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A Venturi Effect Can Help Cure Our Trees
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Any-k: Anytime Top-k Tree Pattern Retrieval in Labeled Graphs.

Xiaofeng Yang1, Patrick K Nicholson2, Deepak Ajwani3

  • 1Northeastern University, Boston, MA.

Proceedings of the ... International World-Wide Web Conference. International WWW Conference
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PubMed
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Finding top results in large labeled graphs is challenging. This study introduces an any-k ranking algorithm that efficiently returns as many top-ranked results as possible within a given time budget, improving pattern search in heterogeneous information networks.

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Area of Science:

  • Computer Science
  • Data Mining
  • Graph Theory

Background:

  • Pattern search on labeled graphs, also known as heterogeneous information networks (HINs), is crucial for applications like recommendation systems and semantic search.
  • A key challenge is efficiently finding top-k matches based on node and edge weights, especially when the value of 'k' is difficult for users to determine.

Purpose of the Study:

  • To propose a novel "any-k ranking algorithm" that returns top-ranked results incrementally within a specified time budget.
  • To develop a practical algorithm for pattern search on acyclic patterns in arbitrary labeled graphs that leverages HIN properties and user exploration behavior.

Main Methods:

  • The KARPET algorithm integrates aggressive pruning, utilizing the acyclic nature of query patterns.
  • It employs an incremental guided search strategy to efficiently discover and rank results.
  • The method focuses on exploiting selective label constraints inherent in heterogeneous networks.

Main Results:

  • KARPET provides strong, non-trivial time and space guarantees for graph search problems.
  • The algorithm achieves millisecond running times for tree patterns on large networks with millions of nodes and edges.
  • Experimental studies validate the efficiency and effectiveness of the proposed approach.

Conclusions:

  • The any-k ranking approach addresses the user's difficulty in selecting 'k' by providing flexible result retrieval.
  • KARPET offers a practical and efficient solution for pattern search in heterogeneous information networks, particularly for acyclic patterns.
  • The algorithm's performance demonstrates its suitability for large-scale graph analysis tasks.