2017
Conference article  Open Access

Searching linked data with a twist of serendipity

Eichler J. S. A., Casanova M. A., Furtado A. L., Ruback L., Leme L. A. P. P., Lopes G. R., Pereira Nunes B., Raffaetà A., Renso C.

Serendipity  Settore INF/01 - Informatica  SPARQL query  Linked Data  Information Retrieval 

Serendipity is defined as the discovery of a thing when one is not searching for it. In other words, serendipity means the discovery of information that provides valuable insights by unveiling previously unknown knowledge. This paper focuses on the problem of Linked Data serendipitous search. It first discusses how to capture a set of serendipity patterns in the context of Linked Data. Then, the paper introduces a Linked Data serendipitous search application, called the Serendipity Over Linked Data Search tool - SOL-Tool. Finally, the paper describes experiments with the tool to illustrate the serendipity effect using DBpedia. The experimental results present a prom-issory score of 90% of unexpectedness for real-world scenarios of the mu-sic domain

Source: CAiSE 2017 - Advanced Information Systems Engineering 29th International Conference, pp. 495–510, Essen, Germany, 12-16 June 2017


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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:384699,
	title = {Searching linked data with a twist of serendipity},
	author = {Eichler J. S. A. and Casanova M. A. and Furtado A. L. and Ruback L. and Leme L. A. P. P. and Lopes G. R. and Pereira Nunes B. and Raffaetà A. and Renso C.},
	doi = {10.1007/978-3-319-59536-8_31},
	booktitle = {CAiSE 2017 - Advanced Information Systems Engineering 29th International Conference, pp. 495–510, Essen, Germany, 12-16 June 2017},
	year = {2017}
}