article

Discovering informative connection subgraphs in multi-relational graphs

Authors:

Cartic Ramakrishnan,

William H. Milnor,

Amit P. ShethAuthors Info & Claims

ACM SIGKDD Explorations Newsletter, Volume 7, Issue 2

Pages 56 - 63

https://doi.org/10.1145/1117454.1117462

Published: 01 December 2005 Publication History

Abstract

Discovering patterns in graphs has long been an area of interest. In most approaches to such pattern discovery either quantitative anomalies, frequency of substructure or maximum flow is used to measure the interestingness of a pattern. In this paper we introduce heuristics that guide a subgraph discovery algorithm away from banal paths towards more "informative" ones. Given an RDF graph a user might pose a question of the form: "What are the most relevant ways in which entity X is related to entity Y?" the response to which is a subgraph connecting X to Y. We use our heuristics to discover informative subgraphs within RDF graphs. Our heuristics are based on weighting mechanisms derived from edge semantics suggested by the RDF schema. We present an analysis of the quality of the subgraphs generated with respect to path ranking metrics. We then conclude presenting intuitions about which of our weighting schemes and heuristics produce higher quality subgraphs.

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Yang XProcopiuc CSrivastava D(2020)Summary graphs for relational database schemasProceedings of the VLDB Endowment10.14778/3402707.34027284:11(899-910)Online publication date: 3-Jun-2020
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Gao SKorchiev NSamatova VAnyanwu K(2020)Efficient Constrained Subgraph Extraction for Exploratory Discovery in Large Knowledge Graphs2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9378338(623-630)Online publication date: 10-Dec-2020
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Index Terms

Discovering informative connection subgraphs in multi-relational graphs
1. Computing methodologies
  1. Machine learning
2. Mathematics of computing
  1. Discrete mathematics
    1. Graph theory

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Published In

cover image ACM SIGKDD Explorations Newsletter

ACM SIGKDD Explorations Newsletter Volume 7, Issue 2

December 2005

152 pages

ISSN:1931-0145

EISSN:1931-0153

DOI:10.1145/1117454

Issue’s Table of Contents

Copyright © 2005 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 December 2005

Published in SIGKDD Volume 7, Issue 2

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Gabbolini GBridge D(2021)Generating Interesting Song-to-Song Segues With DaveProceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3450613.3456819(98-107)Online publication date: 21-Jun-2021
https://dl.acm.org/doi/10.1145/3450613.3456819
Yang XProcopiuc CSrivastava D(2020)Summary graphs for relational database schemasProceedings of the VLDB Endowment10.14778/3402707.34027284:11(899-910)Online publication date: 3-Jun-2020
https://dl.acm.org/doi/10.14778/3402707.3402728
Gao SKorchiev NSamatova VAnyanwu K(2020)Efficient Constrained Subgraph Extraction for Exploratory Discovery in Large Knowledge Graphs2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9378338(623-630)Online publication date: 10-Dec-2020
https://doi.org/10.1109/BigData50022.2020.9378338
Pirrò GKejriwal MLopez VSequeda J(2019)Building relatedness explanations from knowledge graphsSemantic Web10.3233/SW-19034810:6(963-990)Online publication date: 1-Jan-2019
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Ghazimatin ASaha Roy RWeikum GCulpepper JMoffat ABennett PLerman K(2019)FAIRYProceedings of the Twelfth ACM International Conference on Web Search and Data Mining10.1145/3289600.3290990(240-248)Online publication date: 30-Jan-2019
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Yang XAjwani DGatterbauer WNicholson PRiedewald MSala AChampin PGandon FMédini LLalmas MIpeirotis P(2018)Any-kProceedings of the 2018 World Wide Web Conference10.1145/3178876.3186115(489-498)Online publication date: 10-Apr-2018
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Jia YWang YJin XZhao ZCheng X(2017)Link Inference in Dynamic Heterogeneous Information Network: A Knapsack-Based ApproachIEEE Transactions on Computational Social Systems10.1109/TCSS.2017.27150694:3(80-92)Online publication date: Sep-2017
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Sabetghadam SLupu MRauber A(2017)Role of semantic links in performance of Information Retrieval on graph-based multimodal collections2017 Iranian Conference on Electrical Engineering (ICEE)10.1109/IranianCEE.2017.7985295(1574-1579)Online publication date: May-2017
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Koumoutsos GFasli MLewin IMilward D(2017)Graph-based information exploration over structured and unstructured data2017 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2017.8258145(1991-2000)Online publication date: Dec-2017
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