Mining Tree-Structured Data on Multicore Systems

Summary: Architecture-conscious mining of frequent subtrees in rooted, labeled trees for multicore systems. Memory locality optimizations, reduced bus pressure, and adaptive moldable-task scheduling enable efficient parallelization up to 16 cores and a general scheduling service. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 9975
Venue: VLDB
Year: 2009
Pagerank: 4.6512834e-05
Overall Rank: 7,771 | 46.00%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Shirish Tatikonda
2. Srinivasan Parthasarathy

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
1,522	Efficient Subgraph Matching: Harmonizing Dynamic Programming, Adaptive Matching Order, and Failing Set Together	2019	SIGMOD	0.0001152219
12,274	Ten Thousand SQLs: Parallel Keyword Queries Computing	2010	VLDB	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
182	Mining Frequent Patterns without Candidate Generation	2000	SIGMOD	0.00036955562
826	Main-Memory Scan Sharing For Multi-Core CPUs	2008	VLDB	0.00016161625
8,374	LCS-TRIM: Dynamic Programming Meets XML Indexing and Querying	2007	VLDB	4.5282277e-05

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