Comparing Vocabulary Term Recommendations using Association Rules and Learning To Rank: A User Study

Johann Schaible, Pedro Szekely & Ansgar Scherp
The user-study evaluates a vocabulary term recommendation service that is based on how other data providers have used RDF classes and properties in the Linked Open Data cloud. The study compares the machine learning technique Learning to Rank (L2R), the classical data mining approach Association Rule mining (AR), and a baseline that does not provide any recommendations. This data collection comprises the raw results of this user-study in SPSS format.
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