The dynamics of collective sorting robot-like ants and ant-like robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Diversity and adaptation in populations of clustering ants
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
ACM Computing Surveys (CSUR)
Improved Ant-Based Clustering and Sorting
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Learning ontologies from natural language texts
International Journal of Human-Computer Studies
Ant-Based Clustering and Topographic Mapping
Artificial Life
Measuring data-driven ontology changes using text mining
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
| Hi-index | 0.00 |
Besides being difficult to scale between different domains and to handle knowledge fluctuations, the results of terms clustering presented by existing ontology engineering systems are far from desirable. In this paper, we propose a new version of ant-based method for clustering terms known as Tree-Traversing Ants (TTA). With the help of the Normalized Google Distance (NGD) and n° of Wikipedia (n°W) as measures for similarity and distance between terms, we attempt to achieve an adaptable clustering method that is highly scalable across domains. Initial experiments with two datasets show promising results and demonstrated several advantages that are not simultaneously present in standard ant-based and other conventional clustering methods.