Title :
New word detection and emotional tendency judgment based on mixed model
Author :
Xiao Sun ; Chongyuan Sun ; Fuji Ren
Author_Institution :
Sch. of Comput. & Inf., Hefei Univ. of Technol., Hefei, China
Abstract :
The paper studies a new method for Chinese new word detection and emotional tendency judgment based on mixed model and proposes a new word generation framework. First we construct conditional random fields (CRFs) to recognize the new words, lead-in features based on character combined with the crowd sourcing network dictionary. And then express word as a word vector based on neural network language model (NNLM) to judge the new word emotional tendency. The experimental results show that the method can improve the precision and recall of the new word detection with a good system performance, and it also provides a new way for forecasting the public mood.
Keywords :
natural language processing; neural nets; text analysis; word processing; CRF; Chinese new word detection; NNLM; conditional random fields; crowd sourcing network dictionary; mixed model; neural network language model; new word emotional tendency judgment; new word generation framework; precision; public mood forecasting; recall; Artificial neural networks; Dictionaries; Lead; Rain; Training; Conditional Random Fields; Emotional Tendency Judgment; Neural Network Language Model; New Word Detection;
Conference_Titel :
Cloud Computing and Intelligence Systems (CCIS), 2014 IEEE 3rd International Conference on
Print_ISBN :
978-1-4799-4720-1
DOI :
10.1109/CCIS.2014.7175714