DocumentCode
3564645
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
fYear
2014
Firstpage
154
Lastpage
158
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Modelling and Simulation (UKSim), 2014 UKSim-AMSS 16th International Conference on
Print_ISBN
978-1-4799-4923-6
Type
conf
DOI
10.1109/UKSim.2014.48
Filename
7046055
Link To Document