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    AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
    Newman, M. Finding community structure in networks using the eigenvectors of matrices 2006 Physical Review E
    Vol. 74(3), pp. 36104 
    article  
    BibTeX:
    @article{newman2006fcs,
      author = {Newman, MEJ},
      title = {Finding community structure in networks using the eigenvectors of matrices},
      journal = {Physical Review E},
      publisher = {APS},
      year = {2006},
      volume = {74},
      number = {3},
      pages = {36104}
    }
    
    Chung, F.R.K. Spectral Graph Theory 1997   book  
    BibTeX:
    @book{Chung:1997,
      author = {Chung, F. R. K.},
      title = {Spectral Graph Theory},
      publisher = {American Mathematical Society},
      year = {1997}
    }
    
    Monien, B. On Spectral Bounds for the k-Partitioning of Graphs 2001   misc  
    BibTeX:
    @misc{Monien_onspectral,
      author = {Monien, B.},
      title = {On Spectral Bounds for the k-Partitioning of Graphs},
      year = {2001}
    }
    
    Mohar, B. The Laplacian spectrum of graphs 1991 Graph Theory, Combinatorics, and Applications
    Vol. 2, pp. 871-898 
    article  
    BibTeX:
    @article{mohar1991lsg,
      author = {Mohar, B.},
      title = {The Laplacian spectrum of graphs},
      journal = {Graph Theory, Combinatorics, and Applications},
      publisher = {New York: Wiley},
      year = {1991},
      volume = {2},
      pages = {871--898}
    }
    
    Spielman, D. Spectral Graph Theory and its Applications 2007 Foundations of Computer Science, 2007. FOCS '07. 48th Annual IEEE Symposium on, pp. 29-38  article DOI  
    Abstract: Spectral graph theory is the study of the eigenvalues and eigenvectors of matrices associated with graphs. In this tutorial, we will try to provide some intuition as to why these eigenvectors and eigenvalues have combinatorial significance, and will sitn'ey some of their applications.
    BibTeX:
    @article{4389477,
      author = {Spielman, D.A.},
      title = {Spectral Graph Theory and its Applications},
      journal = {Foundations of Computer Science, 2007. FOCS '07. 48th Annual IEEE Symposium on},
      year = {2007},
      pages = {29-38},
      doi = {http://dx.doi.org/10.1109/FOCS.2007.56}
    }
    
    Johnson, D.S. & Papadimitriou, C.H. On generating all maximal independent sets 1988 Inf. Process. Lett.
    Vol. 27(3), pp. 119-123 
    article DOI URL 
    BibTeX:
    @article{46243,
      author = {Johnson, David S. and Papadimitriou, Christos H.},
      title = {On generating all maximal independent sets},
      journal = {Inf. Process. Lett.},
      publisher = {Elsevier North-Holland, Inc.},
      year = {1988},
      volume = {27},
      number = {3},
      pages = {119--123},
      url = {http://portal.acm.org/citation.cfm?id=46241.46243},
      doi = {http://dx.doi.org/10.1016/0020-0190(88)90065-8}
    }
    
    Dias, V.M., de Figueiredo, C.M. & Szwarcfiter, J.L. Generating bicliques of a graph in lexicographic order 2005 Theoretical Computer Science
    Vol. 337(1-3), pp. 240 - 248 
    article DOI URL 
    Abstract: An independent set of a graph is a subset of pairwise non-adjacent vertices. A complete bipartite set B is a subset of vertices admitting a bipartition B=X[union or logical sum]Y, such that both X and Y are independent sets, and all vertices of X are adjacent to those of Y. If both X,Y[not equal to][empty set], then B is called proper. A biclique is a maximal proper complete bipartite set of a graph. We present an algorithm that generates all bicliques of a graph in lexicographic order, with polynomial-time delay between the output of two successive bicliques. We also show that there is no polynomial-time delay algorithm for generating all bicliques in reverse lexicographic order, unless P=NP. The methods are based on those by Johnson, Papadimitriou and Yannakakis, in the solution of these two problems for independent sets, instead of bicliques.
    BibTeX:
    @article{Dias2005240,
      author = {Dias, Vânia M.F. and de Figueiredo, Celina M.H. and Szwarcfiter, Jayme L.},
      title = {Generating bicliques of a graph in lexicographic order},
      journal = {Theoretical Computer Science},
      year = {2005},
      volume = {337},
      number = {1-3},
      pages = {240 - 248},
      url = {http://www.sciencedirect.com/science/article/B6V1G-4FD0HTT-3/2/7efa1ee4d7b4823c7315a58b94f2f280},
      doi = {DOI: 10.1016/j.tcs.2005.01.014}
    }
    
