Calendar-Based Relevance Boosting

Abstract

Information retrieval systems have become a more central component in modern Software Engineering. It is hence important to improve the models that determine relevance, both concerning what data is used and how to use the data, particularly to support more personalized systems. Among the multiplicity of models to determine relevance, contextbased search aims to improve the relevance of retrieved information by considering in what context a search is being carried out. This study evaluates how improved search relevance can be achieved by considering the context of the calendar. Hence, a model concept was constructed, implemented in a typical enterprise search environment and furthermore evaluated using statistical testing. The results showed a statistically significant improvement on the search relevance using keyword matching. Nevertheless, temporal methods of determining context had no significant impact on the search relevance. Future works include evaluation of the concept in an authentic environment to determine concept applicability.