Title :
Influence Discovery in Semantic Networks: An Initial Approach
Author :
Trovati, Marcello ; Bagdasar, Ovidiu
Author_Institution :
Sch. of Comput. & Math., Univ. of Derby, Derby, UK
Abstract :
Assessing the influence between concepts, which include people, physical objects, as well as theoretical ideas, plays a crucial role in understanding and discovering knowledge. Despite the huge amount of literature on knowledge discovery in semantic networks, there has been little attempt to fully classify and investigate the influence, which also includes causality, of a semantic entity on another one as dynamical entities. In this paper we will introduce an approach to discover and assess influence among nodes in a semantic network, with the aim to provide a tool to identify its type and direction. Even though this is still being developed, the preliminary evaluation shows promising and interesting results.
Keywords :
causality; data mining; semantic networks; causality; influence discovery; knowledge discovery; knowledge understanding; semantic entity; semantic networks; Computational modeling; Educational institutions; Equations; Mathematical model; Semantics; Social network services; Algorithms; Knowledge Discovery; Knowledge Representations; Knowledge acquisition; Semantics;
Conference_Titel :
Computer Modelling and Simulation (UKSim), 2014 UKSim-AMSS 16th International Conference on
Print_ISBN :
978-1-4799-4923-6
DOI :
10.1109/UKSim.2014.48