Exploring Citation Networks with Hybrid Tree Pattern Queries

Document Type

Conference Proceeding

Publication Date

1-1-2020

Abstract

Scientific impact of publications is often measured using citation networks. However, traditional measures typically rely on direct citations only. To fully leverage citation networks for assessing scientific impact, it is necessary to investigate also indirect scientific influence, which is captured by citation paths. Further, the analysis and exploration of citation networks requires the ability to efficiently evaluate expressive queries on them. In this paper, we propose to use hybrid query patterns to query citation networks. These allow for both edge-to-edge and edge-to-path mappings between the query pattern and the graph, thus being able to extract both direct and indirect relationships. To efficiently evaluate hybrid pattern queries on citation graphs, we employ a pattern matching algorithm which exploits graph simulation to prune nodes that do not appear in the final answer. Our experimental results on citation networks show that our method not only allows for more expressive queries but is also efficient and scalable.

Identifier

85090094877 (Scopus)

ISBN

[9783030558130]

Publication Title

Communications in Computer and Information Science

External Full Text Location

https://doi.org/10.1007/978-3-030-55814-7_26

e-ISSN

18650937

ISSN

18650929

First Page

311

Last Page

322

Volume

1260 CCIS

Grant

61872276

Fund Ref

National Natural Science Foundation of China

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