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Big graph mining for the web and social media

U. Kang, Leman Akoglu, Duen Horng Chau
2014 Proceedings of the 7th ACM international conference on Web search and data mining - WSDM '14  
We start with important graph algorithms that are central to graph mining and pattern discoveries, including graphbased anomaly detection techniques (complement of pattern discoveries) that are playing  ...  What are the patterns and anomalies in such massive graphs? How to design scalable algorithms to find them? What visual analytics techniques to use to make sense of such massive graphs?  ...  Her research interests are in data mining, machine learning, and applied statistics with a focus on pattern mining, and anomaly and event detection in large dynamic data using graph mining and compression  ... 
doi:10.1145/2556195.2556198 dblp:conf/wsdm/KangAC14 fatcat:fbe7ciirlzd3xm42h3y67bw77i

Big graph mining

U. Kang, Christos Faloutsos
2013 SIGKDD Explorations  
How do we find patterns and anomalies in very large graphs with billions of nodes and edges? How to mine such big graphs efficiently?  ...  Mining big graphs leads to many interesting applications including cyber security, fraud detection, Web search, recommendation, and many more.  ...  Due to the simplicity, scalability, and fault tolerance, big graph mining using Hadoop attracted significant attentions in research community [41; 3; 23; 17].  ... 
doi:10.1145/2481244.2481249 fatcat:fzidqzmctndj3nxh2qw55txyuu

Compressing Graph Data by Leveraging Domain Independent Knowledge

Dr. Sirisha Velampalli
2021 Proceedings of the ... International Florida Artificial Intelligence Research Society Conference  
We compare CRADLE with baseline approaches.Our proposed approach is comparable in compressionrate, search space, and runtimes to other well-knowngraph mining approaches.  ...  Graphs are used to solve many problems in the real world.At the same time size of the graphs presents a complexscenario to analyze essential information that they contain.Graph compression is used to understand  ...  We compare CRADLE with well-known graph mining approaches. Related Work Discovering interesting substructures in a structural database improves the ability to interpret and compress the data.  ... 
doi:10.32473/flairs.v34i1.128573 fatcat:vqypra6k2nbgzhlvdfg635wk54

Frequent pattern mining: current status and future directions

Jiawei Han, Hong Cheng, Dong Xin, Xifeng Yan
2007 Data mining and knowledge discovery  
However, there are still some challenging research issues that need to be solved before frequent pattern mining can claim a cornerstone approach in data mining applications.  ...  Frequent pattern mining has been a focused theme in data mining research for over a decade.  ...  Zhu et al. (2007) investigated a novel mining approach, called Pattern-Fusion, to efficiently find a good approximation to colossal patterns.  ... 
doi:10.1007/s10618-006-0059-1 fatcat:fpblaafhurfbtiimurret4idde

A distributed placement service for graph-structured and tree-structured data

Gregory Buehrer, Srinivasan Parthasarathy, Shirish Tatikonda
2010 Proceedings of the 15th ACM SIGPLAN symposium on Principles and practice of parallel programming - PPoPP '10  
Target applications include the placement of a single large graph (e.g. Web graph), a single large tree (e.g. large XML file), a forest of graphs or trees (e.g.  ...  We empirically evaluate our service by demonstrating its use in improving mining executions for pattern discovery, nearest neighbor searching, graph computations, and applications that combine link and  ...  Preliminary Results Distributed Placement and Compression of the Web Graph: We consider a large web graph dataset (EU2005) with approximately one million nodes and 14 million edges, and evaluate the  ... 
doi:10.1145/1693453.1693511 dblp:conf/ppopp/BuehrerPT10 fatcat:yyr4yybalfbujatqyqcgew4zou

Research Challenges for Data Mining in Science and Engineering [chapter]

Jiawei Han, Jing Gao
2008 Chapman & Hall/CRC Data Mining and Knowledge Discovery Series  
In this paper, we discuss the research challenges in science and engineering, from the data mining perspective, with a focus on the following issues: (1) information network analysis, (2) discovery, usage  ...  , and understanding of patterns and knowledge, (3) stream data mining, (4) mining moving object data, RFID data, and data from sensor networks, (5) spatiotemporal and multimedia data mining, (6) mining  ...  Recently, studies have proceeded to scalable methods for mining colossal patterns [35] where the size of the patterns could be rather large so that the step-by-step growth using an Apriori-like approach  ... 
doi:10.1201/9781420085877.pt1 fatcat:ljs2uybdofgkxfpouawfekdaz4

Scalable Compression of a Weighted Graph [article]

Kifayat Ullah Khan, Waqas Nawaz, Young-Koo Lee
2016 arXiv   pre-print
Therefore, this paper presents a scalable compression solution to compute summary of a weighted graph.  ...  Therefore, creating a summary graph while considering this vital aspect is necessary to learn insights of different communication patterns.  ...  We find that clustering a graph helps to learn its overall charactertics [5] . However, it does not reduce size of a graph for efficient execution of various graph mining operations.  ... 
arXiv:1611.03159v1 fatcat:jjlke7hzifcale7en7mrvuw5jm

