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

Version
1
Resource Type
Dataset
Creator
- Schaible, Johann (GESIS)
- Szekely, Pedro (USC Information Science Institute)
- Scherp, Ansgar (Kiel University and ZBW)
Publication Date
2016
Classification
- ZA:
- Technology, Energy
Description
-
Abstract
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.
Temporal Coverage
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2015-11-01 / 2016-01-31
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2015-11-01 / 2016-01-31
Geographic Coverage
-
Germany / DE
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United States / US
Data and File Information
-
-
File Name:
termpickerSurvey.pdf
File Format: application/pdf
File Size: 450167
Data Fingerprint: a917a4fdf7d230dab405b8b1ab26ab33
Method Fingerprint: MD5
-
File Name:
termpickerSurvey.pdf
-
-
File Name:
termpickerSurvey.pdf
File Format: application/pdf
File Size: 450167
Data Fingerprint: a917a4fdf7d230dab405b8b1ab26ab33
Method Fingerprint: MD5
-
File Name:
termpickerSurvey.pdf
-
-
File Name:
data_project_700359_2016_02_29.sav
File Format: application/x-spss-sav
File Size: 37398
Data Fingerprint: fc736d4cfa32561372eb8e16e9e30f16
Method Fingerprint: MD5
-
File Name:
data_project_700359_2016_02_29.sav
-
-
File Name:
data_project_700359_2016_02_29.sav
File Format: application/x-spss-sav
File Size: 37398
Data Fingerprint: fc736d4cfa32561372eb8e16e9e30f16
Method Fingerprint: MD5
-
File Name:
data_project_700359_2016_02_29.sav
Availability
Download
Free Access (without Registration)
Publications
-
Comparing Vocabulary Term Recommendations using Association Rules and Learning To Rank: A User Study;
Update Metadata: 2019-10-01 | Issue Number: 3 | Registration Date: 2016-03-02