the decisions individuals make. These networks link different types of
entities, for example, people and the events they attend. Network analysis
algorithms usually project such networks unto simple graphs composed of
entities of a single type. In the process, they conflate relations between
entities of different types and loose important structural information. We
develop a mathematical framework that can be used to compactly represent and
analyze heterogeneous networks that combine multiple entity and link types. We
generalize Bonacich centrality, which measures connectivity between nodes by
the number of paths between them, to heterogeneous networks and use this
measure to study network structure. Specifically, we extend the popular
modularity-maximization method for community detection to use this centrality
metric. We also rank nodes based on their connectivity to other nodes. One
advantage of this centrality metric is that it has a tunable parameter we can
use to set the length scale of interactions. By studying how rankings change
with this parameter allows us to identify important nodes in the network. We
apply the proposed method to analyze the structure of several heterogeneous
networks. We show that exploiting additional sources of evidence corresponding
to links between, as well as among, different entity types yields new insights
into network structure.
ER - TY - GEN AU - Noack, Andreas A2 - T1 - Modularity clustering is force-directed layout JO - PB - C1 - PY - 2008/ VL - IS - SP - EP - UR - http://www.citebase.org/abstract?id=oai:arXiv.org:0807.4052 DO - KW - clustering KW - communities KW - community KW - graph KW - layout KW - modularity KW - network KW - sna L1 - N1 - [0807.4052] Modularity clustering is force-directed layout N1 - AB - Two natural and widely used representations for the community structure of networks are clusterings, which partition the vertex set into disjoint subsets, and layouts, which assign the vertices to positions in a metric space. This paper unifies prominent characterizations of layout quality and clustering quality, by showing that energy models of pairwise attraction and repulsion subsume Newman and Girvan's modularity measure. Layouts with optimal energy are relaxations of, and are thus consistent with, clusterings with optimal modularity, which is of practical relevance because both representations are complementary and often used together. ER - TY - CONF AU - Zhu, Feida AU - Chen, Chen AU - Yan, Xifeng AU - Han, Jiawei AU - Yu, Philip S A2 - T1 - Graph OLAP: Towards Online Analytical Processing on Graphs T2 - Proc. 2008 Int. Conf. on Data Mining (ICDM'08), Pisa, Italy, Dec. 2008. PB - C1 - PY - 2008/12 CY - VL - IS - SP - EP - UR - DO - KW - graph KW - graphs KW - olap KW - sna L1 - SN - N1 - Resource: Graph OLAP: Towards Online Analytical Processing on Graphs N1 - AB - ER - TY - CONF AU - Hotho, Andreas AU - Jäschke, Robert AU - Schmitz, Christoph AU - Stumme, Gerd A2 - T1 - Information Retrieval in Folksonomies: Search and Ranking T2 - Proceedings of the 3rd European Semantic Web Conference PB - Springer C1 - PY - 2006/ CY - VL - IS - SP - 411 EP - 426 UR - DO - KW - FCA KW - OntologyHandbook KW - folkrank KW - folksonomy KW - graph KW - information KW - mining KW - pagerank KW - rank KW - ranking KW - retrieval KW - search KW - seminar2006 L1 - SN - N1 - N1 - AB - ER - TY - CONF AU - Schmitz, Christoph AU - Hotho, Andreas AU - Jäschke, Robert AU - Stumme, Gerd A2 - Sure, York A2 - Domingue, John T1 - Content Aggregation on Knowledge Bases using Graph Clustering T2 - The Semantic Web: Research