Uncovering Interesting Attributed Anomalies in Large Graphs

[1]  Tong Zhang,et al.  Linear prediction models with graph regularization for web-page categorization , 2006, KDD '06.

[2]  Jorge Nocedal,et al.  On the limited memory BFGS method for large scale optimization , 1989, Math. Program..

[3]  Hong Cheng,et al.  A model-based approach to attributed graph clustering , 2012, SIGMOD Conference.

[4]  Dániel Fogaras,et al.  Towards Scaling Fully Personalized PageRank: Algorithms, Lower Bounds, and Experiments , 2005, Internet Math..

[5]  Nan Li,et al.  Neighborhood based fast graph search in large networks , 2011, SIGMOD '11.

[6]  Desheng Dash Wu,et al.  Using text mining and sentiment analysis for online forums hotspot detection and forecast , 2010, Decis. Support Syst..

[7]  Charu C. Aggarwal,et al.  On Node Classification in Dynamic Content-based Networks , 2011, SDM.

[8]  Jiawei Han,et al.  gIceberg: Towards iceberg analysis in large graphs , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).

[9]  Deepayan Chakrabarti,et al.  AutoPart: Parameter-Free Graph Partitioning and Outlier Detection , 2004, PKDD.

[10]  Daniel Gildea,et al.  Convergence of the EM Algorithm for Gaussian Mixtures with Unbalanced Mixing Coefficients , 2012, ICML.

[11]  Vagelis Hristidis,et al.  Keyword proximity search on XML graphs , 2003, Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405).

[12]  Xiaowei Xu,et al.  SCAN: a structural clustering algorithm for networks , 2007, KDD '07.

[13]  Graham Cormode,et al.  Applying Link-Based Classification to Label Blogs , 2007, WebKDD/SNA-KDD.

[14]  Cristina G. Fernandes,et al.  Motif Search in Graphs: Application to Metabolic Networks , 2006, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[15]  Türkay Dereli,et al.  PROJECT TEAM SELECTION USING FUZZY OPTIMIZATION APPROACH , 2007, Cybern. Syst..

[16]  Philip S. Yu,et al.  BLINKS: ranked keyword searches on graphs , 2007, SIGMOD '07.

[17]  Piotr Indyk,et al.  Enhanced hypertext categorization using hyperlinks , 1998, SIGMOD '98.

[18]  J. Tenenbaum,et al.  A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.

[19]  Haim H. Permuter,et al.  A study of Gaussian mixture models of color and texture features for image classification and segmentation , 2006, Pattern Recognit..

[20]  Jeff A. Bilmes,et al.  A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models , 1998 .

[21]  Rajeev Motwani,et al.  Computing Iceberg Queries Efficiently , 1998, VLDB.

[22]  Mining Attribute-structure Correlated Patterns in Large Attributed Graphs , 2012, Proc. VLDB Endow..

[23]  Hong Cheng,et al.  Graph Clustering Based on Structural/Attribute Similarities , 2009, Proc. VLDB Endow..

[24]  Thorsten Joachims,et al.  Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.

[25]  Christos Faloutsos,et al.  R-MAT: A Recursive Model for Graph Mining , 2004, SDM.

[26]  Bernhard Schölkopf,et al.  Learning with Local and Global Consistency , 2003, NIPS.

[27]  Aditya Bhaskara,et al.  Detecting high log-densities: an O(n¼) approximation for densest k-subgraph , 2010, STOC '10.

[28]  K. Rose Deterministic annealing for clustering, compression, classification, regression, and related optimization problems , 1998, Proc. IEEE.

[29]  Jennifer Widom,et al.  Scaling personalized web search , 2003, WWW '03.

[30]  Jure Leskovec,et al.  Latent Multi-group Membership Graph Model , 2012, ICML.

[31]  Wentian Li,et al.  Random texts exhibit Zipf's-law-like word frequency distribution , 1992, IEEE Trans. Inf. Theory.

[32]  Eleazar Eskin,et al.  Anomaly Detection over Noisy Data using Learned Probability Distributions , 2000, ICML.

[33]  C. Lee Giles,et al.  CiteSeer: an automatic citation indexing system , 1998, DL '98.

[34]  S. Sudarshan,et al.  Bidirectional Expansion For Keyword Search on Graph Databases , 2005, VLDB.

