TermPicker: Enabling the Reuse of Vocabulary Terms by Exploiting Data from the Linked Open Data Cloud

author: Johann Schaible, GESIS - Leibniz Institute for the Social Sciences
published: July 28, 2016,   recorded: June 2016,   views: 1293


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


Deciding which RDF vocabulary terms to use when modeling data as Linked Open Data (LOD) is far from trivial. In this paper, we propose TermPicker as a novel approach enabling vocabulary reuse by recommending vocabulary terms based on various features of a term. These features include the term’s popularity, whether it is from an already used vocabulary, and the so-called schema-level pattern (SLP) feature that exploits which terms other data providers on the LOD cloud use to describe their data. We apply Learning To Rank to establish a ranking model for vocabulary terms based on the utilized features. The results show that using the SLP-feature improves the recommendation quality by 29–36 % considering the Mean Average Precision and the Mean Reciprocal Rank at the first five positions compared to recommendations based on solely the term’s popularity and whether it is from an already used vocabulary.

See Also:

Download slides icon Download slides: eswc2016_schaible_open_data_01.pdf (2.2 MB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: