@article{linden2003, title = {Amazon.com recommendations: item-to-item collaborative filtering}, author = {G. Linden and B. Smith and J. York}, journal = {Internet Computing, IEEE}, number = 1, pages = {76--80}, volume = 7, year = 2003, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1167344}, id = {615956}, priority = {3}, description = {Dissertation}, abstract = {Recommendation algorithms are best known for their use on e-commerce Web sites, where they use input about a customer's interests to generate a list of recommended items. Many applications use only the items that customers purchase and explicitly rate to represent their interests, but they can also use other attributes, including items viewed, demographic data, subject interests, and favorite artists. At Amazon.com, we use recommendation algorithms to personalize the online store for each customer. The store radically changes based on customer interests, showing programming titles to a software engineer and baby toys to a new mother. There are three common approaches to solving the recommendation problem: traditional collaborative filtering, cluster models, and search-based methods. Here, we compare these methods with our algorithm, which we call item-to-item collaborative filtering. Unlike traditional collaborative filtering, our algorithm's online computation scales independently of the number of customers and number of items in the product catalog. Our algorithm produces recommendations in real-time, scales to massive data sets, and generates high quality recommendations.}, biburl = {http://www.bibsonomy.org/bibtex/2880e27782ec86737a931b9d92d9e905a/minguez}, keywords = {recommender matchmaking master} } @inproceedings{352887, title = {Analysis of recommendation algorithms for e-commerce}, address = {New York, NY, USA}, author = {Badrul Sarwar and George Karypis and Joseph Konstan and John Riedl}, booktitle = {EC '00: Proceedings of the 2nd ACM conference on Electronic commerce}, pages = {158--167}, publisher = {ACM Press}, year = 2000, url = {http://portal.acm.org/citation.cfm?id=352887}, location = {Minneapolis, Minnesota, United States}, isbn = {1-58113-272-7}, doi = {http://doi.acm.org/10.1145/352871.352887}, description = {Analysis of recommendation algorithms for e-commerce}, biburl = {http://www.bibsonomy.org/bibtex/28761b337bd08a4ac7b72bac4c84851fb/minguez}, keywords = {recommender matchmaking master} } @inproceedings{conf/atal/KluschFS06, title = {Automated semantic web service discovery with OWLS-MX.}, author = {Matthias Klusch and Benedikt Fries and Katia Sycara}, booktitle = {AAMAS}, crossref = {conf/atal/2006}, editor = {Hideyuki Nakashima and Michael P. Wellman and Gerhard Weiss and Peter Stone}, pages = {915-922}, publisher = {ACM}, year = 2006, url = {http://dblp.uni-trier.de/db/conf/atal/aamas2006.html#KluschFS06}, ee = {http://doi.acm.org/10.1145/1160633.1160796}, isbn = {1-59593-303-4}, date = {2006-09-27}, description = {dblp}, biburl = {http://www.bibsonomy.org/bibtex/27b18c5dec3672081adfdcfc000e3ff50/minguez}, keywords = {descriptionlogic matchmaking master} } @inproceedings{borgida05similarity, title = {Towards Measuring Similarity in Description Logics.}, author = {Alexander Borgida and Thomas Walsh and Haym Hirsh}, booktitle = {Proceedings of the 2005 International Workshop on Description Logics (DL2005), July 26-28, 2005, Edinburgh, Scotland, UK}, editor = {Ian Horrocks and Ulrike Sattler and Frank Wolter}, publisher = {CEUR-WS.org}, series = {CEUR Workshop Proceedings}, volume = 147, year = 2005, url = {http://www.ceur-ws.org/Vol-147/25-BorgidaEtAl.pdf}, biburl = {http://www.bibsonomy.org/bibtex/21bfb5f33156769d97d22bf8d5b4369dc/minguez}, keywords = {descriptionlogic matchmaking master} } @inproceedings{Kiefer/2007/Fundamentals, title = {The Fundamentals of iSPARQL - A Virtual Triple Approach For Similarity-Based Semantic Web Tasks}, address = {Berlin, Heidelberg}, author = {Christoph Kiefer and Abraham Bernstein and Markus Stocker}, booktitle = {Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference (ISWC/ASWC2007), Busan, South Korea}, crossref = {http://data.semanticweb.org/conference/iswc-aswc/2007/proceedings}, editor = {Karl Aberer and Key-Sun Choi and Natasha Noy and Dean Allemang and Kyung-Il Lee and Lyndon J B Nixon and Jennifer Golbeck and Peter Mika and Diana Maynard and Guus Schreiber and Philippe Cudré-Mauroux}, month = {November}, pages = {295--308}, publisher = {Springer Verlag}, series = {LNCS}, volume = 4825, year = 2007, url = {http://iswc2007.semanticweb.org/papers/295.pdf}, abstract = {This research explores three SPARQL-based techniques to solve Semantic Web tasks that often require similarity measures, such as semantic data integration, ontology mapping, and Semantic Web service matchmaking. Our aim is to see how far it is possible to integrate customized similarity functions (CSF) into SPARQL to achieve good results for these tasks. Our first approach exploits virtual triples calling property functions to establish virtual relations among resources under comparison; the second approach uses extension functions to filter out resources that do not meet the requested similarity criteria; finally, our third technique applies new solution modifiers to post-process a SPARQL solution sequence. The semantics of the three approaches are formally elaborated and discussed. We close the paper with a demonstration of the usefulness of our iSPARQL framework in the context of a data integration and an ontology mapping experiment.