Publications
Tag recommendations based on tensor dimensionality reduction
Symeonidis, P.; Nanopoulos, A. & Manolopoulos, Y.
, 'RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems', ACM, New York, NY, USA, [http://doi.acm.org/10.1145/1454008.1454017], 43-50 (2008) [pdf]
On Finding Graph Clusterings with Maximum Modularity
Brandes, U.; Delling, D.; Gaertler, M.; Görke, R.; Hoefer, M.; Nikoloski, Z. & Wagner, D.
Brandstädt, A.; Kratsch, D. & Müller, H., ed., 'Graph-Theoretic Concepts in Computer Science', 4769(), Springer, Berlin / Heidelberg, 121-132 (2007) [pdf]
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.
Spectral Graph Theory and its Applications
Spielman, D.
Foundations of Computer Science, 2007. FOCS '07. 48th Annual IEEE Symposium on 29-38 (2007)
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.
Finding community structure in networks using the eigenvectors of matrices
Newman, M.
Physical Review E, 74(3) 36104 (2006)
Content Aggregation on Knowledge Bases using Graph Clustering
Schmitz, C.; Hotho, A.; Jäschke, R. & Stumme, G.
Sure, Y. & Domingue, J., ed., 'The Semantic Web: Research and Applications', 4011(), LNAI, Springer, Heidelberg, 530-544 (2006) [pdf]
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.
Generating bicliques of a graph in lexicographic order
Dias, V. M.; de Figueiredo, C. M. & Szwarcfiter, J. L.
Theoretical Computer Science, 337(1-3) 240 - 248 (2005) [pdf]
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.
Graph Theory
Diestel, R.
2005, Springer-Verlag Heidelberg, New York [pdf]
The second eigenvalue of the Google matrix
Haveliwala, T. & Kamvar, S.
A Stanford University Technical Report http://dbpubs. stanford. edu (2003)
Multiclass Spectral Clustering
Yu, S. X. & Shi, J.
, 'Proc. International Conference on Computer Vision (ICCV 03)', Nice, France (2003)
Graph Separators
Blelloch, G.
(2002)
Co-clustering documents and words using bipartite spectral graph partitioning
Dhillon, I. S.
, 'KDD '01: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining', ACM Press, New York, NY, USA, [10.1145/502512.502550], 269-274 (2001) [pdf]
On Spectral Bounds for the k-Partitioning of Graphs
Monien, B.
(2001)
Some uses of spectral methods
Ranade, A.
(2000)
Spectral Graph Theory
Chung, F. R. K.
1997, American Mathematical Society
Spectral K-way ratio-cut partitioning and clustering.
Chan, P. K.; Schlag, M. D. F. & Zien, J. Y.
IEEE Trans. on CAD of Integrated Circuits and Systems, 13(9) 1088-1096 (1994) [pdf]
New spectral methods for ratio cut partitioning and clustering.
Hagen, L. W. & Kahng, A. B.
IEEE Trans. on CAD of Integrated Circuits and Systems, 11(9) 1074-1085 (1992) [pdf]
The Laplacian spectrum of graphs
Mohar, B.
Graph Theory, Combinatorics, and Applications, 2() 871-898 (1991)
Partitioning Sparse Matrices with Eigenvectors of Graphs
Pothen, A.; Simon, H. & Liou, K.
SIAM J. MATRIX ANAL. APPLIC., 11(3) 430-452 (1990) [pdf]
On generating all maximal independent sets
Johnson, D. S. & Papadimitriou, C. H.
Inf. Process. Lett., 27(3) 119-123 (1988) [pdf]
A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory
Fiedler, M.
Czechoslovak Mathematical Journal, 25(100) 619-633 (1975)