4,327 Hits in 3.9 sec

Finding Motifs in Knowledge Graphs using Compression [article]

Peter Bloem
2021 arXiv   pre-print
We introduce a method to find network motifs in knowledge graphs. Network motifs are useful patterns or meaningful subunits of the graph that recur frequently.  ...  Specifically, we show that in random graphs, no motifs are found, and that when we insert a motif artificially, it can be detected.  ...  In this paper, we extend this compression-based motif analysis to knowledge graphs. For the purposes of this research we define knowledge graphs as labeled, directed multigraphs.  ... 
arXiv:2104.08163v1 fatcat:qk3tpyuwlfagvcidwjpjxe7oiq

Large-scale network motif analysis using compression [article]

Peter Bloem, Steven de Rooij
2019 arXiv   pre-print
We introduce a new method for finding network motifs: interesting or informative subgraph patterns in a network.  ...  Subgraphs are motifs when their frequency in the data is high compared to the expected frequency under a null model.  ...  Since a graph can, in principle, be compressed with only a very small number of instances of a given motif, this gives us a very scalable method to find motifs in large data.  ... 
arXiv:1701.02026v3 fatcat:mgrse5y4ojg5bftghc7z6vsube

Large-scale network motif analysis using compression

Peter Bloem, Steven de Rooij
2020 Data mining and knowledge discovery  
We introduce a new method for finding network motifs. Subgraphs are motifs when their frequency in the data is high compared to the expected frequency under a null model.  ...  We use ideas from the minimum description length literature to define a new measure of motif relevance. With our method, samples from the null model are not required.  ...  Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long  ... 
doi:10.1007/s10618-020-00691-y fatcat:ze2fwwj7r5epliorxnjqju6vve

FCA in a Logical Programming Setting for Visualization-Oriented Graph Compression [chapter]

Lucas Bourneuf, Jacques Nicolas
2017 Lecture Notes in Computer Science  
Royer et al. introduced in 2008 Power graph analysis, a dedicated program using classes of nodes with similar properties and classes of edges linking node classes to achieve a lossless graph compression  ...  Exploring potentially interesting substructures (clusters, motifs) within such graphs requires proper abstraction and visualization methods.  ...  Théret (Inserm) for providing us the networks used in the results section. We would also like to express our gratitude to the reviewers for their feedbacks.  ... 
doi:10.1007/978-3-319-59271-8_6 fatcat:j7dhxcnpnjc63apn3fqeahi66e

Anomaly Detection in Large Labeled Multi-Graph Databases [article]

Hung T. Nguyen, Pierre J. Liang, Leman Akoglu
2022 arXiv   pre-print
., node-labeled network motifs) that losslessly compress database G as concisely as possible. Graphs that do not compress well are flagged as anomalous.  ...  CODETECT exhibits two novel building blocks: (i) a motif-based lossless graph encoding scheme, and (ii) fast memory-efficient search algorithms for S.  ...  Any conclusions expressed in this material are those of the author and do not necessarily reflect the views, expressed or implied, of the funding parties.  ... 
arXiv:2010.03600v2 fatcat:u7tqcw7ek5bjfag26f6lfzj2jy

GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning [article]

Sixing Yu, Arya Mazaheri, Ali Jannesari
2021 arXiv   pre-print
In this paper, we propose a novel multi-stage graph embedding technique based on graph neural networks (GNNs) to identify the DNNs' topology and use reinforcement learning (RL) to find a suitable compression  ...  We performed resource-constrained (i.e., FLOPs) channel pruning and compared our approach with state-of-the-art compression methods using over-parameterized DNNs (e.g., ResNet and VGG-16) and mobile-friendly  ...  Among such methods, network pruning has shown to be considerably useful in model compression by introducing sparsity or eliminating channels or filters, yet requires extensive knowledge and effort to find  ... 
arXiv:2102.03214v1 fatcat:dls3bhpvlfd3rlmh45emmvtue4

Motion-Motif Graphs [article]

Philippe Beaudoin, Stelian Coros, Michiel Van De Panne, Pierre Poulin
2008 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation - SCA '04  
They can be used in support of motion compression, the removal of redundant motions, and the creation of blend spaces.  ...  This paper develops a string-based motif-finding algorithm which allows for a user-controlled compromise between motif length and the number of motions in a motif.  ...  Acknowledgements This work was supported in part by grants from NSERC and FQRNT. The data used in this project was obtained from  ... 
doi:10.2312/sca/sca08/117-126 fatcat:kubwod74ezf4bdcy3adp2runtu

Rigid Graph Compression: Motif-Based Rigidity Analysis for Disordered Fiber Networks

Samuel Heroy, Dane Taylor, F. Bill Shi, M. Gregory Forest, Peter J. Mucha
2018 Multiscale Modeling & simulation  
To address some of these challenges, we use the graph theoretic property of rigidity to model mechanical reinforcement in composites with stiff rod-like particles.  ...  We develop an efficient algorithmic approach called rigid graph compression (RGC) to describe the transition from floppy to rigid in disordered fiber networks ("rod-hinge systems"), which form the reinforcing  ...  In general, iterative graph compression of two intersecting motifs might achieve different final states if different orderings of motif compression are used.  ... 
doi:10.1137/17m1157271 pmid:30450018 pmcid:PMC6234004 fatcat:uvwq5wzgnbhh7ajgx6mrlbsv3u

