Resumen de High-performance annotation tagging over solr full-text indexes
Paolo Manghi, Michele Artini, Alessia Bardi, Claudio Atzori, Sandro La Bruzzo
In this work, we focus on the problem of �annotation tagging� over Information Spaces of objects stored in a full-text index. In such a scenario, tags are assigned to objects by �data curator� users with the purpose of classification, while generic end-users will perceive tags as searchable and browsable object properties. To carry out their activities, data curators need �annotation tagging tools� which allow them to �bulk� tag or untag large sets of objects in temporary work sessions, where they can �virtually� and in �real-time� experiment the effect of their actions before making the changes visible to end-users. The implementation of these tools over full-text indexes is a challenge, since bulk object updates in this context are far from being real-time and in critical cases may slow down index performance. We devised TagTick, a tool which offers to data curators a fully functional annotation tagging environment over the full-text index Apache Solr, regarded as a �de-facto standard� in this area. TagTick consists of a TagTick Virtualizer module, which extends the APIs of Solr to support real-time, virtual, bulk-tagging operations, and a TagTick User Interface module, which offers end-user functionalities for annotation tagging. The tool scales optimally with the number and size of bulk tag operations, without compromising index performance.
