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Re: PageRank approaches

From: Jörn Hees <j_hees@cs.uni-kl.de>
Date: Fri, 11 May 2012 16:10:06 +0200
Cc: semantic-web@w3.org
Message-Id: <78197A08-E422-4769-BD59-CDB5D0206F2E@cs.uni-kl.de>
To: Michael Brunnbauer <brunni@netestate.de>

On 11. May. 2012, at 15:50, Michael Brunnbauer wrote:

> there has been some work on applying Page Rank algorithms onto the semantic
> web in the past. Most approaches seem to rank semantic web entities by
> considering the probability to get to a specific entity - or node - while 
> following the edges of the RDF graph.
> I wonder if an approach of ranking a semantic web document by the probability
> to stumble upon it while dereferencing URIs (follow your nose) is feasible or
> has been tried. In this approach, every URI of every triple in a semantic
> web document will be considered a link to another document (which can contain
> triples and therefor further outgoing links - or not).

Just some from my related work (alphabetically):

Aleman-Meza, B., C. Halaschek-Wiener, I.B. Arpinar, C. Ramakrishnan, and a.P. Sheth. 2005. “Ranking Complex Relationships on the Semantic Web.” IEEE Internet Computing 9 (3) (May): 37-44. doi:10.1109/MIC.2005.63. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=1438303.

Anyanwu, Kemafor, Angela Maduko, and Amit P. Sheth. 2005. SemRank: Ranking Complex Relationship Search Results on the Semantic Web. In Proc. of the WWW 2005. Chiba, Japan. http://dl.acm.org/citation.cfm?id=1060766.

Balmin, Andrey, Vagelis Hristidis, and Yannis Papakonstantinou. 2004. ObjectRank: Authority-Based Keyword Search in Databases. In Proc. of the 13th International Conference on Very Large Data Bases, VLDB Endowment, 564-575.

Delbru, Renaud, Nickolai Toupikov, Michele Catasta, Giovanni Tummarello, and Stefan Decker. 2010. Hierarchical Link Analysis for Ranking Web Data. In Proc. of the ESWC 2010, ed. Lora Aroyo, Grigoris Antoniou, Eero Hyvönen, Annette ten Teije, Heiner Stuckenschmidt, Liliana Cabral, and Tania Tudorache, 225-239. Heraklion, Crete, Greece: Springer Berlin / Heidelberg. doi:http://dx.doi.org/10.1007/978-3-642-13489-0_16.

Ding, Li, Rong Pan, Tim Finin, Anupam Joshi, Yun Peng, and Pranam Kolari. 2005. Finding and Ranking Knowledge on the Semantic Web. In Proc. of the ISWC 2005, ed. Yolanda Gil, Enrico Motta, V. Richard Benjamins, and Mark A. Musen, 156-170. Galway, Ireland: Springer Berlin / Heidelberg. doi:http://dx.doi.org/10.1007/11574620_14.

Franz, Thomas, Antje Schultz, Sergej Sizov, and Steffen Staab. 2009. TripleRank: Ranking Semantic Web Data by Tensor Decomposition. In Proc. of the ISWC 2009, ed. Abraham Bernstein, David R. Karger, Tom Heath, Lee Feigenbaum, Diana Maynard, Enrico Motta, and Krishnaprasad Thirunarayan, 213-228. Chantilly, VA, USA: Springer Berlin / Heidelberg. doi:http://dx.doi.org/10.1007/978-3-642-04930-9_14. http://www.springerlink.com/index/W173VM22556877N3.pdf.

Harth, Andreas, Sheila Kinsella, and Stefan Decker. 2009. Using Naming Authority to Rank Data and Ontologies for Web Search. In Proc. of the ISWC 2009, ed. Abraham Bernstein, David R. Karger, Tom Heath, Lee Feigenbaum, Diana Maynard, Enrico Motta, and Krishnaprasad Thirunarayan, 2:277-292. Chantilly, VA, USA: Springer Berlin / Heidelberg. doi:http://dx.doi.org/10.1007/978-3-642-04930-9_18.

Harth, Andreas, and Sheila Kinsella. 2009. TOPDIS: Tensor-Based Ranking for Data Search and Navigation. Business.

Tummarello, Giovanni, Renaud Delbru, and Eyal Oren. 2007. Sindice.com: Weaving the Open Linked Data. In Proc. of the ISWC 2007, 552-565. Springer Berlin / Heidelberg. doi:10.1007/978-3-540-76298-0_40.

If you know more I'd be interested ;)

Received on Friday, 11 May 2012 14:10:50 UTC

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