Hi Mathias, Can you give more details? Is your application for text + ontology, or ontology only?
regards jiang xing On 1/19/06, Mathias Lux <[EMAIL PROTECTED]> wrote: > > Hi! > > (1) I'm working on a similar problem, but based on MPEG-7 Semantic > Description Graphs. I've already a prototype for pakth based matching > within Lucene integrated in my sf project Caliph & Emir > (http://caliph-emir.sf.net). I've already adapted the approach to an > ontology, which had to be searched. > > My approach works roughly like this: > * index all paths up to a certain length in a graph as strings in > Lucene > * index all node descriptions in another index > * Within the query graph nodes are lucene queries -> query expansion to > node ids based on the node index > * search for all expanded query graphs and merge results. > > Unfortunately I didn't have time yet to do a full evaluation, but > preeliminary results are promising. > > The valuation and a more comprehensive description of the approach can > be found in the proceedings of the TIR 05 (Text Information Retrieval > Workschop 2005 in Koblenz, Germany): > http://www-ai.upb.de/aisearch/tir-05/proceedings/lux05-fast-and-simple-p > ath-index-based-retrieval.pdf > > The prototype is available @ http://caliph-emir.sf.net. > > I'm open to comments and ideas on the approach as it is part of my PhD > and I'm working on a method without query expansion :-) > > (2) A second thing is the feature based retrieval of nodes within an > ontology, which allows really fast indexing and retrieval as no > pathwalking takes place. > Works like this: > * nodes being the documents / entities being searched for in the > ontology are extracted * surrounding nodes / literals are used as characteristic features > * with some heuristics and some runtime configuration classifications, > text & keyword fields are separated > * Retrieval is purely based on text and keywords, the same with > similarity search > * additional Clustering is done on snippets from search results. > I already have a prototype running with this approach, but no evaluation > yet, sorry! For more information on this one please contact me. A > publication on this is currently in review, so I cannot give a link here > ;( > > References: > - Rodriguez, M.A. & Egenhofer, M.J. (2003), 'Determining Semantic > Similarity among Entity Classes from Different Ontologies', IEEE > Transactions on Knowledge and Data Engineering 15(2), 442--456. > - Varelas, G.; Voutsakis, E.; Raftopoulou, P.; Petrakis, E.G. & Milios, > E.E. (2005), Semantic similarity meth-ods in wordNet and their > application to information retrieval on the web, in 'WIDM '05: > Proceedings of the 7th annual ACM international workshop on Web > information and data management', ACM Press, New York, NY, USA, pp. > 10--16. > > > regards, > Mathias > > ============================================================ > DI Mathias Lux > Know-Center & Graz University of Technology, Austria > Institute for Knowledge Management (IWM) > Inffeldgasse 21a, 8010 Graz, Austria > Email : [EMAIL PROTECTED] > Tel: +43 316 873 9274 Fax: +43 316 873 9252 > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [EMAIL PROTECTED] > For additional commands, e-mail: [EMAIL PROTECTED] > > -- Regards Jiang Xing