[35]  Luis Gravano,et al.  Evaluating top-k queries over web-accessible databases , 2004, TODS.

[36]  Zhen Wen,et al.  Density index and proximity search in large graphs , 2012, CIKM '12.

[37]  Pavel Berkhin,et al.  Bookmark-Coloring Algorithm for Personalized PageRank Computing , 2006, Internet Math..

[38]  Purnamrita Sarkar,et al.  Fast incremental proximity search in large graphs , 2008, ICML '08.

[39]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[40]  Raghu Ramakrishnan,et al.  Bottom-up computation of sparse and Iceberg CUBE , 1999, SIGMOD '99.

[41]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.

[42]  Jignesh M. Patel,et al.  Efficient aggregation for graph summarization , 2008, SIGMOD Conference.

[43]  Beng Chin Ooi,et al.  EASE: an effective 3-in-1 keyword search method for unstructured, semi-structured and structured data , 2008, SIGMOD Conference.

[44]  Kiyoko F. Aoki-Kinoshita,et al.  A new efficient probabilistic model for mining labeled ordered trees applied to glycobiology , 2008, TKDD.

[45]  Kurt Mehlhorn,et al.  LEDA: a platform for combinatorial and geometric computing , 1997, CACM.

[46]  Lise Getoor,et al.  Link-Based Classification , 2003, Encyclopedia of Machine Learning and Data Mining.

[47]  A team formation model based on knowledge and collaboration , 2009, IEEE Engineering Management Review.

[48]  Hongyuan Zha,et al.  Probabilistic models for discovering e-communities , 2006, WWW '06.

[49]  Foster J. Provost,et al.  Classification in Networked Data: a Toolkit and a Univariate Case Study , 2007, J. Mach. Learn. Res..

[50]  Yufei Tao,et al.  Querying Communities in Relational Databases , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[51]  Michael J. Carey,et al.  On saying “Enough already!” in SQL , 1997, SIGMOD '97.

[52]  Diane J. Cook,et al.  Graph-based anomaly detection , 2003, KDD '03.

[53]  Yiming Yang,et al.  An Evaluation of Statistical Approaches to Text Categorization , 1999, Information Retrieval.

[54]  Aijun An,et al.  Keyword Search in Graphs: Finding r-cliques , 2011, Proc. VLDB Endow..

[55]  Purnamrita Sarkar,et al.  Fast nearest-neighbor search in disk-resident graphs , 2010, KDD.

[56]  Charu C. Aggarwal,et al.  On supervised mining of dynamic content‐based networks 1 , 2012, Stat. Anal. Data Min..

[57]  Kun-Lung Wu,et al.  Towards proximity pattern mining in large graphs , 2010, SIGMOD Conference.

[58]  Luo Si,et al.  Adjusting Mixture Weights of Gaussian Mixture Model via Regularized Probabilistic Latent Semantic Analysis , 2005, PAKDD.

[59]  Taku Kudo,et al.  Clustering graphs by weighted substructure mining , 2006, ICML.

[60]  Sariel Har-Peled,et al.  Fast Algorithms for Computing the Smallest k-Enclosing Circle , 2004, Algorithmica.

[61]  Jiawei Han,et al.  Star-Cubing: Computing Iceberg Cubes by Top-Down and Bottom-Up Integration , 2003, Very Large Data Bases Conference.

[62]  Jiawei Han,et al.  gSpan: graph-based substructure pattern mining , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

[63]  Ben Taskar,et al.  Discriminative Probabilistic Models for Relational Data , 2002, UAI.

[64]  Joachim M. Buhmann,et al.  Multi-assignment clustering for Boolean data , 2009, ICML '09.

[65]  Ihab F. Ilyas,et al.  A survey of top-k query processing techniques in relational database systems , 2008, CSUR.

[66]  Minas Gjoka,et al.  Walking in Facebook: A Case Study of Unbiased Sampling of OSNs , 2010, 2010 Proceedings IEEE INFOCOM.

[67]  Theodoros Lappas,et al.  Finding a team of experts in social networks , 2009, KDD.

[68]  Martin Ester,et al.  Mining Cohesive Patterns from Graphs with Feature Vectors , 2009, SDM.

