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<rdf:RDF xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><channel rdf:about="https://www.bibsonomy.org/user/hotho/graph"><title>BibSonomy bookmarks for /user/hotho/graph</title><link>https://www.bibsonomy.org/user/hotho/graph</link><description>BibSonomy RSS Feed for /user/hotho/graph</description><items><rdf:Seq><rdf:li rdf:resource="https://journal-submission.dagstuhl.de/TGDK/"/><rdf:li rdf:resource="https://inciteful.xyz/"/><rdf:li rdf:resource="https://tgraph.info/index.html"/><rdf:li rdf:resource="https://graphdeeplearning.github.io/post/transformers-are-gnns/"/><rdf:li rdf:resource="https://concept.research.microsoft.com/Home/Introduction"/><rdf:li rdf:resource="https://academicgraph.blob.core.windows.net/graph/index.html?eulaaccept=on"/><rdf:li rdf:resource="http://webdatacommons.org/hyperlinkgraph/"/><rdf:li rdf:resource="http://www.cs.umd.edu/hcil/graphvis/"/><rdf:li rdf:resource="http://research.microsoft.com/en-us/projects/trueskill/default.aspx"/><rdf:li rdf:resource="http://wiki.neo4j.org/content/Neo4j_Spatial"/><rdf:li rdf:resource="http://gephi.org/"/><rdf:li rdf:resource="http://www.cs.cmu.edu/~christos/TALKS/11-LinkedIn/FOILS/faloutsos_linkedin_2011.pdf"/><rdf:li rdf:resource="http://www.heise.de/newsticker/meldung/GraphDB-wird-schneller-und-kleiner-1235547.html"/><rdf:li rdf:resource="http://neo4j.org/"/><rdf:li rdf:resource="http://socialmedia.typepad.com/blog/2008/10/social-network-visualization-eyecandy.html"/><rdf:li rdf:resource="http://three-mode.leidenuniv.nl/"/><rdf:li rdf:resource="http://socialmedia.typepad.com/blog/2008/09/ranking-nodes-via-random-walks.html"/><rdf:li rdf:resource="http://www.sonivis.org/"/><rdf:li rdf:resource="http://micans.org/mcl/"/><rdf:li rdf:resource="http://plasma-gate.weizmann.ac.il/Grace/"/></rdf:Seq></items></channel><item rdf:about="https://journal-submission.dagstuhl.de/TGDK/"><title>Transactions on Graph Data and Knowledge</title><description></description><link>https://journal-submission.dagstuhl.de/TGDK/</link><dc:creator>hotho</dc:creator><dc:date>2024-10-04T18:10:30+02:00</dc:date><dc:subject>Janeway TGDK graph jws knowledge submission system transactions </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2024-10-04T18:10:30+02:00&#034; href=&#034;https://journal-submission.dagstuhl.de/TGDK/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://journal-submission.dagstuhl.de/TGDK/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Janeway"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/TGDK"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/jws"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/knowledge"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/submission"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/system"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/transactions"/></rdf:Bag></taxo:topics></item><item rdf:about="https://inciteful.xyz/"><title>Using Citations to Explore Academic Literature | Inciteful.xyz</title><description>Using citations to find the most relevant literature</description><link>https://inciteful.xyz/</link><dc:creator>hotho</dc:creator><dc:date>2024-04-29T20:05:11+02:00</dc:date><dc:subject>citation graph literature network paper scholar search </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Using citations to find the most relevant literature&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/citation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/literature"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/paper"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/scholar"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/search"/></rdf:Bag></taxo:topics></item><item rdf:about="https://tgraph.info/index.html"><title>TGRAPH: Transactions on Graph Data and Knowledge</title><description></description><link>https://tgraph.info/index.html</link><dc:creator>hotho</dc:creator><dc:date>2023-02-12T16:36:58+01:00</dc:date><dc:subject>KG graph journal knowledge semantics tgraph </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2023-02-12T16:36:58+01:00&#034; href=&#034;https://tgraph.info/index.html&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://tgraph.info/index.html&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/KG"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/journal"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/knowledge"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/semantics"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tgraph"/></rdf:Bag></taxo:topics></item><item rdf:about="https://graphdeeplearning.github.io/post/transformers-are-gnns/"><title>Transformers are Graph Neural Networks | NTU Graph Deep Learning Lab</title><description>Engineer friends often ask me: Graph Deep Learning sounds great, but are there any big commercial success stories? Is it being deployed in practical applications? Besides the obvious ones–recommendation systems at Pinterest, Alibaba and Twitter–a slightly nuanced success story is the Transformer architecture, which has taken the NLP industry by storm. Through this post, I want to establish links between Graph Neural Networks (GNNs) and Transformers. I’ll talk about the intuitions behind model architectures in the NLP and GNN communities, make connections using equations and figures, and discuss how we could work together to drive progress.