Graph Kernels for Task 1 and 2 of the Linked Data Data-Mining Challenge 2013
| Authors | |
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| Publication date | 2013 |
| Host editors |
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| Book title | Proceedings of the International Workshop on Data Mining on Linked Data, with Linked Data Mining Challenge |
| Book subtitle | collocated with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD 2013) : Prague, Czech Republic, September 23, 2013 |
| Series | CEUR Workshop Proceedings |
| Event | DMoLD 2013: Data Mining on Linked Data with Linked Data Mining Challenge |
| Number of pages | 5 |
| Publisher | Aachen: CEUR-WS |
| Organisations |
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| Abstract | In this paper we present the application of two RDF graph kernels to task 1 and 2 of the linked data data-mining challenge. Both graph kernels use term vectors to handle RDF literals. Based on experiments with the task data, we use the Weisfeiler-Lehman RDF graph kernel for task 1 and the intersection path tree kernel for task 2 in our final classiers for the challenge. Applying these graph kernels is very straightforward and requires (almost) no preprocessing of the data. |
| Document type | Conference contribution |
| Language | English |
| Published at | http://ceur-ws.org/Vol-1082/paper3.pdf |
| Other links | http://ceur-ws.org/Vol-1082/ |
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