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A Word Prediction Methodology Based on Posgrams

Chapter
Publication Date:
2017
abstract:
This work introduces a two steps methodology for the prediction of missing words in incomplete sentences. In a first step the number of candidate words is restricted to the ones fulfilling the predicted part of speech; to this aim a novel algorithm based on "posgrams" analysis is also proposed. Then, in a second step, a word prediction algorithm is applied on the reduced words set. The work quantifies the advantages in predicting a word part of speech before predicting the word itself, in terms of accuracy and execution time. The methodology can be applied in several tasks, such as Text Autocompletion, Speech Recognition and Optical Text Recognition.
Iris type:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
Word prediction; statistical NLP
List of contributors:
Spiccia, Carmelo; Pilato, Giovanni; Augello, Agnese
Authors of the University:
AUGELLO AGNESE
PILATO GIOVANNI
Handle:
https://iris.cnr.it/handle/20.500.14243/337788
Book title:
Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2015.
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