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AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
Newman, M. Finding community structure in networks using the eigenvectors of matrices 2006 Physical Review E   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   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   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.   article DOIURL  
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   article DOIURL  
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   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   inproceedings DOIURL  
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.   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   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   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   inproceedings DOIURL  
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 The Semantic Web: Research and Applications   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 Graph-Theoretic Concepts in Computer Science   incollection DOIURL  
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   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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