}, biburl = {http://www.bibsonomy.org/bibtex/25af761051f5ee7543ac1606fbd91ea96/minguez}, keywords = {matchmaking master sparql} } @inproceedings{lin98informationtheroreticsimilarity, title = {An Information-Theoretic Definition of Similarity}, author = {Dekang Lin}, booktitle = {Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), Madison, Wisconson, USA, July 24-27, 1998}, editor = {Jude W. Shavlik}, pages = {296-304}, publisher = {Morgan Kaufmann}, year = 1998, url = {http://dblp.uni-trier.de/db/conf/icml/icml1998.html#Lin98}, isbn = {1-57735-189-4}, description = {dblp}, biburl = {http://www.bibsonomy.org/bibtex/20e3fd7b6cceacfea45f1166669bd33a1/minguez}, keywords = {similarity matchmaking master} } @article{journals/corr/cmp-lg-9709008, title = {Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy}, author = {Jay J. Jiang and David W. Conrath}, journal = {CoRR}, note = {informal publication}, volume = {cmp-lg/9709008}, year = 1997, url = {http://dblp.uni-trier.de/db/journals/corr/corr9709.html#cmp-lg-9709008}, ee = {http://arxiv.org/abs/cmp-lg/9709008}, date = {2008-01-02}, description = {dblp}, biburl = {http://www.bibsonomy.org/bibtex/275183eed0a84f9c9e0b0a170a23ec54a/minguez}, keywords = {similarity matchmaking master} } @misc{resnik95-using, title = {Using Information Content to Evaluate Semantic Similarity in a Taxonomy}, author = {Philip Resnik}, year = 1995, url = {http://www.citebase.org/abstract?id=oai:arXiv.org:cmp-lg/9511007}, lastdatemodified = {2006-09-25}, pdf = {resnik95-using.pdf}, lastname = {Resnik}, read = {notread}, own = {notown}, abstract = {This paper presents a new measure of semantic similarity in an IS-A taxonomy, based on the notion of information content. Experimental evaluation suggests that the measure performs encouragingly well (a correlation of r = 0.79 with a benchmark set of human similarity judgments, with an upper bound of r = 0.90 for human subjects performing the same task), and significantly better than the traditional edge counting approach (r = 0.66).}, biburl = {http://www.bibsonomy.org/bibtex/2454781d9c6deadeae45d0eba0d0cdf91/minguez}, keywords = {similarity matchmaking master} } @article{leacock98using, title = {Using Corpus Statistics and WordNet Relations for Sense Identification}, author = {Claudia Leacock and Martin Chodorow and George A. Miller}, journal = {Computational Linguistics}, number = 1, pages = {147-165}, volume = 24, year = 1998, url = {citeseer.ist.psu.edu/leacock98using.html}, description = {Using Corpus Statistics and WordNet Relations for Sense Identification - Leacock, Chodorow, Miller (ResearchIndex)}, biburl = {http://www.bibsonomy.org/bibtex/2a16e81a95c661887d3e6e14483efe693/minguez}, keywords = {similarity matchmaking master} } @inproceedings{wu94verbsemantics, title = {Verb Semantics and Lexical Selection}, author = {Zhibiao Wu and Martha Stone Palmer}, booktitle = {Proceedings of the 32nd. Annual Meeting of the Association for Computational Linguistics (ACL 1994)}, pages = {133-138}, year = 1994, url = {http://dblp.uni-trier.de/db/conf/acl/acl94.html#WuP94}, ee = {http://acl.ldc.upenn.edu/acl2003/main/pdfs/Fleischman.pdf}, description = {dblp}, biburl = {http://www.bibsonomy.org/bibtex/2b71e50d2998528d120b95763104ccf07/minguez}, keywords = {similarity matchmaking master} } @article{rada89metric, title = {Development and application of a metric on semantic nets}, author = {R. Rada and H. Mili and E. Bicknell and M. Blettner}, booktitle = {IEEE Transactions on Systems, Man and Cybernetics}, pages = {17-30}, volume = 19, year = 1989, url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=24528}, issn = {0018-9472}, doi = {10.1109/21.24528}, abstract = {Motivated by the properties of spreading activation and conceptual distance, the authors propose a metric, called distance, on the power set of nodes in a semantic net. Distance is the average minimum path length over all pairwise combinations of nodes between two subsets of nodes. Distance can be successfully used to assess the conceptual distance between sets of concepts when used on a semantic net of hierarchical relations. When other kinds of relationships, like `cause', are used, distance must be amended but then can again be effective. The judgements of distance significantly correlate with the distance judgements that people make and help to determine whether one semantic net is better or worse than another. The authors focus on the mathematical characteristics of distance that presents novel cases and interpretations. Experiments in which distance is applied to pairs of concepts and to sets of concepts in a hierarchical knowledge base show the power of hierarchical relations in representing information about the conceptual distance between concepts}, biburl = {http://www.bibsonomy.org/bibtex/27489a4e2594e6ec10048b740bcccb34c/minguez}, keywords = {similarity matchmaking master} } @inproceedings{agarwal-lamparter-smart-05, title = {{sMart - A Semantic Matchmaking Portal for Electronic Markets}}, address = {Munich, Germany}, author = {Sudhir Agarwal and Steffen Lamparter}, booktitle = {Proceedings of the 7th International IEEE Conference on E-Commerce Technology 2005}, month = {JUL}, publisher = {IEEE Computer Society}, year = 2005, biburl = {http://www.bibsonomy.org/bibtex/2340187a0fa89b82d55e8dfaf049160f4/minguez}, keywords = {fuzzyLogic matchmaking master} }