A Methodology for the Automatic Creation of Massive Continuous Query Datasets from Real Life Corpora

摘要

In the information filtering (or publish/ subscribe) paradigm, clients subscribe to a server withcontinuous queries that express their information needs while information sources publishdocuments to servers. Whenever a document is published, the continuous queries satisfying thisdocument are found and notifications are sent to appropriate subscribed clients. Althoughinformation filtering has been in the research agenda for about half a century, there is a hugeparadox when it comes to benchmarking the performance of such systems. There is a strikinglack of a benchmarking mechanism (in the form of a large-scale standarised test collection ofcontinuous queries and the relevant document publications) specifically created for evaluatingfiltering tasks. This work aims at filling this gap by proposing a methodology for automaticallycreating massive continuous query datasets from available document collections. We intend topublicly release all related material (including the software accompanying the proposedmethodology) to the research community after publication.