The Linked Data Mining Challenge 2016

The 2015 edition of the Linked Data Mining Challenge, con- ducted in conjunction with Know@LOD 2015, has been the third edition of this challenge. This year's dataset collected movie ratings, where the task was to classify well and badly rated movies. The solutions submitted reached an accuracy of almost 95%, which is a clear advancement over the baseline of 60%. However, there is still headroom for improvement, as the majority vote of the three best systems reaches an even higher accuracy.

[1]  Meyer A. Bossert.  Predicting Metacritic Film Reviews Using Linked Open Data and Semantic Technologies , 2015, KNOW@LOD.

[2]  Trevor Darrell,et al.  Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.

[3]  Heiko Paulheim,et al.  Adoption of the Linked Data Best Practices in Different Topical Domains , 2014, SEMWEB.

[4]  Vojtech Svátek,et al.  Linked Data Mining Challenge (LDMC) 2013 Summary , 2013, DMoLD.

[5]  Anna Lisa Gentile,et al.  Can You Judge a Music Album by its Cover? , 2016, @ESWC.

[6]  Heiko Paulheim,et al.  Mining the Web of Linked Data with RapidMiner , 2015, J. Web Semant..

[7]  Jedrzej Potoniec.  Not-So-Linked Solution to the Linked Data Mining Challenge 2016 , 2016, @ESWC.

[8]  Jens Lehmann,et al.  DBpedia - A large-scale, multilingual knowledge base extracted from Wikipedia , 2015, Semantic Web.

[9]  Halife Kodaz,et al.  A Hybrid Method for Rating Prediction Using Linked Data Features and Text Reviews , 2016, @ESWC.

[10]  Heiko Paulheim,et al.  Data Mining with Background Knowledge from the Web , 2014 .

[11]  Emir Muñoz,et al.  A Linked Data-Based Decision Tree Classifier to Review Movies , 2015, KNOW@LOD.

[12]  Johann Schaible,et al.  Utilizing the Open Movie Database API for Predicting the Review Class of Movies , 2015, KNOW@LOD.

[13]  Jacob Cohen,et al.  The Equivalence of Weighted Kappa and the Intraclass Correlation Coefficient as Measures of Reliability , 1973 .

[14]  Heiko Paulheim.  Exploiting Linked Open Data as Background Knowledge in Data Mining , 2013, DMoLD.

[15]  Heiko Paulheim,et al.  The Linked Data Mining Challenge 2014: Results and Experiences , 2014, KNOW@LOD.