    Fiedler, M. A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory 1975 Czechoslovak Mathematical Journal
    Vol. 25(100), pp. 619-633 
    article  
    BibTeX:
    @article{fiedler1975pen,
      author = {Fiedler, M.},
      title = {A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory},
      journal = {Czechoslovak Mathematical Journal},
      year = {1975},
      volume = {25},
      number = {100},
      pages = {619--633}
    }
    
    Haveliwala, T. & Kamvar, S. The second eigenvalue of the Google matrix 2003 A Stanford University Technical Report http://dbpubs. stanford. edu  article  
    BibTeX:
    @article{haveliwala8090seg,
      author = {Haveliwala, T.H. and Kamvar, S.D.},
      title = {The second eigenvalue of the Google matrix},
      journal = {A Stanford University Technical Report http://dbpubs. stanford. edu},
      year = {2003}
    }
    
    Dhillon, I.S. Co-clustering documents and words using bipartite spectral graph partitioning 2001 KDD '01: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 269-274  inproceedings DOI URL 
    BibTeX:
    @inproceedings{coclustering01,
      author = {Dhillon, Inderjit S.},
      title = {Co-clustering documents and words using bipartite spectral graph partitioning},
      booktitle = {KDD '01: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining},
      publisher = {ACM Press},
      year = {2001},
      pages = {269--274},
      url = {http://portal.acm.org/citation.cfm?id=502512.502550},
      doi = {http://dx.doi.org/10.1145/502512.502550}
    }
    
    Blelloch, G. Graph Separators 2002   unpublished  
    BibTeX:
    @unpublished{graphseparators02,
      author = {Blelloch, Guy},
      title = {Graph Separators},
      year = {2002}
    }
    
    Pothen, A., Simon, H. & Liou, K. Partitioning Sparse Matrices with Eigenvectors of Graphs 1990 SIAM J. MATRIX ANAL. APPLIC.
    Vol. 11(3), pp. 430-452 
    article URL 
    BibTeX:
    @article{partitioning89,
      author = {Pothen, A. and Simon, H.D. and Liou, K.P.},
      title = {Partitioning Sparse Matrices with Eigenvectors of Graphs},
      journal = {SIAM J. MATRIX ANAL. APPLIC.},
      year = {1990},
      volume = {11},
      number = {3},
      pages = {430--452},
      url = {http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19970011963_1997016998.pdf }
    }
    
    Chan, P.K., Schlag, M.D.F. & Zien, J.Y. Spectral K-way ratio-cut partitioning and clustering. 1994 IEEE Trans. on CAD of Integrated Circuits and Systems
    Vol. 13(9), pp. 1088-1096 
    article URL 
    BibTeX:
    @article{journals/tcad/ChanSZ94,
      author = {Chan, Pak K. and Schlag, Martine D. F. and Zien, Jason Y.},
      title = {Spectral K-way ratio-cut partitioning and clustering.},
      journal = {IEEE Trans. on CAD of Integrated Circuits and Systems},
      year = {1994},
      volume = {13},
      number = {9},
      pages = {1088-1096},
      url = {http://dblp.uni-trier.de/db/journals/tcad/tcad13.html#ChanSZ94}
    }
    
    Yu, S.X. & Shi, J. Multiclass Spectral Clustering 2003 Proc. International Conference on Computer Vision (ICCV 03)  inproceedings  
    BibTeX:
    @inproceedings{yu2003multiclass,
      author = {Yu, Stella X. and Shi, Jianbo},
      title = {Multiclass Spectral Clustering},
      booktitle = {Proc. International Conference on Computer Vision (ICCV 03)},
      year = {2003}
    }
    
    Hagen, L.W. & Kahng, A.B. New spectral methods for ratio cut partitioning and clustering. 1992 IEEE Trans. on CAD of Integrated Circuits and Systems
    Vol. 11(9), pp. 1074-1085 
    article URL 
    BibTeX:
    @article{journals/tcad/HagenK92,
      author = {Hagen, Lars W. and Kahng, Andrew B.},
      title = {New spectral methods for ratio cut partitioning and clustering.},
      journal = {IEEE Trans. on CAD of Integrated Circuits and Systems},
      year = {1992},
      volume = {11},
      number = {9},
      pages = {1074-1085},
      url = {http://dblp.uni-trier.de/db/journals/tcad/tcad11.html#HagenK92}
    }
    