Partition based Graph Compression

Meera Dhabu, Dr. P., Siyaram Vishwakarma
2013 International Journal of Advanced Computer Science and Applications  
Also with the current size of main memory it seems impossible to load the whole graph into main memory. Hence the need of graph compression techniques arises.  ...  Graphs are used in diverse set of disciplines ranging from computer networks to biological networks, social networks, World Wide Web etc.  ...  Other contemporary research works mine the Web graph to find dense bipartite cliques, and through them Web communities [16] and link spam [05] .  ... 
doi:10.14569/ijacsa.2013.040902 fatcat:p5yx4ldtzndbdpcbqieggvxfsq


Carlos H. C. Teixeira, Alexandre J. Fonseca, Marco Serafini, Georgos Siganos, Mohammed J. Zaki, Ashraf Aboulnaga
2015 Proceedings of the 25th Symposium on Operating Systems Principles - SOSP '15  
Currently a PhD student at the Federal University of Minas Gerais, Brazil.  ...  Teixeira would like to thank CNPq, Fapemig and Inweb for the travel support to attend the conference.  ...  Acknowledgments We would like to thank Landon Cox for shepherding the paper, the SOSP reviewers for their valuable feedback, Ehab Abdelhamid for the GRAMI implementation, Nilothpal Talukder for some of  ... 
doi:10.1145/2815400.2815410 dblp:conf/sosp/TeixeiraFSSZA15 fatcat:y532l5fke5cbjknyzeaofqkjui

Graph-based data mining

D.J. Cook, L.B. Holder
2000 IEEE Intelligent Systems and their Applications  
Scalability A barrier to integrating scientific discovery into practical data-mining approaches is that discovery systems lack scalability.  ...  Unlike other approaches to finding patterns in gene data, 11 Subdue uses a graph to represent structural information in the sequence.  ... 
doi:10.1109/5254.850825 fatcat:uhmbej7osncgndxkc7rbyvvtmi

Compressed representations for web and social graphs

Cecilia Hernández, Gonzalo Navarro
2013 Knowledge and Information Systems  
Compressed representations have become effective to store and access large Web and social graphs, in order to support various graph querying and mining tasks.  ...  With this approach, we match the best current compression ratios that support out-neighbor queries (i.e., nodes pointed from a given node), using 1.0-1.8 bits per edge (bpe) on large Web graphs, and retrieving  ...  We refer to this approach as dense subgraph mining (DSM).  ... 
doi:10.1007/s10115-013-0648-4 fatcat:zt4zdfp42bdrdgmcwws3cr6qsy

Logical Linked Data Compression [chapter]

Amit Krishna Joshi, Pascal Hitzler, Guozhu Dong
2013 Lecture Notes in Computer Science  
Unlike other compression techniques, our approach not only takes advantage of syntactic verbosity and data redundancy but also utilizes semantic associations present in the RDF graph.  ...  In this study, we introduce a novel lossless compression technique for RDF datasets, called Rule Based Compression (RB Compression) that compresses datasets by generating a set of new logical rules from  ...  [4] explored pattern mining based compression schemes for web graphs specifically designed to accomodate community queries.  ... 
doi:10.1007/978-3-642-38288-8_12 fatcat:zk4ec4omarffhos36jn7qee2na

Arabesque: A System for Distributed Graph Mining - Extended version [article]

Carlos H. C. Teixeira, Alexandre J. Fonseca, Marco Serafini, Georgos Siganos, Mohammed J. Zaki, Ashraf Aboulnaga
2015 arXiv   pre-print
It defines a high-level filter-process computational model that simplifies the development of scalable graph mining algorithms: Arabesque explores subgraphs and passes them to the application, which must  ...  We use Arabesque's API to produce distributed solutions to three fundamental graph mining problems: frequent subgraph mining, counting motifs, and finding cliques.  ...  Teixeira would like to thank CNPq, Fapemig and Inweb for the travel support to attend the conference.  ... 
arXiv:1510.04233v1 fatcat:774mihqn4najngl7p3xsqqr7w4

Summarizing and understanding large graphs

Danai Koutra, U Kang, Jilles Vreeken, Christos Faloutsos
2015 Statistical analysis and data mining  
To this end, we first mine candidate subgraphs using one or more graph partitioning algorithms.  ...  How can we succinctly describe a million-node graph with a few simple sentences?  ...  ACKNOWLEDGMENTS The authors would like to thank Niki Kittur and Jeffrey Rzeszotarski for sharing the Wikipedia datasets.  ... 
doi:10.1002/sam.11267 fatcat:okiu65f65beo7kjvl2ogm6v47a

Anomaly Extraction and Mitigation using Efficient-Web Miner Algorithm

Gargi Joshi, A. K. Bongale
2014 International Journal of Computer Applications  
Frequent pattern mining technique namely Efficient-Web Miner Algorithm will be used to generate the set of association rules applied on metadata.  ...  Using network traffic log data, algorithms effectively finds the flow associated with the anomalous event(s). Efficient-Web Miner Algorithm triggers a very small number of false positives.  ...  Figure 4 Performance graph of proposed E Web Miner Algorithm 4) Due to better efficiency of E-Web miner algorithm, it is proved to be scalable in comparison with Apriori All algorithm.  ... 
doi:10.5120/17495-8024 fatcat:sxoegbt57jarvagclg6ncjhx7i
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