Lu, WZ; Janssen, J; Milios, E; Japkowicz, N; Zhang, YZ "Node similarity in the citation graph" Knowledge and Information Systems 11(1):105-129 Jan 2007

[Eugene Garfield]

E-mail: eem at cs.dal.ca

TITLE:          Node similarity in the citation graph (Article, English)

AUTHOR:         Lu, WZ; Janssen, J; Milios, E; Japkowicz, N; Zhang, YZ

SOURCE:         KNOWLEDGE AND INFORMATION SYSTEMS 11 (1). JAN 2007.
                p.105-129 SPRINGER LONDON LTD, GODALMING

ABSTRACT:       Published scientific articles are linked together into a
graph, the citation graph, through their citations. This paper explores the 
notion of similarity based on connectivity alone, and proposes several 
algorithms to quantify it. Our metrics take advantage of the local 
neighborhoods of the nodes in the citation graph. Two variants of link-
based similarity estimation between two nodes are described, one based on 
the separate local neighborhoods of the nodes, and another based on the 
joint local neighborhood expanded from both nodes at the same time. The 
algorithms are implemented and evaluated on a subgraph of the citation 
graph of computer science in a retrieval context. The results are compared 
with text-based similarity, and demonstrate the complementarity of link-
based and text-based retrieval.

AUTHOR ADDRESS: E Milios, Dalhousie Univ, Fac Comp Sci, 6050 Univ Ave,
                Halifax, NS B3H 1W5, Canada