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- W20174551 abstract "Local structures have become frequent through Web 2.0: Users tag their data without specifying the underlying semantics. Ev- ery user annotates items in an individual way using the own labels. Even if two users happen to use a with the same name, it need not mean the same. Moreover, within the collection of a single user, media items are tagged multiply using dierent aspects, e.g., topic, genre, occasion, mood. Again, several users applying the same name for an aspect does not imply that actually the same aspect is meant. Nevertheless, users could benefit from the tagging work of others (folk- sonomies). The set of items clustered together by the same label in one user's collection form a pattern. Knowing this pattern is informative for another user. In contrast to other cluster ensemble methods or dis- tributed clustering, a global model (consensus) is not the aim. Each user wants to keep the tags already annotated, wants to keep the diverse as- pects under which the items were organized, and only wishes to enhance the own structure by those of others. A clustering algorithm which struc- tures items has to take into account the local, multi-aspect nature of the task structures. The LACE algorithm (9) is such a clustering algorithm." @default.
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- W20174551 date "2007-01-01" @default.
- W20174551 modified "2023-09-23" @default.
- W20174551 title "Multi-Aspect Tagging for Collaborative Structuring" @default.
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