AUTOMATED SUPPORT FOR A COLLABORATIVE SYSTEM TO ORGANIZE A COLLECTION USING FACETS

We are developing a system that improves access to a large, growing image collec-tion by supporting users to collaboratively build a faceted (multi-perspective) clas-sification schema. For collections that grow in both volume and variety, a major challenge is to evolve the facet schema, and to reclassify existing objects into the modified facet schema. Centrally managed classification systems often find it diffi-cult to adapt to evolving collections. The proposed system allows: (a) users to col-laboratively build and maintain a faceted classification, (b) to systematically enrich the user-created facet schema, and (c) to automatically classify documents into an evolving, user-managed facet schema. In this paper, we focus on (c), where we de-scribe the approach to automatically classify documents into an evolving facet schema. We propose a learning-based system that periodically learns from manu-ally classified images, and then classify new images accordingly