http://www.cnr.it/ontology/cnr/individuo/prodotto/ID44358
On tag spell checking (Contributo in atti di convegno)
- Type
- Label
- On tag spell checking (Contributo in atti di convegno) (literal)
- Anno
- 2010-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1007/978-3-642-16321-0_4 (literal)
- Alternative label
Frieder O., Nardini F. M., Silvestri F., Vahabi H., Vahabi P. (2010)
On tag spell checking
in SPIRE 2010 - String Processing and Information Retrieval. 17th International Symposium, Los Cabos, Mexico, 11-13 October 2010
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Frieder O., Nardini F. M., Silvestri F., Vahabi H., Vahabi P. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.springerlink.com/content/d0pk6m0058r7321j/ (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
- In: SPIRE 2010 - String Processing and Information Retrieval. 17th International Symposium (Los Cabos, Mexico, 11-13 October 2010). Proceedings, pp. 37 - 42. Edgar Chavez, Stefano Lonardi (eds.). (Lecture Notes in Computer Science, vol. 6393). Springer, 2010. (literal)
- Note
- Scopu (literal)
- PuMa (literal)
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Department of Computer Science, Georgetown University, Washington DC, USA; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; IMT, Lucca, Italy; University of Modena and Reggio Emilia, Modena, Italy (literal)
- Titolo
- On tag spell checking (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-3-642-16321-0 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
- Edgar Chavez, Stefano Lonardi (literal)
- Abstract
- Exploiting the cumulative behavior of users is a common technique used to improve many popular online services. We build a tag spell checker using a graph-based model. In particular, we present a novel technique based on the graph of tags associated with objects made available by online sites such as Flickr and YouTube. We show the effectiveness of our approach on the basis of an experimentation done on real-world data. We show a precision of up to 93% with a recall (i.e., the number of errors detected) of up to 100%. (literal)
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