Digital library query clearing using clustering and fuzzy decision-making

A method is proposed and analysed for servicing keyword queries expressed in a digital library. Efficiency in the service routine is introduced via the concept of customers and producer. From the customer perspective, queries are grouped into clusters of similar concepts. The action of the servicing digital library is then formulated in terms of the amount of overlap each cluster of queries has with respect to the information density of the library. Furthermore, the concept of query priorities is incorporated within the formulation of the initial query clusters. The ensuing combination of prioritised query clustering and fuzzy decision-making is shown to ensure that the prioritised query instances receive preferential service times without increasing the query queue length or delay times.