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Personalizing the GAMS Cross-Index

By Saverio Perugini, Priya Lakshminarayanan and Naren Ramakrishnan

Abstract

The NIST Guide to Available Mathematical Software (GAMS)system at http://gams.nist.gov serves as the gateway to thousands of scientific codes and modules for numerical com-putation.We describe the PIPE personalization facility for GAMS,whereby content from the cross-index is specialized for a user desiring software recommendations for a specific problem instance.The key idea is to (i)mine structure,and (ii)exploit it in a programmatic manner to generate personalized web pages.Our approach supports both content based and collaborative personalization and enables information integration from multiple (and complementary)web resources.We present case studies for the domain of linear,second-order,elliptic partial differential equations that indicate strong empirical evidence for the usefulness of our semi-automatic approach

Topics: Artificial Intelligence
Year: 2000
OAI identifier: oai:vtcstechreports.OAI2:557

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