Evaluating similarity measures for emergent semantics of social tagging
By Benjamin Markines, Ciro Cattuto, Filippo Menczer, Dominik Benz, Andreas Hotho, Gerd Stumme. The Web Conference, 2009
337 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/b707332e6c03495e3448a07809a28e386a8e4ce6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Filippo Menczer
- Alessandro Flammini
- Lora Aroyo
- Chris Welty
- Alessandro Vespignani
- L. Weng
- Marián Boguñá
- Dmitri V. Krioukov
In Information Systems
- Filippo Menczer
- Alessandro Flammini
- Marián Boguñá
- Dmitri V. Krioukov
- Fragkiskos Papadopoulos
- Emilio Ferrara
- Kristina Lerman
- David M. Beskow
Citations in the corpus
- Popularity versus similarity in growing networks (2011, background): “In similarity-based models, for example, such validation is difficult because there are too many different similarity measures, and it is usually unclear which one should be used in which case [22, 69], so that cases where model predictions are validated directly against real-world similarity data [”
- Truth Is a Lie: Crowd Truth and the Seven Myths of Human Annotation (2015, background): “In Markines et al. (2009), an approach to finding the similarity between folksonomies is proposed, which also breaks up the problem according to the triangle of reference (figure 3).”
- Competition among memes in a world with limited attention (2012, methodology): “We turn to the Maximum Information Path similarity measur”