    Symeonidis, P., Nanopoulos, A. & Manolopoulos, Y. Tag recommendations based on tensor dimensionality reduction 2008 RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems, pp. 43-50  inproceedings DOI URL 
    BibTeX:
    @inproceedings{1454017,
      author = {Symeonidis, Panagiotis and Nanopoulos, Alexandros and Manolopoulos, Yannis},
      title = {Tag recommendations based on tensor dimensionality reduction},
      booktitle = {RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems},
      publisher = {ACM},
      year = {2008},
      pages = {43--50},
      url = {http://portal.acm.org/citation.cfm?id=1454017},
      doi = {http://doi.acm.org/10.1145/1454008.1454017}
    }
    
    Ranade, A. Some uses of spectral methods 2000   unpublished  
    BibTeX:
    @unpublished{ranade:sus,
      author = {Ranade, A.G.},
      title = {Some uses of spectral methods},
      year = {2000}
    }
    
    Schmitz, C., Hotho, A., Jäschke, R. & Stumme, G. Content Aggregation on Knowledge Bases using Graph Clustering 2006
    Vol. 4011The Semantic Web: Research and Applications, pp. 530-544 
    inproceedings URL 
    Abstract: Recently, research projects such as PADLR and SWAP
    have developed tools like Edutella or Bibster, which are targeted at
    establishing peer-to-peer knowledge management (P2PKM) systems. In
    such a system, it is necessary to obtain provide brief semantic
    descriptions of peers, so that routing algorithms or matchmaking
    processes can make decisions about which communities peers should
    belong to, or to which peers a given query should be forwarded.
    This paper provides a graph clustering technique on
    knowledge bases for that purpose. Using this clustering, we can show
    that our strategy requires up to 58% fewer queries than the
    baselines to yield full recall in a bibliographic P2PKM scenario.
    BibTeX:
    @inproceedings{schmitz2006content,
      author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
      title = {Content Aggregation on Knowledge Bases using Graph Clustering},
      booktitle = {The Semantic Web: Research and Applications},
      publisher = {Springer},
      year = {2006},
      volume = {4011},
      pages = {530-544},
      url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006content.pdf}
    }
    
    Brandes, U., Delling, D., Gaertler, M., Görke, R., Hoefer, M., Nikoloski, Z. & Wagner, D. On Finding Graph Clusterings with Maximum Modularity 2007
    Vol. 4769Graph-Theoretic Concepts in Computer Science, pp. 121-132 
    incollection DOI URL 
    Abstract: Modularity is a recently introduced quality measure for graph clusterings. It has immediately received considerable attention in several disciplines, and in particular in the complex systems literature, although its properties are not well understood. We study the problem of finding clusterings with maximum modularity, thus providing theoretical foundations for past and present work based on this measure. More precisely, we prove the conjectured hardness of maximizing modularity both in the general case and with the restriction to cuts, and give an Integer Linear Programming formulation. This is complemented by first insights into the behavior and performance of the commonly applied greedy agglomaration approach.
    BibTeX:
    @incollection{springerlink:10.1007/978-3-540-74839-7_12,
      author = {Brandes, Ulrik and Delling, Daniel and Gaertler, Marco and Görke, Robert and Hoefer, Martin and Nikoloski, Zoran and Wagner, Dorothea},
      title = {On Finding Graph Clusterings with Maximum Modularity},
      booktitle = {Graph-Theoretic Concepts in Computer Science},
      publisher = {Springer},
      year = {2007},
      volume = {4769},
      pages = {121-132},
      url = {http://dx.doi.org/10.1007/978-3-540-74839-7_12},
      doi = {http://dx.doi.org/10.1007/978-3-540-74839-7_12}
    }
    
    Diestel, R. Graph Theory 2005 , pp. I-XVI, 1-344  book URL 
    BibTeX:
    @book{diestel2006graphentheorie,
      author = {Diestel, Reinhard},
      title = {Graph Theory},
      publisher = {Springer-Verlag Heidelberg, New York},
      year = {2005},
      pages = {I-XVI, 1-344},
      edition = {3 (electronic edition)},
      url = {http://www.math.ubc.ca/~solymosi/2007/443/GraphTheoryIII.pdf}
    }
    

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