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]
