Skip to main content

Table 2 Comparison of prominence models on the global Biozon graph.

From: Hubs of knowledge: using the functional link structure in Biozon to mine for biologically significant entities

Query Term Query Type Prominence Model Average No. Neighbors Average Consistent Neighbors Average Ratio Q(R) UROC(R)
   Hubs & Authorities 4.38 0.6 0.13 167 4879
ubiquitin protein Eigenvector Centrality 4.38 0.6 0.13 167 4879
   Katz's Status 3.82 0.48 0.12 135 3436
   PageRank 12.18 3.56 0.27 977 26021
   Hubs & Authorities 1.19 0.79 0.48 357 10086
stromelysin protein Eigenvector Centrality 1.19 0.79 0.48 357 9912
   Katz's Status 1.19 0.79 0.48 357 10061
   PageRank 1.19 0.79 0.48 357 11593
   Hubs & Authorities 5.22 1.08 0.25 317 6137
cancer protein Eigenvector Centrality 5.20 0.9 0.21 245 5346
   Katz's Status 4.84 0.64 0.19 170 4915
   PageRank 6.68 1.8 0.30 535 16082
   Hubs & Authorities 1.26 0.5 0.46 166 4628
cancer nucleic Eigenvector Centrality 1.26 0.46 0.45 151 4635
   Katz's Status 1.08 0.44 0.44 146 4529
   PageRank 1.60 0.52 0.39 167 4633
   Hubs & Authorities 1.1 0.67 0.58 223 4520
autoimmune protein Eigenvector Centrality 1.1 0.67 0.58 223 4520
   Katz's Status 1.1 0.67 0.58 223 4520
   PageRank 1.1 0.67 0.58 223 4582
   Hubs & Authorities 0.98 0.4 0.4 226 4559
autoimmune nucleic Eigenvector Centrality 0.98 0.4 0.4 226 5430
   Katz's Status 0.98 0.4 0.4 226 4401
   PageRank 0.98 0.4 0.4 226 7659
  1. Only the principal eigenspace is used. For each query consisting of (query term, query type, prominence model) we report the following results over the set R of the top 50 documents returned by that query: The average number of neighbors per document in that set, the average number of consistent neighbors, the average ratio of these numbers, the quality of results set Q(R), and the most informative measure UROC(R).