Title :
A study of data fusion in Cayley graphs G(sn,pn)
Author :
Hsu, D. Frank ; Palumbo, Andrew
Author_Institution :
Dept. of Comput. & Inf. Sci., Fordham Univ., New York, NY, USA
Abstract :
In this paper, we examine a method for the fusion of ranked data in the context of a Cayley graph. We investigate this Cayley graph model for optimization of fusion by rank combination. We outline a method of data fusion by combination of weighted rankings. Information systems are represented as nodes in a Cayley graph. Our goal is to determine a metric of diversity and performance in this graph in order to build a model for optimizing fusion by rank combination. We use the Kendall distance between nodes in the Cayley graph of the symmetric group Sn as a measure of performance. In doing so we demonstrate that in S6 there is a quadratic relationship between the weights of the fusion of two information systems and the performance of the fusion in our abstract space. From such a relationship we propose a set of functions for extrapolating optimal fusion weights in the symmetric group Sn.
Keywords :
graph theory; information retrieval systems; merging; optimisation; sensor fusion; Cayley graphs; Kendall distance; fusion optimization; information systems; rank combination; ranked data fusion; Character generation; Diversity reception; Information retrieval; Information science; Information systems; Solid modeling; Tin;
Conference_Titel :
Parallel Architectures, Algorithms and Networks, 2004. Proceedings. 7th International Symposium on
Print_ISBN :
0-7695-2135-5
DOI :
10.1109/ISPAN.2004.1300537