</description><link>https://graphdeeplearning.github.io/post/transformers-are-gnns/</link><dc:creator>hotho</dc:creator><dc:date>2020-03-10T15:48:11+01:00</dc:date><dc:subject>deep graph learning network neural nn transformer </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Engineer friends often ask me: Graph Deep Learning sounds great, but are there any big commercial success stories? Is it being deployed in practical applications? Besides the obvious ones–recommendation systems at Pinterest, Alibaba and Twitter–a slightly nuanced success story is the Transformer architecture, which has taken the NLP industry by storm. Through this post, I want to establish links between Graph Neural Networks (GNNs) and Transformers. I’ll talk about the intuitions behind model architectures in the NLP and GNN communities, make connections using equations and figures, and discuss how we could work together to drive progress.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/deep"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learning"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/neural"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/nn"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/transformer"/></rdf:Bag></taxo:topics></item><item rdf:about="https://concept.research.microsoft.com/Home/Introduction"><title>Microsoft Concept Graph and Concept Tagging Release</title><description></description><link>https://concept.research.microsoft.com/Home/Introduction</link><dc:creator>hotho</dc:creator><dc:date>2016-11-02T13:56:05+01:00</dc:date><dc:subject>concept dataset graph knowledge microsoft ontology </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-11-02T13:56:05+01:00&#034; href=&#034;https://concept.research.microsoft.com/Home/Introduction&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://concept.research.microsoft.com/Home/Introduction&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/concept"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dataset"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/knowledge"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/microsoft"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/ontology"/></rdf:Bag></taxo:topics></item><item rdf:about="https://academicgraph.blob.core.windows.net/graph/index.html?eulaaccept=on"><title>Microsoft Academic Graph</title><description>Microsoft Academic Graph Releases:</description><link>https://academicgraph.blob.core.windows.net/graph/index.html?eulaaccept=on</link><dc:creator>hotho</dc:creator><dc:date>2015-09-15T11:40:16+02:00</dc:date><dc:subject>MSAC WSDM challenge citation cup dataset graph </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Microsoft Academic Graph Releases:&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/MSAC"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/WSDM"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/challenge"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/citation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/cup"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dataset"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/></rdf:Bag></taxo:topics></item><item rdf:about="http://webdatacommons.org/hyperlinkgraph/"><title>WDC - Hyperlink Graph</title><description>This page provides a large hyperlink graph for public download. The graph has been extracted from the Common Crawl 2012 web corpus and covers 3.5 billion web pages and 128 billion hyperlinks between these pages. To the best of our knowledge, this graph is the largest hyperlink graph that is available to the public outside companies such as Google, Yahoo, and Microsoft. Below we provide instructions on how to download the graph as well as basic statistics about its topology. </description><link>http://webdatacommons.org/hyperlinkgraph/</link><dc:creator>hotho</dc:creator><dc:date>2013-11-13T10:36:31+01:00</dc:date><dc:subject>dataset graph hyperlink web </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;This page provides a large hyperlink graph for public download. The graph has been extracted from the Common Crawl 2012 web corpus and covers 3.5 billion web pages and 128 billion hyperlinks between these pages. To the best of our knowledge, this graph is the largest hyperlink graph that is available to the public outside companies such as Google, Yahoo, and Microsoft. Below we provide instructions on how to download the graph as well as basic statistics about its topology. &lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dataset"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/hyperlink"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/web"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.cs.umd.edu/hcil/graphvis/"><title>Graph Visualization</title><description>Graph Visualization
Summary of HCIL projects </description><link>http://www.cs.umd.edu/hcil/graphvis/</link><dc:creator>hotho</dc:creator><dc:date>2013-03-14T10:44:41+01:00</dc:date><dc:subject>graph tools visualization </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Graph Visualization
