%0 %0 Conference Proceedings %A Schmitz, Christoph; Hotho, Andreas; J\"aschke, Robert & Stumme, Gerd %D 2006 %T Content Aggregation on Knowledge Bases using Graph Clustering %E %B Proceedings of the 3rd European Semantic Web Conference %C Budva, Montenegro %I Springer %V 4011 %6 %N %P 530-544 %& %Y %S LNCS %7 %8 June %9 %? %! %Z %@ 3-540-34544-2 %( %) %* %L %M %1 %2 %3 inproceedings %4 %# %$ %F schmitz2006content %K 2006, aggregation, clustering, content, graph, myown, ontology, theory %X %Z %U http://www.kde.cs.uni-kassel.de/hotho/pub/2006/schmitz2006sumarize_eswc.pdf %+ %^ %0 %0 Conference Proceedings %A Schmitz, Christoph; Hotho, Andreas; Jäschke, Robert & Stumme, Gerd %D 2006 %T Content Aggregation on Knowledge Bases using Graph Clustering %E Sure, York & Domingue, John %B The Semantic Web: Research and Applications %C Heidelberg %I Springer %V 4011 %6 %N %P 530-544 %& %Y %S LNAI %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 inproceedings %4 %# %$ %F schmitz2006content %K 2006, aggregation, clustering, content, graph, itegpub, l3s, myown, nepomuk, ontologies, ontology, seminar2006, theory %X 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. %Z %U http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006content.pdf %+ %^ %0 %0 Journal Article %A Soderberg, B. %D 2002 %T General formalism for inhomogeneous random graphs %E %B Phys. Rev. E %C %I APS %V 66 %6 %N 6 %P 066121 %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 article %4 %# %$ %F soderberg2002gfi %K graph, k-partite, random, theory %X %Z %U %+ %^ %0 %0 Generic %A Molloy, M. & Reed, B. %D 1995 %T A critical point for random graphs with a given degree sequence %E %B %C %I %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 misc %4 %# %$ %F molloy_reed95 %K component, configuration, giant, graph, model, random, theory %X %Z %U /brokenurl#citeseer.ist.psu.edu/molloy95critical.html %+ %^ %0 %0 Journal Article %A Frank, O. %D 1988 %T Random sampling and social networks: a survey of various approaches %E %B Math. Sci. Humaines %C %I %V 104 %6 %N %P 19--33 %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 article %4 %# %$ %F frank1988rsa %K graph, random, review, sna, theory %X %Z %U %+ %^ %0 %0 Journal Article %A Karonski, M. %D 1982 %T A review of random graphs %E %B Journal of Graph Theory %C %I Wiley Subscription Services, Inc., A Wiley Company New York %V 6 %6 %N 4 %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 article %4 %# %$ %F karonski1982rrg %K graph, random, theory %X %Z %U %+ %^