Database Paper Browser

Back to papers

Neighborhood Based Fast Graph Search in Large Networks

Summary: Proposes Ness, a neighborhood-based similarity for top-k approximate subgraph/graph matching in large labeled networks, avoiding isomorphism and edit-distance. An information-propagation model embeds networks into vectors for fast indexing; robust to noise, with subgraph match NP-hard, graph similarity polynomial. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4441
Venue
SIGMOD
Year
2011
Pagerank
0.00012833377
Overall Rank
1,285 | 91.07%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 12 of 12 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 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