AD - PY - 2005/08 VL - IS - SP - EP - UR - http://arxiv.org/abs/cs.DL/0508082 M3 - KW - folksonomy KW - tagging KW - structure L1 - N1 - N1 - N1 - AB - ER - TY - THES AU - Jäschke, Robert T1 - Die Struktur der Monoide binärer Relationen auf endlichen Mengen PY - 2005/ PB - Technische Universität Dresden SP - EP - UR - http://www.kde.cs.uni-kassel.de/pub/pdf/jaeschke2005struktur.pdf M3 - KW - 2005 KW - binary KW - diploma KW - monoid KW - myown KW - relation KW - semigroup KW - structure KW - thesis L1 - N1 - N1 - AB - ER - TY - CONF AU - Brandes, Ulrik AU - Lerner, Jürgen A2 - Fleischer, Rudolf A2 - Trippen, Gerhard T1 - Structural Similarity in Graphs (A Relaxation Approach for Role Assignment). T2 - ISAAC PB - Springer CY - PY - 2004/ M2 - VL - 3341 IS - SP - 184 EP - 195 UR - http://kops.ub.uni-konstanz.de/volltexte/2009/7777/ M3 - KW - actor KW - assignment KW - graph KW - relaxation KW - role KW - similarity KW - structure L1 - SN - 3-540-24131-0 N1 - N1 - AB - Standard methods for role assignment partition the vertex set of a graph in such a way that vertices in the same class can be considered to have equivalent roles in the graph. Several classes of equivalence relations such as regular equivalence and equitable partitions have been proposed for role assignment, but they all suffer from the strictness of classifying vertices into being either equivalent or not. It is an open problem how to allow for varying degrees of similarity. Proposals include ad-hoc algorithmic approaches and optimization approaches which are computationally hard. In this paper we introduce the concept of structural similarity by relaxation of equitable partitions, thus providing a theoretical foundation for similarity measures which enjoys desirable properties with respect to existence, structure, and tractability. ER - TY - JOUR AU - Clauset, Aaron AU - Newman, M.E.J. AU - Moore, Cristopher T1 - Finding community structure in very large networks JO - Physical Review E PY - 2004/ VL - 70 IS - SP - EP - UR - http://www.citebase.org/cgi-bin/citations?id=oai:arXiv.org:cond-mat/0408187 M3 - KW - community KW - detection KW - gn KW - large KW - network KW - newman KW - structure L1 - SN - N1 - N1 - AB - ER - TY - JOUR AU - Kumar, Ravi AU - Novak, Jasmine AU - Raghavan, Prabhakar AU - Tomkins, Andrew T1 - Structure and evolution of blogspace JO - Commun. ACM PY - 2004/ VL - 47 IS - 12 SP - 35 EP - 39 UR - http://doi.acm.org/10.1145/1035134.1035162 M3 - KW - blogging KW - seminar2006 KW - structure KW - community L1 - SN - N1 - N1 - AB - ER - TY - JOUR AU - Newman, M.E.J. AU - Girvan, M. T1 - Finding and evaluating community structure in networks JO - Physical Review E PY - 2004/ VL - 69 IS - SP - EP - UR - http://arxiv.org/abs/cond-mat/0308217 M3 - 10.1103/PhysRevE.69.026113 KW - community KW - detection KW - girvan KW - gn KW - modularity KW - network KW - newman KW - structure L1 - SN - N1 - N1 - AB - We propose and study a set of algorithms for discovering community structure in networks -- natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using one of a number of possible "betweenness" measures, and second, these measures are, crucially, recalculated after each removal. We also propose a measure for the strength of the community structure found by our algorithms, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our algorithms are highly effective at discovering community structure in both computer-generated and real-world network data, and show how they can be used to shed light on the sometimes dauntingly complex structure of networked systems. ER - TY - GEN AU - Tyler, Joshua R. AU - Wilkinson, Dennis M. AU - Huberman, Bernardo A. A2 - T1 - Email as Spectroscopy: Automated Discovery of Community Structure within Organizations JO - PB - Kluwer, B.V. AD - Deventer, The Netherlands, The Netherlands PY - 2003/ VL - IS - SP - 81 EP - 96 UR - http://www.citebase.org/cgi-bin/citations?id=oai:arXiv.org:cond-mat/0303264 M3 - KW - gn KW - detection KW - email KW - structure KW - community L1 - N1 - N1 - AB - We describe a method for the automatic identification of communities of practice from email logs within an organization. We use a betweenness centrality algorithm that can rapidly find communities within a graph representing information flows. We apply this algorithm to an email corpus of nearly one million messages collected over a two-month span, and show that the method is effective at identifying true communities, both formal and informal, within these scale-free graphs. This approach also enables the identification of leadership roles within the communities. These studies are complemented by a qualitative evaluation of the results in the field. ER - TY - JOUR AU - Girvan, Michelle AU - Newman, M.E.J. T1 - Community structure in social and biological networks JO - Proceedings of the National Academy of Science PY - 2002/ VL - 99 IS - 12 SP - 7821 EP - 7826 UR - M3 - KW - social KW - gn KW - detection KW - structure KW - community KW - network L1 - SN - N1 - N1 - AB - A number of recent studies have focused on the statistical properties of networked systems such as social networks and the Worldwide Web. Researchers have concentrated particularly on a few properties that seem to be common to many networks: the small-world property, power-law degree distributions, and network transitivity. In this article, we highlight another property that is found in many networks, the property of community structure, in which network nodes are joined together in tightly knit groups, between which there are only looser connections. We propose a method for detecting such communities, built around the idea of using centrality indices to find community boundaries. We test our method on computer-generated and real-world graphs whose community structure is already known and find that the method detects this known structure with high sensitivity and reliability. We also apply the method to two networks whose community structure is not well known---a collaboration network and a food web---and find that it detects significant and informative community divisions in both cases. ER - TY - JOUR AU - Wille, Rudolf AU - Wille, Uta T1 - Coordinatization of ordinal structures JO - Order PY - 1996/10 VL - 13 IS - 3 SP - 281 EP - 294 UR - http://dx.doi.org/10.1007/BF00338747 M3 - KW - algebra KW - order KW - ordinal KW - structure L1 - SN - N1 - N1 - AB - Dependencies between attributes in ordinal data contexts are algebraically described. Suitable conditions are analysed which allow coordinatizations of ordinal contexts (ordinal structures) by ordered n-quasigroups, ordered abelian groups, and ordered fields. The presented development offers a new approach to conjoint measurement.
ER - ER - TY - JOUR AU - White, Howard D. AU - Griffith, Belver C. T1 - Author cocitation: A literature measure of intellectual structure JO - Journal of the American Society for Information Science PY - 1981/ VL - 32 IS - 3 SP - 163 EP - 171 UR - http://dx.doi.org/10.1002/asi.4630320302 M3 - 10.1002/asi.4630320302 KW - analysis KW - citation KW - literature KW - structure L1 - SN - N1 - N1 - AB - It is shown that the mapping of a particular area of science, in this case information science, can be done using authors as units of analysis and the cocitations of pairs of authors as the variable that indicates their “distances” from each other. The analysis assumes that the more two authors are cited together, the closer the relationship between them. The raw data are cocitation counts drawn online from Social Scisearch (Social Sciences Citation Index) over the period 1972–1979. The resulting map shows (1) identifiable author groups (akin to “schools”) of information science, (2) locations of these groups with respect to each other, (3) the degree of centrality and peripherality of authors within groups, (4) proximities of authors within group and across group boundaries (“border authors” who seem to connect various areas of research), and (5) positions of authors with respect to the map's axes, which were arbitrarily set spanning the most divergent groups in order to aid interpretation. Cocitation analysis of authors offers a new technique that might contribute to the understanding of intellectual structure in the sciences and possibly in other areas to the extent that those areas rely on serial publications. The technique establishes authors, as well as documents, as an effective unit in analyzing subject specialties. ER -