Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On bicluster aggregation and its benefits for enumerative solutions   Biclustering involves the simultaneous clustering of objects and their
attributes, thus defining local two-way clustering models. Recently, efficient
algorithms were conceived to enumerate all biclusters in real-valued datasets.
In this case, the solution composes a complete set of maximal and non-redundant
biclusters. However, the ability to enumerate biclusters revealed a challenging
scenario: in noisy datasets, each true bicluster may become highly fragmented
and with a high degree of overlapping. It prevents a direct analysis of the
obtained results. To revert the fragmentation, we propose here two approaches
for properly aggregating the whole set of enumerated biclusters: one based on
single linkage and the other directly exploring the rate of overlapping. Both
proposals were compared with each other and with the actual state-of-the-art in
several experiments, and they not only significantly reduced the number of
biclusters but also consistently increased the quality of the solution.

8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
2
The categories of this paper are: math
3
The categories of this paper are: physics
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
20
The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga