Tagging is a common Web 2.0 practice which allows users to collaboratively classify or evaluate the objects of an Information Space with the aim of improving object search, browse, and consumption. In this work, we focus on the problem of "classification tagging" over Information Spaces of objects stored in an Apache Solr full-text index. In such 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 classification tagging tools which allow them to "bulk" tag or untag sets of objects in temporary work sessions, where they can in "real-time" experiment the effect of their actions before making the changes visible to end-users. The implementation of such tools over Solr Information Spaces is a challenge, since bulk object updates in Solr are far from being real-time and in critical cases may slow down index performance. To solve these issues, we devised TagTick, a tool which offers to data curators a fully functional classification tagging environment. At its core, TagTick integrates the "tag virtualizer" module, which extends the APIs of Solr to support real-time, virtual, bulk-(un)tagging functionalities.

TagTick: tool for classification tagging of metadata records

Manghi P;Artini M;Atzori C;Bardi A;La Bruzzo S
2012

Abstract

Tagging is a common Web 2.0 practice which allows users to collaboratively classify or evaluate the objects of an Information Space with the aim of improving object search, browse, and consumption. In this work, we focus on the problem of "classification tagging" over Information Spaces of objects stored in an Apache Solr full-text index. In such 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 classification tagging tools which allow them to "bulk" tag or untag sets of objects in temporary work sessions, where they can in "real-time" experiment the effect of their actions before making the changes visible to end-users. The implementation of such tools over Solr Information Spaces is a challenge, since bulk object updates in Solr are far from being real-time and in critical cases may slow down index performance. To solve these issues, we devised TagTick, a tool which offers to data curators a fully functional classification tagging environment. At its core, TagTick integrates the "tag virtualizer" module, which extends the APIs of Solr to support real-time, virtual, bulk-(un)tagging functionalities.
2012
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Tagging
SOLR
Lucene
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/178057
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