A Linked Data Recommender System using a Neighborhood-based Graph Kernel
作者： Vito Claudio Ostuni , Tommaso Di Noia , Roberto Mirizzi , Eugenio Di Sciascio
DOI: 10.1007/978-3-319-10491-1_10
关键词: Novelty 、 Linked data 、 RSS 、 Boosting (machine learning) 、 Boom 、 Recommender system 、 Graph kernel 、 MovieLens 、 Data mining 、 Computer science
摘要: The ultimate mission of a Recommender System (RS) is to help users discover items they might be interested in. In order really useful for the end-user, Content-based (CB) RSs need both harvest as much information possible about such and effectively handle it. boom Linked Open Data (LOD) datasets with their huge amount semantically interrelated data thus great opportunity boosting CB-RSs. this paper we present CB-RS that leverages LOD profits from neighborhood-based graph kernel. proposed kernel able compute semantic item similarities by matching local neighborhood graphs. Experimental evaluation on MovieLens dataset shows approach outperforms in terms accuracy novelty other competitive approaches.
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Vito Claudio Ostuni, Giosia Gentile, Tommaso Di Noia, Roberto Mirizzi, Davide Romito, Eugenio Di Sciascio, Mobile Movie Recommendations with Linked Data availability reliability and security. pp. 400- 415 ,(2013) , 10.1007/978-3-642-40511-2_29
Uta Lösch, Stephan Bloehdorn, Achim Rettinger, Graph Kernels for RDF Data Lecture Notes in Computer Science. pp. 134- 148 ,(2012) , 10.1007/978-3-642-30284-8_16
Conor Hayes, Benjamin Heitmann, Using Linked Data to Build Open, Collaborative Recommender Systems. national conference on artificial intelligence. ,(2010)
Nello Cristianini, John Shawe-Taylor, Kernel Methods for Pattern Analysis ,(2004)
Michael J. Pazzani, Daniel Billsus, Content-Based Recommendation Systems The Adaptive Web. pp. 325- 341 ,(2007) , 10.1007/978-3-540-72079-9_10
Iván Cantador, Alejandro Bellogín, Pablo Castells, A multilayer ontology-based hybrid recommendation model Ai Communications. ,vol. 21, pp. 203- 210 ,(2008) , 10.3233/AIC-2008-0437
Bamshad Mobasher, Xin Jin, Yanzan Zhou, Semantically Enhanced Collaborative Filtering on the Web European Web Mining Forum. pp. 57- 76 ,(2003) , 10.1007/978-3-540-30123-3_4
Thomas Gärtner, Peter Flach, Stefan Wrobel, On Graph Kernels: Hardness Results and Efficient Alternatives Learning Theory and Kernel Machines. pp. 129- 143 ,(2003) , 10.1007/978-3-540-45167-9_11
Stuart E. Middleton, David De Roure, Nigel R. Shadbolt, Ontology-Based Recommender Systems Handbook on Ontologies. pp. 779- 796 ,(2009) , 10.1007/978-3-540-92673-3_35
Tarek Abudawood, Peter Flach, Evaluation Measures for Multi-class Subgroup Discovery european conference on machine learning. pp. 35- 50 ,(2009) , 10.1007/978-3-642-04180-8_20