Featureless similarities for terms clustering using tree-traversing ants
|Featureless similarities for terms clustering using tree-traversing ants|
|Author(s)||Wong W., Liu W., Bennamoun M.|
|Published in||ACM International Conference Proceeding Series|
|Keyword(s)||ant-based clustering method, featureless similarity measures, terms clustering (Extra: Ant-based clustering, Clustering methods, Conventional clustering, Data sets, Different domains, Normalized Google distances, Ontology engineering, Similarity measure, Wikipedia, Knowledge engineering, Natural language processing systems, Ontology, Cluster analysis)|
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Featureless similarities for terms clustering using tree-traversing ants is a 2006 conference paper written in English by Wong W., Liu W., Bennamoun M. and published in ACM International Conference Proceeding Series.
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. Copyright
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