Word Sense Induction (WSI) usually relies on data structures built upon the words to be disambiguated. This is a time-consuming process that requires a huge computational effort. In this paper, we propose an approach to automatically build a generic sense inventory (called iSC) to be used as a reference for disambiguation. The sense inventory is built extracting insight from Big Data exploiting a community detection algorithm. Since generate taking into account large corpora of data, the iSCis independent of the domain of application and of predefined target words.

Using Big Data to Support Automatic Word Sense Disambiguation / Guerra, Francesco; Simonini, Giovanni. - STAMPA. - (2014), pp. 311-314. ((Intervento presentato al convegno Conference on High Performance Computing & Simulation tenutosi a Bologna nel 21 25 July 2014.

Using Big Data to Support Automatic Word Sense Disambiguation

GUERRA, Francesco;SIMONINI, GIOVANNI
2014

Abstract

Word Sense Induction (WSI) usually relies on data structures built upon the words to be disambiguated. This is a time-consuming process that requires a huge computational effort. In this paper, we propose an approach to automatically build a generic sense inventory (called iSC) to be used as a reference for disambiguation. The sense inventory is built extracting insight from Big Data exploiting a community detection algorithm. Since generate taking into account large corpora of data, the iSCis independent of the domain of application and of predefined target words.
Conference on High Performance Computing & Simulation
Bologna
21 25 July 2014
311
314
Guerra, Francesco; Simonini, Giovanni
Using Big Data to Support Automatic Word Sense Disambiguation / Guerra, Francesco; Simonini, Giovanni. - STAMPA. - (2014), pp. 311-314. ((Intervento presentato al convegno Conference on High Performance Computing & Simulation tenutosi a Bologna nel 21 25 July 2014.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1038916
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