Summary of HCIL projects &lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tools"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/visualization"/></rdf:Bag></taxo:topics></item><item rdf:about="http://research.microsoft.com/en-us/projects/trueskill/default.aspx"><title>TrueSkill Ranking System - Microsoft Research</title><description>TrueSkill™ Ranking System
TrueSkill™ Ranking System

The TrueSkill™ ranking system is a skill based ranking system for Xbox Live developed at Microsoft Research.</description><link>http://research.microsoft.com/en-us/projects/trueskill/default.aspx</link><dc:creator>hotho</dc:creator><dc:date>2012-03-19T16:37:19+01:00</dc:date><dc:subject>bayes elo factor graph microsoft prediction ranking research trueskill </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;TrueSkill™ Ranking System
TrueSkill™ Ranking System

The TrueSkill™ ranking system is a skill based ranking system for Xbox Live developed at Microsoft Research.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/elo"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/factor"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/microsoft"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/ranking"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/research"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/trueskill"/></rdf:Bag></taxo:topics></item><item rdf:about="http://wiki.neo4j.org/content/Neo4j_Spatial"><title>Neo4j Spatial - Neo4j Wiki</title><description>The Neo4j database core has no built in support for spatial data. </description><link>http://wiki.neo4j.org/content/Neo4j_Spatial</link><dc:creator>hotho</dc:creator><dc:date>2011-09-19T18:42:30+02:00</dc:date><dc:subject>database graph neo4j spatial </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;The Neo4j database core has no built in support for spatial data. &lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/database"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/neo4j"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/spatial"/></rdf:Bag></taxo:topics></item><item rdf:about="http://gephi.org/"><title>Gephi, an open source graph visualization and manipulation software</title><description>Gephi is an open-source software for visualizing and analyzing large networks graphs. Gephi uses a 3D render engine to display graphs in real-time and speed up the exploration. Use Gephi to explore, analyse, spatialise, filter, cluterize, manipulate and export all types of graphs.</description><link>http://gephi.org/</link><dc:creator>hotho</dc:creator><dc:date>2011-08-15T09:44:36+02:00</dc:date><dc:subject>analysis graph network sna visualization </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Gephi is an open-source software for visualizing and analyzing large networks graphs. Gephi uses a 3D render engine to display graphs in real-time and speed up the exploration. Use Gephi to explore, analyse, spatialise, filter, cluterize, manipulate and export all types of graphs.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/analysis"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/sna"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/visualization"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.cs.cmu.edu/~christos/TALKS/11-LinkedIn/FOILS/faloutsos_linkedin_2011.pdf"><title>Mining Billion-node Graphs: Patterns and Tools</title><description></description><link>http://www.cs.cmu.edu/~christos/TALKS/11-LinkedIn/FOILS/faloutsos_linkedin_2011.pdf</link><dc:creator>hotho</dc:creator><dc:date>2011-06-22T10:38:14+02:00</dc:date><dc:subject>graph linkedin mining tools toread </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2011-06-22T10:38:14+02:00&#034; href=&#034;http://www.cs.cmu.edu/~christos/TALKS/11-LinkedIn/FOILS/faloutsos_linkedin_2011.pdf&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.cs.cmu.edu/~christos/TALKS/11-LinkedIn/FOILS/faloutsos_linkedin_2011.pdf&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/linkedin"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/mining"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tools"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/toread"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.heise.de/newsticker/meldung/GraphDB-wird-schneller-und-kleiner-1235547.html"><title>heise online - GraphDB wird schneller und kleiner</title><description>Version 2 der freien Graph-Datenbank GraphDB haben die Entwickler modularisiert, auch haben sie die Verteilung von Graphen auf mehrere Knoten ermöglicht. Hinzugekommen sind außerdem neue Schnittstellen, unter anderem für PHP.</description><link>http://www.heise.de/newsticker/meldung/GraphDB-wird-schneller-und-kleiner-1235547.html</link><dc:creator>hotho</dc:creator><dc:date>2011-05-11T15:15:57+02:00</dc:date><dc:subject>datenbank db everyaware graph </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Version 2 der freien Graph-Datenbank GraphDB haben die Entwickler modularisiert, auch haben sie die Verteilung von Graphen auf mehrere Knoten ermöglicht. Hinzugekommen sind außerdem neue Schnittstellen, unter anderem für PHP.