| 3 |
Entity Linking meets Word Sense Disambiguation: A Unified Approach
|
|
|
|
In: http://wwwusers.di.uniroma1.it/~navigli/pubs/TACL_2014_Babelfy.pdf (2014)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
A robust approach to aligning heterogeneous lexical resources.
|
|
|
|
In: http://acl2014.org/acl2014/P14-1/pdf/P14-1044.pdf (2014)
|
|
BASE
|
|
Show details
|
|
|
| 5 |
Multilingual word sense disambiguation and entity linking for everybody
|
|
|
|
In: http://ceur-ws.org/Vol-1272/paper_30.pdf (2014)
|
|
BASE
|
|
Show details
|
|
|
| 6 |
Spred: Large-scale harvesting of semantic predicates
|
|
|
|
In: http://wing.comp.nus.edu.sg/~antho/P/P13/P13-1120v2.pdf (2013)
|
|
BASE
|
|
Show details
|
|
|
| 7 |
Clustering and diversifying Web search results with graph-based Word Sense Induction
|
|
|
|
In: http://wwwusers.di.uniroma1.it/~navigli/pubs/CL_2013_DiMarco_Navigli.pdf (2013)
|
|
BASE
|
|
Show details
|
|
|
| 8 |
Clustering and diversifying Web search results with graph-based Word Sense Induction
|
|
|
|
In: http://wing.comp.nus.edu.sg/~antho/J/J13/J13-3008.pdf (2013)
|
|
BASE
|
|
Show details
|
|
|
| 9 |
SPred: Large-scale Harvesting of Semantic Predicates
|
|
|
|
In: http://aclweb.org/anthology/P/P13/P13-1120.pdf (2013)
|
|
BASE
|
|
Show details
|
|
|
| 10 |
SemEval-2013 Task 12: Multilingual Word Sense Disambiguation
|
|
|
|
In: http://wwwusers.di.uniroma1.it/%7Enavigli/pubs/Semeval_2013_Navigli_etal.pdf (2013)
|
|
BASE
|
|
Show details
|
|
|
| 11 |
GlossBoot: Bootstrapping multilingual domain glossaries from the Web
|
|
|
|
In: http://aclweb.org/anthology/P/P13/P13-1052.pdf (2013)
|
|
BASE
|
|
Show details
|
|
|
| 12 |
BabelNet goes to the (Multilingual) Semantic Web
|
|
|
|
In: http://wwwusers.di.uniroma1.it/~navigli/pubs/MSW_2012_Navigli.pdf (2012)
|
|
BASE
|
|
Show details
|
|
|
| 13 |
A Quick Tour of Word Sense Disambiguation, Induction and Related Approaches
|
|
|
|
In: http://www.dsi.uniroma1.it/%7Enavigli/pubs/SOFSEM_2012_Navigli.pdf (2012)
|
|
BASE
|
|
Show details
|
|
|
| 14 |
BabelNetXplorer: a platform for multilingual lexical knowledge base access and exploration, in: Companion Volume to the
|
|
|
|
In: http://www2012.wwwconference.org/proceedings/companion/p393.pdf (2012)
|
|
BASE
|
|
Show details
|
|
|
| 15 |
BabelNetXplorer: A Platform for Multilingual Lexical Knowledge Base Access and Exploration ABSTRACT
|
|
|
|
In: http://www.dsi.uniroma1.it/%7Enavigli/pubs/WWW2012_Navigli_Ponzetto.pdf (2012)
|
|
BASE
|
|
Show details
|
|
|
| 16 |
An Experimental Study of Graph Connectivity for Unsupervised Word Sense Disambiguation
|
|
|
|
In: http://wwwusers.di.uniroma1.it/~navigli/pubs/PAMI_2010_Navigli_Lapata.pdf (2010)
|
|
BASE
|
|
Show details
|
|
|
| 17 |
BabelNet: Building a Very Large Multilingual Semantic Network
|
|
|
|
In: http://lcl.uniroma1.it/babelnet/papers/navigli_ponzetto_acl_2010.pdf (2010)
|
|
BASE
|
|
Show details
|
|
|
| 18 |
BabelNet: Building a very large multilingual semantic network
|
|
|
|
In: http://www.dsi.uniroma1.it/%7Enavigli/pubs/ACL_2010_Navigli_Ponzetto.pdf (2010)
|
|
BASE
|
|
Show details
|
|
|
| 19 |
An Experimental Study of Graph Connectivity for Unsupervised Word Sense Disambiguation
|
|
|
|
In: http://www.dsi.uniroma1.it/~navigli/pubs/PAMI_2010_Navigli_Lapata.pdf (2010)
|
|
Abstract:
Word sense disambiguation (WSD), the task of identifying the intended meanings (senses) of words in context, has been a long-standing research objective for natural language processing. In this paper, we are concerned with graph-based algorithms for large-scale WSD. Under this framework, finding the right sense for a given word amounts to identifying the most “important” node among the set of graph nodes representing its senses. We introduce a graph-based WSD algorithm which has few parameters and does not require sense-annotated data for training. Using this algorithm, we investigate several measures of graph connectivity with the aim of identifying those best suited for WSD. We also examine how the chosen lexicon and its connectivity influences WSD performance. We report results on standard data sets and show that our graph-based approach performs comparably to the state of the art.
|
|
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.154.2514
http://www.dsi.uniroma1.it/~navigli/pubs/PAMI_2010_Navigli_Lapata.pdf
|
|
BASE
|
|
Hide details
|
|
|
| 20 |
Using Cycles and Quasi-Cycles to disambiguate dictionary glosses
|
|
|
|
In: http://www.aclweb.org/anthology/E/E09/E09-1068.pdf (2009)
|
|
BASE
|
|
Show details
|
|
|
|
|