Structure induction by lossless graph compression

Leonid Peshkin
2007 2007 Data Compression Conference (DCC'07)  
A novel algorithm, dubbed Graphitour, for structure induction by lossless graph compression is presented and illustrated by a clear and broadly known case of nested structure in a DNA molecule.  ...  The algorithm accepts a variety of graph types including directed graphs and graphs with labeled nodes and arcs. The resulting structure could be used for representation and classification of graphs.  ...  Alon et al. find that much of the network could be composed of repeated appearances of three highly significant motifs, that is a sub-graph, of a fixed topology, in which nodes are instantiated with different  ... 
doi:10.1109/dcc.2007.73 dblp:conf/dcc/Peshkin07 fatcat:xxdp6dvkf5fihbr3ux5im4v34m

Efficient community detection using power graph analysis

George Tsatsaronis, Matthias Reimann, Iraklis Varlamis, Orestis Gkorgkas, Kjetil Nørvåg
2011 Proceedings of the 9th workshop on Large-scale and distributed informational retrieval - LSDS-IR '11  
Motivated by this analogy, we apply the Power Graph Analysis methodology, for the first time to the best of our knowledge, to the field of community mining.  ...  The advances in the field of community mining allow us to experiment with widely accepted benchmark data sets, and our results show that the suggested methodology performs favorably against state of the  ...  The analysis is based on identifying re-occurring network motifs using several abstractions. The three basic motifs recognized by Power Graphs are shown in Figure 1 (c).  ... 
doi:10.1145/2064730.2064738 fatcat:2l3gba24urhk7muaccmjbcdltu

Towards Unambiguous Edge Bundling: Investigating Confluent Drawings for Network Visualization

Benjamin Bach, Nathalie Henry Riche, Christophe Hurter, Kim Marriott, Tim Dwyer
2017 IEEE Transactions on Visualization and Computer Graphics  
Finally, we present the first user study that compares edge compression techniques, including CD, power-graphs, metro-style, and common edge bundling.  ...  Abstract-In this paper, we investigate Confluent Drawings (CD), a technique for bundling edges in node-link diagrams based on network connectivity.  ...  Our research aims at expanding this knowledge for practical use of CD in network visualization.  ... 
doi:10.1109/tvcg.2016.2598958 pmid:27875170 fatcat:ynle6litc5bupf7hlwsymxrcnm

How to Become a Group Leader? or Modeling Author Types Based on Graph Mining [chapter]

George Tsatsaronis, Iraklis Varlamis, Sunna Torge, Matthias Reimann, Kjetil Nørvåg, Michael Schroeder, Matthias Zschunke
2011 Lecture Notes in Computer Science  
The representation and visualization of bibliographic databases as graphs and the application of data mining techniques can help us uncover interesting knowledge regarding how the publication records of  ...  In this paper we propose a novel methodology to model bibliographical databases as Power Graphs, and mine them in an unsupervised manner, in order to learn basic author types and their properties through  ...  The analysis is based on identifying re-occurring network motifs using several abstractions. The three basic motifs recognized by Power Graphs are shown in Figure 2 .  ... 
doi:10.1007/978-3-642-24469-8_4 fatcat:h4ufkkcktfhv3ijhhds462wdye

A hybrid approach for efficient provenance storage

Yulai Xie, Dan Feng, Zhipeng Tan, Lei Chen, Kiran-Kumar Muniswamy-Reddy, Yan Li, Darrell D.E. Long
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
Our evaluation indicates that our hybrid scheme, a combination of web graph compression (adapted for provenance) and dictionary encoding, provides the best tradeoff in terms of compression ratio, compression  ...  We then propose a hybrid scheme that takes advantage of the graph structure of provenance data and the inherent duplication in provenance data.  ...  The web graph compression algorithm allows us to compress provenance while still satisfying the characteristics we observed.  ... 
doi:10.1145/2396761.2398511 dblp:conf/cikm/XieFTCMLL12 fatcat:r5lose7ryfe3rjzwt7luhruo24

Graph Summarization Methods and Applications: A Survey [article]

Yike Liu, Tara Safavi, Abhilash Dighe, Danai Koutra
2018 arXiv   pre-print
Finally, we discuss applications of summarization on real-world graphs and conclude by describing some open problems in the field.  ...  In particular, while data summarization techniques have been studied extensively, only recently has summarizing interconnected data, or graphs, become popular.  ...  In these cases, although compression is the means, finding the absolutely smallest representation of the graph is not the end goal.  ... 
arXiv:1612.04883v3 fatcat:fhg2g5eldfdgfkzoqdmbfl5er4

A Method for Evaluating Options for Motif Detection in Electricity Meter Data

Ian Dent, Tony Craig, Uwe Aickelin, Tom Rodden
2021 Journal of Data Science  
Using UK data collected from several hundred households in Spring 2011 monitored at a frequency of five minutes, a process for finding repeating short patterns (motifs) is defined.  ...  This paper addresses the question as to whether a reasonable number of meaningful motifs, that each represent a regular activity within a domestic household, can be identified solely using the household  ...  Evaluation of Different Techniques The approach to finding motifs detailed above makes use of a number of parameters such as the type of motif to use (compressed, normalised, etc.), the size of alphabet  ... 
doi:10.6339/jds.201801_16(1).0001 fatcat:x4jybd2rs5azbltvpe6qwgu45i
« Previous Showing results 1 — 15 out of 4,327 results