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/datenbank"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/db"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/everyaware"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/></rdf:Bag></taxo:topics></item><item rdf:about="http://neo4j.org/"><title>neo4j open source nosql graph database »</title><description></description><link>http://neo4j.org/</link><dc:creator>hotho</dc:creator><dc:date>2011-03-14T18:52:38+01:00</dc:date><dc:subject>database everyaware graph open source </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2011-03-14T18:52:38+01:00&#034; href=&#034;http://neo4j.org/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://neo4j.org/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/database"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/everyaware"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/open"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/source"/></rdf:Bag></taxo:topics></item><item rdf:about="http://socialmedia.typepad.com/blog/2008/10/social-network-visualization-eyecandy.html"><title>Social Media Research Blog: Social Network Visualization Eyecandy</title><description>Visualization of graph data is incredibly challenging, particularly when it comes to extremely large, scale-free graphs and social networks. A few simple searches on the Web and you will find some mesmerizing and very cool images. Perhaps the most cited...</description><link>http://socialmedia.typepad.com/blog/2008/10/social-network-visualization-eyecandy.html</link><dc:creator>hotho</dc:creator><dc:date>2009-04-28T15:06:41+02:00</dc:date><dc:subject>blog community detection graph media network post social visualization </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Visualization of graph data is incredibly challenging, particularly when it comes to extremely large, scale-free graphs and social networks. A few simple searches on the Web and you will find some mesmerizing and very cool images. Perhaps the most cited...&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/blog"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/community"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/detection"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/media"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/network"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/post"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/social"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/visualization"/></rdf:Bag></taxo:topics></item><item rdf:about="http://three-mode.leidenuniv.nl/"><title>The Three-Mode Company Home Page</title><description></description><link>http://three-mode.leidenuniv.nl/</link><dc:creator>hotho</dc:creator><dc:date>2009-02-09T13:06:19+01:00</dc:date><dc:subject>analysis data graph mode tools tripartite </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2009-02-09T13:06:19+01:00&#034; href=&#034;http://three-mode.leidenuniv.nl/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://three-mode.leidenuniv.nl/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/analysis"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/data"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/mode"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tools"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tripartite"/></rdf:Bag></taxo:topics></item><item rdf:about="http://socialmedia.typepad.com/blog/2008/09/ranking-nodes-via-random-walks.html"><title>Social Media Research Blog: Ranking Nodes via Random Walks</title><description></description><link>http://socialmedia.typepad.com/blog/2008/09/ranking-nodes-via-random-walks.html</link><dc:creator>hotho</dc:creator><dc:date>2008-10-09T13:33:48+02:00</dc:date><dc:subject>graph random ranking toread walk </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2008-10-09T13:33:48+02:00&#034; href=&#034;http://socialmedia.typepad.com/blog/2008/09/ranking-nodes-via-random-walks.html&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://socialmedia.typepad.com/blog/2008/09/ranking-nodes-via-random-walks.html&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/random"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/ranking"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/toread"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/walk"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.sonivis.org/"><title>SONIVIS</title><description></description><link>http://www.sonivis.org/</link><dc:creator>hotho</dc:creator><dc:date>2008-09-03T14:23:36+02:00</dc:date><dc:subject>SONIVIS graph sna tools visualization </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2008-09-03T14:23:36+02:00&#034; 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data-versiondate=&#034;2007-12-03T11:52:51+01:00&#034; href=&#034;http://plasma-gate.weizmann.ac.il/Grace/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://plasma-gate.weizmann.ac.il/Grace/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/gnuplot"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/grace"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/graph"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/latex"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/linux"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/math"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tools"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/visualization"/></rdf:Bag></taxo:topics></item></rdf:RDF>