Enhancing digital libraries using missing content analysis

Abstract

This work shows how the content of a digital library can be enhanced to better satisfy its users' needs. Missing content is identified by finding missing content topics in the system's query log or in a pre-defined taxonomy of required knowledge. The collection is then enhanced with new relevant knowledge, which is extracted from external sources that satisfy those missing content topics. Experiments we conducted measure the precision of the system before and after content enhancement. The results demonstrate a significant improvement in the system effectiveness as a result of content enhancement and the superiority of the missing content enhancement policy over several other possible policies. Copyright 2008 ACM.