Any-k: Anytime Top-k Tree Pattern Retrieval in Labeled Graphs

Proceedings of the ... International World-Wide Web Conference
Xiaofeng YangAlessandra Sala

Abstract

Many problems in areas as diverse as recommendation systems, social network analysis, semantic search, and distributed root cause analysis can be modeled as pattern search on labeled graphs (also called "heterogeneous information networks" or HINs). Given a large graph and a query pattern with node and edge label constraints, a fundamental challenge is to find the top-k matches according to a ranking function over edge and node weights. For users, it is difficult to select value k. We therefore propose the novel notion of an any-k ranking algorithm: for a given time budget, return as many of the top-ranked results as possible. Then, given additional time, produce the next lower-ranked results quickly as well. It can be stopped anytime, but may have to continue until all results are returned. This paper focuses on acyclic patterns over arbitrary labeled graphs. We are interested in practical algorithms that effectively exploit (1) properties of heterogeneous networks, in particular selective constraints on labels, and (2) that the users often explore only a fraction of the top-ranked results. Our solution, KARPET, carefully integrates aggressive pruning that leverages the acyclic nature of the query, and incremental guided searc...Continue Reading

Citations

Mar 16, 2021·Proceedings of the VLDB Endowment·Nikolaos TziavelisXiaofeng Yang
Apr 13, 2018··Wolfgang GatterbauerDeepak Ajwani

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Software Mentioned

VF2
KARPET
OpenStack
QuickSI
Unguided
NEXTPREORDER
PTIME
CandEdge
CandNode
GraphEdge

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