and it could be easily extended by adding new mapping agents in the framework. The new added mapping agents could run different similarity algorithms (either semantic or syntactic). In this way, DSSim could assess which algorithm has a better performance. Additionally, this paper presents the algorithms used in our ontology alignment system DSSim.

The Implementation of DSSim

2018 ◽  
pp. 1217-1238
Author(s):  
Maria Vargas-Vera
Keyword(s):  
Ontology Mapping ◽  
Ontology Alignment ◽  
Alignment System ◽  
Mapping System ◽  
Multi Agent ◽  
Syntactic Similarity

This paper presents the decisions taken during the implementation of DSSim (DSSim stands for Similarity based on Dempster-Shafer) our multi-agent ontology mapping system. It describes several types of agents and their roles in the DSSim architecture. These agents are mapping agents which are able to perform either semantic or syntactic similarity. Our architecture is generic as no mappings need to be learned in advance and it could be easily extended by adding new mapping agents in the framework. The new added mapping agents could run different similarity algorithms (either semantic or syntactic). In this way, DSSim could assess which algorithm has a better performance. Additionally, this paper presents the algorithms used in our ontology alignment system DSSim.

Architecture of DSSim

2015 ◽  
Vol 6 (2) ◽  
pp. 65-82
Author(s):  
Maria Vargas-Vera ◽  
Miklos Nagy
Keyword(s):  
Ontology Mapping ◽  
Mapping System ◽  
Multi Agent ◽  
Syntactic Similarity

This paper presents the architecture of DSSim (DSSim stands for Similarity based on Dempster-Shafer) our multi-agent ontology mapping system. It describes several types of agents and their roles in the DSSim architecture. These agents are mapping agents which are able to perform either semantic or syntactic similarity. The authors' architecture is generic as no mappings need to be learned in advance and it could be easily extended by adding new mapping agents in the framework. These new mapping agents could run different similarity algorithms either semantic or syntactic. In this way, DSSim could assess which algorithm has a better performance. Additionally, this paper presents the main algorithms used in DSSim and discusses DSSim advantages and drawbacks.

A New Approach Based on the Bee Optimization Algorithm for Ontology Alignment

2019 ◽  
Vol 9 (4) ◽  
pp. 13-22
Author(s):  
Fatima Ardjani ◽  
Djelloul Bouchiha
Keyword(s):  
Similarity Measures ◽  
Optimization Method ◽  
Ontology Alignment ◽  
New Approach ◽  
Alignment System ◽  
Alignment Process ◽  
Joint Consideration ◽  
Bee Colonies ◽  
Web Research ◽  
Better Than

The ontology alignment process aims at generating a set of correspondences between entities of two ontologies. It is an important task, notably in the semantic web research, because it allows the joint consideration of resources defined in different ontologies. In this article, the authors developed an ontology alignment system called ABCMap+. It uses an optimization method based on artificial bee colonies (ABC) to solve the problem of optimizing the aggregation of three similarity measures of different matchers (syntactic, linguistic and structural) to obtain a single similarity measure. To evaluate the ABCMap+ ontology alignment system, authors considered the OAEI 2012 alignment system evaluation campaign. Experiments have been carried out to get the best ABCMap+'s alignment. Then, a comparative study showed that the ABCMap+ system is better than participants in the OAEI 2012 in terms of Recall and Precision.

Experiences on the Evaluation of DSSim

2015 ◽  
Vol 6 (2) ◽  
pp. 20-50
Author(s):  
Maria Vargas-Vera ◽  
Miklos Nagy
Keyword(s):  
Comprehensive Evaluation ◽  
Ontology Alignment ◽  
Alignment System

This paper presents a comprehensive evaluation of DSSim (DSSim stands for Similarity based on Dempster-Shafer), our ontology alignment system. The authors participated several years in the annual evaluation defined by the Ontology Alignment Initiative (OAEI). Each year their DSSim was evolved and participated in more difficult tracks defined by the Ontology Alignment Initiative. In fact, DSSim obtained exceptional results in the OAEI-2008 Evaluation. In this evaluation (OAEI-2008), DSSim participated on all given tracks namely, benchmark, anatomy, fao, directory, mldirectory, library, very large crosslingual resources and conference. The challenges presented by each track were addressed by the DSSim team.

Ontology Alignment

2010 ◽  
Vol 1 (4) ◽  
pp. 22-40
Author(s):  
Tatyana Ivanova
Keyword(s):  
The State ◽  
Ontology Mapping ◽  
Ontology Alignment ◽  
Main Motivation ◽  
Significant Research ◽  
Component Matching ◽  
The Web ◽  
Made In

A grand number of ontologies have been developed and are publicly accessible on the Web making techniques for mapping between various ontologies more significant. Research has been made in the area of ontology alignment, a grand number of approaches, algorithms, and tools have been developed in recent years, but are still not “perfect” and excellent knowledge. In this article, the author makes an overall view of the state of ontology alignment, including the latest research, comparing many approaches, and analyzing their strengths and drawbacks. The main motivation behind this work is the fact that despite many component matching solutions that have been developed so far, there is no integrated solution that is a clear success, which can be used for ontology mapping in all cases, making knowledge about developed ontology mapping methods and their clear classification needed.

scholarly journals User validation in ontology alignment: functional assessment and impact

2019 ◽  
Vol 34 ◽  
Author(s):  
Huanyu Li ◽  
Zlatan Dragisic ◽  
Daniel Faria ◽  
Valentina Ivanova ◽  
Ernesto Jiménez-Ruiz ◽  
...  
Keyword(s):  
Ontology Alignment ◽  
Validation Process ◽  
Alignment Algorithms ◽  
Alignment System ◽  
Key Issues ◽  
Ontology Alignment Evaluation Initiative ◽  
Automated Alignment ◽  
The Impact ◽  
Current Systems

Abstract User validation is one of the challenges facing the ontology alignment community, as there are limits to the quality of the alignments produced by automated alignment algorithms. In this paper, we present a broad study on user validation of ontology alignments that encompasses three distinct but inter-related aspects: the profile of the user, the services of the alignment system, and its user interface. We discuss key issues pertaining to the alignment validation process under each of these aspects and provide an overview of how current systems address them. Finally, we use experiments from the Interactive Matching track of the Ontology Alignment Evaluation Initiative 2015–2018 to assess the impact of errors in alignment validation, and how systems cope with them as function of their services.

scholarly journals Falcon-AO++: An Improved Ontology Alignment System

2014 ◽  
Vol 94 (2) ◽  
pp. 1-7 ◽  
Author(s):  
Fatsuma Jauro ◽  
S. B. Junaidu ◽  
S. E. Abdullahi
Keyword(s):  
Ontology Alignment ◽  
Alignment System
Sign in / Sign up

Export Citation Format

Share Document