Database Paper Browser

Back to papers

Building Hierarchical Classifiers Using Class Proximity

Summary: Proposes class proximity to measure closeness in hierarchical classification, replacing local-split models with a global classifier. Employs generalized association rules as the feature space to encode relations for proximity-aware flat classification. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8581
Venue
VLDB
Year
1999
Pagerank
9.0304462e-05
Overall Rank
2,325 | 83.83%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers