2026-04-17T00:48:23Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

49cd2226b244de0cbc580fe4c4a778b376a21822f5abb466020c27738d062363 2025-06-17T03:14:18Z language:enopenaire_data

DDI study level documentation for study 10.7802/1206 Comparing Vocabulary Term Recommendations using Association Rules and Learning To Rank: A User Study Comparing Vocabulary Term Recommendations using Association Rules and Learning To Rank: A User Study Comparing Vocabulary Term Recommendations using Association Rules and Learning To Rank: A User Study 10.7802/120610.7802/120610.7802/120610.7802/1206 Schaible, Johann Schaible, Johann Szekely, Pedro Szekely, Pedro Scherp, Ansgar Scherp, Ansgar GESIS Data Archive for the Social SciencesGESIS Datenarchiv für Sozialwissenschaften 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.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. DeutschlandDeutschlandVereinigte StaatenVereinigte Staaten Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.Freier Zugang (ohne Registrierung) - Die Forschungsdaten können von jedem direkt heruntergeladen werden. http://dbkapps.gesis.org/dbkoai/oai.asp oai:dbk.gesis.org:SDN/10.7802_1206 2023-03-11 ddi:codebook:2_5