Abstract | ||
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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 promissory score of 90% of unexpectedness for real-world scenarios in the music domain. |
Year | DOI | Venue |
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2017 | 10.1007/978-3-319-59536-8_31 | ADVANCED INFORMATION SYSTEMS ENGINEERING (CAISE 2017) |
Keywords | Field | DocType |
Serendipity,Linked data,Information retrieval | Data mining,Information retrieval,Computer science,Linked data,Calculus,Serendipity | Conference |
Volume | ISSN | Citations |
10253 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 14 | 9 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jeronimo S. A. Eichler | 1 | 1 | 0.37 |
Marco A. Casanova | 2 | 1007 | 979.09 |
Antonio L. Furtado | 3 | 704 | 917.22 |
Lívia Ruback | 4 | 10 | 1.93 |
Luiz André P. Paes Leme | 5 | 90 | 13.81 |
Giseli Rabello Lopes | 6 | 107 | 16.44 |
Bernardo Pereira Nunes | 7 | 185 | 30.96 |
Alessandra Raffaetà | 8 | 187 | 16.45 |
Chiara Renso | 9 | 925 | 76.04 |