Title :
Notice of Retraction
Chinese subjectivity analysis using bilingual knowledge and adaptation technology
Author :
Rongjun Li ; Yuan Kuang ; Xiaojie Wang
Author_Institution :
Center of Intell. Sci. Technol. Res., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Research in opinion analysis have drawn a great attention these days. Many of the effective opinion analysis system are based on supervised learning technology. However there lack of annotation sentiment corpora for Chinese opinion analysis. The purpose of our work is try to make use of annotation English corpora, where are rich and reliable to improve opinion analysis in Chinese. We propose a approach that to construct Chinese corpora by translating English corpora using different translation engines, as well as introducing domain adaption technique and meta-learning framework in order to improve the accuracy and stability of identifying subjective sentences. Through comparative evaluation with upper bound, we show the effectiveness of the proposed method.
Keywords :
learning (artificial intelligence); natural language processing; Chinese subjectivity analysis; adaptation technology; annotation English corpora; annotation sentiment corpora; bilingual knowledge; meta-learning framework; opinion analysis; translation engines; Book reviews; Engines; Natural language processing; Stability analysis; Supervised learning; Testing; Training; bilingual knowledge; domain adaptation; natural language processing; opinion analysis;
Conference_Titel :
Web Society (SWS), 2010 IEEE 2nd Symposium on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6356-5
DOI :
10.1109/SWS.2010.5607432