and Applications PB - Springer C1 - Heidelberg PY - 2006/ CY - VL - 4011 IS - SP - 530 EP - 544 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006content.pdf DO - KW - 2006 KW - aggregation KW - clustering KW - content KW - graph KW - itegpub KW - l3s KW - myown KW - nepomuk KW - ontologies KW - ontology KW - seminar2006 KW - theory L1 - SN - N1 - N1 - AB - 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. ER - TY - CONF AU - Brandes, U. AU - Willhalm, T. A2 - T1 - Visualization of bibliographic networks with a reshaped landscape metaphor T2 - Proceedings of the symposium on Data Visualisation 2002 PB - Eurographics Association C1 - Aire-la-Ville, Switzerland, Switzerland PY - 2002/ CY - VL - IS - SP - 159 EP - ff UR - http://portal.acm.org/citation.cfm?id=509740.509765 DO - KW - bibliographic KW - bibliography KW - citation KW - graph KW - networks KW - sna L1 - SN - 1-58113-536-X N1 - Visualization of bibliographic networks with a reshaped landscape metaphor N1 - AB - We describe a novel approach to visualize bibliographic networks that facilitates the simultaneous identification of clusters (e.g., topic areas) and prominent entities (e.g., surveys or landmark papers). While employing the landscape metaphor proposed in several earlier works, we introduce new means to determine relevant parameters of the landscape. Moreover, we are able to compute prominent entities, clustering of entities, and the landscape's surface in a surprisingly simple and uniform way. The effectiveness of our network visualizations is illustrated on data from the graph drawing literature. ER - TY - CONF AU - Eklund, P. AU - Groh, B. AU - Stumme, G. AU - Wille, R. A2 - Ganter, B. A2 - Mineau, G. W. T1 - Contextual-Logic Extension of TOSCANA. T2 - Conceptual Structures: Logical, Linguistic, and Computational PB - Springer C1 - Heidelberg PY - 2000/ CY - VL - 1867 IS - SP - 453 EP - 467 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2000/ICCS_toscanaextension.pdf DO - KW - 2000 KW - analysis KW - cg KW - cgs KW - concept KW - conceptual KW - fca KW - formal KW - graph KW - graphs KW - iccs KW - myown KW - toscana L1 - SN - N1 - Publications of Gerd Stumme N1 - AB - ER - TY - CONF AU - Prediger, Susanne AU - Wille, Rudolf A2 - Tepfenhart, William M. A2 - Cyre, Walling R. T1 - The Lattice of Concept Graphs of a Relationally Scaled Context T2 - ICCS PB - Springer C1 - PY - 1999/ CY - VL - 1640 IS - SP - 401 EP - 414 UR - http://dblp.uni-trier.de/db/conf/iccs/iccs99.html#PredigerW99 DO - KW - analysis KW - cg KW - concept KW - fca KW - formal KW - graph KW - graphs L1 - SN - 3-540-66223-5 N1 - N1 - AB - ER - TY - CONF AU - Wille, Rudolf A2 - Lukose, D. A2 - Delugach, H. A2 - Keeler, M. A2 - Searle, L. A2 - Sowa, J. F. T1 - Conceptual Graphs and Formal Concept Analysis T2 - Conceptual Structures: Fulfilling Peirce's Dream PB - Springer C1 - Heidelberg PY - 1997/ CY - VL - 1257 IS - SP - 290 EP - 303 UR - DO - KW - ag1 KW - analysis KW - begriffsanalyse KW - cg KW - concept KW - conceptual KW - darmstadt KW - fba KW - fca KW - formal KW - graph KW - graphs L1 - SN - N1 - N1 - AB - ER - TY - CONF AU - Stumme, Gerd AU - Wille, Rudolf A2 - Tamassia, R. A2 - Tollis, I.G. T1 - A Geometrical Heuristic for Drawing Concept Lattices T2 - Graph Drawing PB - Springer C1 - Heidelberg PY - 1995/ CY - VL - 894 IS - SP - 452 EP - 459 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/1994/P1677-GD94.pdf DO - KW - 1995 KW - analysis KW - concept KW - drawing KW - fca KW - formal KW - graph KW - lattices KW - myown L1 - SN - N1 - Publications of Gerd Stumme N1 - AB - ER -