[69]  Christos Faloutsos,et al.  oddball: Spotting Anomalies in Weighted Graphs , 2010, PAKDD.

[70]  Atish Das Sarma,et al.  Multi-skill Collaborative Teams based on Densest Subgraphs , 2011, SDM.

[71]  William W. Cohen,et al.  On the collective classification of email "speech acts" , 2005, SIGIR '05.

[72]  Pang-Ning Tan,et al.  Outrank: a Graph-Based Outlier Detection Framework Using Random Walk , 2008, Int. J. Artif. Intell. Tools.

[73]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[74]  Andrei Z. Broder,et al.  Graph structure in the Web , 2000, Comput. Networks.

[75]  Jennifer Neville,et al.  Randomization tests for distinguishing social influence and homophily effects , 2010, WWW '10.

[76]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[77]  Massimo Franceschet,et al.  PageRank , 2010, Commun. ACM.

[78]  Deng Cai,et al.  Topic modeling with network regularization , 2008, WWW.

[79]  W. Hoeffding Probability Inequalities for sums of Bounded Random Variables , 1963 .

[80]  Shang-Hua Teng,et al.  A Local Clustering Algorithm for Massive Graphs and Its Application to Nearly Linear Time Graph Partitioning , 2008, SIAM J. Comput..

[81]  ARMEN Zzkarian,et al.  Forming teams: an analytical approach , 1999 .

[82]  Heiga Zen,et al.  Deterministic Annealing EM Algorithm in Acoustic Modeling for Speaker and Speech Recognition , 2005, IEICE Trans. Inf. Syst..

[83]  Fan Chung Graham,et al.  Local Partitioning for Directed Graphs Using PageRank , 2007, Internet Math..

[84]  Nan Li,et al.  Cross-Selling Optimization for Customized Promotion , 2010, SDM.

[85]  E. David,et al.  Networks, Crowds, and Markets: Reasoning about a Highly Connected World , 2010 .

[86]  Ben Taskar,et al.  Learning Probabilistic Models of Link Structure , 2003, J. Mach. Learn. Res..

[87]  Riccardo Dondi,et al.  Finding Approximate and Constrained Motifs in Graphs , 2011, CPM.

[88]  Jeffrey Scott Vitter,et al.  Random sampling with a reservoir , 1985, TOMS.

[89]  Seung-won Hwang,et al.  Minimal probing: supporting expensive predicates for top-k queries , 2002, SIGMOD '02.

[90]  Philip S. Yu,et al.  Graph OLAP: a multi-dimensional framework for graph data analysis , 2009, Knowledge and Information Systems.

[91]  Bernhard Schölkopf,et al.  Learning from labeled and unlabeled data on a directed graph , 2005, ICML.

[92]  Jimeng Sun,et al.  Neighborhood formation and anomaly detection in bipartite graphs , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

[93]  S. Chib,et al.  Understanding the Metropolis-Hastings Algorithm , 1995 .

[94]  Sebastian Thrun,et al.  Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.

[95]  David A. Bader,et al.  A Graph-Theoretic Analysis of the Human Protein-Interaction Network Using Multicore Parallel Algorithms , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

[96]  Soumen Chakrabarti,et al.  Fast algorithms for topk personalized pagerank queries , 2008, WWW.

[97]  S. Sudarshan,et al.  Keyword searching and browsing in databases using BANKS , 2002, Proceedings 18th International Conference on Data Engineering.

[98]  Kenichi Kurihara,et al.  Graph Mining with Variational Dirichlet Process Mixture Models , 2008, SDM.

[99]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[100]  Samir Khuller,et al.  On Finding Dense Subgraphs , 2009, ICALP.

[101]  Michalis Faloutsos,et al.  On power-law relationships of the Internet topology , 1999, SIGCOMM '99.

[102]  Chao Wang,et al.  Network Environment and Financial Risk Using Machine Learning and Sentiment Analysis , 2009 .

[103]  Alok Aggarwal,et al.  Finding k Points with Minimum Diameter and Related Problems , 1991, J. Algorithms.

[104]  Ashish Goel,et al.  Fast Incremental and Personalized PageRank , 2010, Proc. VLDB Endow..

[105]  Jiawei Han,et al.  Top-K aggregation queries over large networks , 2010, 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010).