Authors: Guang Hong Wang, Ping Jiang
Addresses: Department of Information and Control Engineering, Tongji University, Shanghai 200092, China. ' Department of Information and Control Engineering, Tongji University, Shanghai 200092, China'Department of Cybernetics and Virtual Systems, University of Bradford, Bradford, BD7 1DP, UK
Abstract: Asymmetric HNN designed as an associative memory for query expansion has been researched in some papers. However, there is no criterion in this method to measure its validity and to tell good results from bad ones objectively. What|s more, convergence characteristic of HNNs may not be guaranteed if the symmetry is broken. Aiming at avoiding these two points, maximum mutual information (informax) principle-based query expansion using symmetric HNNs is proposed from the perspective of combinatorial optimisation.
Keywords: informax principle; query expansion; asymmetric associative model; Hopfield neural networks; combinatorial optimisation; automatic learning; real time.
International Journal of Intelligent Systems Technologies and Applications, 2007 Vol.2 No.2/3, pp.219 - 230
Published online: 19 Feb 2007 *Full-text access for editors Access for subscribers Purchase this article Comment on this article