Document Type
Report
Date
11-14-1994
Keywords
Neural networks, Document allocation, Hopfield Network, Multiprocessor, Information retrieval
Language
English
Disciplines
Computer Sciences
Description/Abstract
We consider the problem of distributing the documents to a given set of processors so that the load on each processor is as equal as possible and the amount of communication is as small as possible. This is an NP-Complete problem. We apply continuous as well as discrete Hopfield neural networks to obtain suboptimal solutions for the problem. These networks perform better than a genetic algorithm for this task proposed by Frieder et al. [4]; in particular, the continuous Hopfield network performs extremely well.
Recommended Citation
Al-Sehibani, Abdulaziz Sultan; Mehrotra, Kishan; Mohan, Chilukuri K.; and Ranka, Sanjay, "Multiprocessor Document Allocation: a Neural Network Approach" (1994). Electrical Engineering and Computer Science - Technical Reports. 151.
https://surface.syr.edu/eecs_techreports/151
Source
local
Additional Information
School of Computer and Information Science, Syracuse University, SU-CIS-94-08