Search Results

Documents authored by Huo, Hongwei

Document
Research
DOI: 10.4230/OASIcs.Grossi.1
An Efficient Heuristic for Graph Edit Distance

Authors: Xiaoyang Chen, Yujia Wang, Hongwei Huo, and Jeffrey Scott Vitter

Published in: OASIcs, Volume 132, From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday (2025)

Abstract
The graph edit distance (GED) is a flexible distance measure widely used in many applications. Existing GED computation methods are usually based upon the tree-based search algorithm that explores all possible vertex (or edge) mappings between two compared graphs. During this process, various GED lower bounds are adopted as heuristic estimations to accelerate the tree-based search algorithm. For the first time, we analyze the relationship among three state-of-the-art GED lower bounds, label edit distance (LED), Hausdorff edit distance (HED), and branch edit distance (BED). Specifically, we demonstrate that BED(G, Q) ≥ HED(G, Q) and BED(G, Q) ≥ LED(G, Q) for any two undirected graphs G and Q. Furthermore, for BED we propose an efficient heuristic BED^+ for improving the tree-based search algorithm. Extensive experiments on real and synthetic datasets confirm that BED^+ achieves smaller deviation and larger solvable ratios than LED, HED and BED when they are employed as heuristic estimations. The source code is available online.
Cite as

Xiaoyang Chen, Yujia Wang, Hongwei Huo, and Jeffrey Scott Vitter. An Efficient Heuristic for Graph Edit Distance. In From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 132, pp. 1:1-1:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{chen_et_al:OASIcs.Grossi.1,
  author =	{Chen, Xiaoyang and Wang, Yujia and Huo, Hongwei and Vitter, Jeffrey Scott},
  title =	{{An Efficient Heuristic for Graph Edit Distance}},
  booktitle =	{From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday},
  pages =	{1:1--1:18},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-391-1},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{132},
  editor =	{Conte, Alessio and Marino, Andrea and Rosone, Giovanna and Vitter, Jeffrey Scott},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Grossi.1},
  URN =		{urn:nbn:de:0030-drops-238004},
  doi =		{10.4230/OASIcs.Grossi.1},
  annote =	{Keywords: Graph edit distance, Label edit distance, Hausdorff edit distance, Branch edit distance, Tree-based search, Heuristics}
}
Document
DOI: 10.4230/OASIcs.Manzini.5
FM-Adaptive: A Practical Data-Aware FM-Index

Authors: Hongwei Huo, Zongtao He, Pengfei Liu, and Jeffrey Scott Vitter

Published in: OASIcs, Volume 131, The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday (2025)

Abstract
The FM-index provides an important solution for efficient retrieval and search in textual big data. Its variants have been widely used in many fields including information retrieval, genome analysis, and web searching. In this paper, we propose improvements via a new compressed representation of the wavelet tree of the Burrows-Wheeler transform of the input text, which incorporates the gap γ-encoding. Our theoretical analysis shows that the new index, called FM-Adaptive, achieves asymptotic space optimality within a factor of 2 in the leading term, but it has a better compression and faster retrieval in practice than the competitive optimal compression boosting used in previous FM-indexes. We present a practical improved locate algorithm that provides substantially faster locating time based upon memoization, which takes advantage of the overlapping subproblems property. We design the lookup table for accelerated decoding to support fast pattern matching in a text. Extensive experiments demonstrate that FM-Adaptive provides faster query performance, often by a considerable amount, and/or comparable or better compression than other state-of-the-art FM-index methods.
Cite as

Hongwei Huo, Zongtao He, Pengfei Liu, and Jeffrey Scott Vitter. FM-Adaptive: A Practical Data-Aware FM-Index. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 5:1-5:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{huo_et_al:OASIcs.Manzini.5,
  author =	{Huo, Hongwei and He, Zongtao and Liu, Pengfei and Vitter, Jeffrey Scott},
  title =	{{FM-Adaptive: A Practical Data-Aware FM-Index}},
  booktitle =	{The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday},
  pages =	{5:1--5:23},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-390-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{131},
  editor =	{Ferragina, Paolo and Gagie, Travis and Navarro, Gonzalo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Manzini.5},
  URN =		{urn:nbn:de:0030-drops-239139},
  doi =		{10.4230/OASIcs.Manzini.5},
  annote =	{Keywords: Text indexing, Burrows-Wheeler transform, Compressed wavelet trees, Entropy-compressed, Compressed data structures}
}
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact