Ge Xu


Selective Annotation of Sentence Parts: Identification of Relevant Sub-sentential Units
Ge Xu | Xiaoyan Yang | Chu-Ren Huang
Proceedings of the 12th Workshop on Asian Language Resources (ALR12)

Many NLP tasks involve sentence-level annotation yet the relevant information is not encoded at sentence level but at some relevant parts of the sentence. Such tasks include but are not limited to: sentiment expression annotation, product feature annotation, and template annotation for Q&A systems. However, annotation of the full corpus sentence by sentence is resource intensive. In this paper, we propose an approach that iteratively extracts frequent parts of sentences for annotating, and compresses the set of sentences after each round of annotation. Our approach can also be used in preparing training sentences for binary classification (domain-related vs. noise, subjectivity vs. objectivity, etc.), assuming that sentence-type annotation can be predicted by annotation of the most relevant sub-sentences. Two experiments are performed to test our proposal and evaluated in terms of time saved and agreement of annotation.


An Analysis of Radicals-based Features in Subjectivity Classification on Simplified Chinese Sentences
Ge Xu | Churen Huang
Proceedings of the 28th Pacific Asia Conference on Language, Information and Computing


Cross-Lingual Mixture Model for Sentiment Classification
Xinfan Meng | Furu Wei | Xiaohua Liu | Ming Zhou | Ge Xu | Houfeng Wang
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Lost in Translations? Building Sentiment Lexicons using Context Based Machine Translation
Xinfan Meng | Furu Wei | Ge Xu | Longkai Zhang | Xiaohua Liu | Ming Zhou | Houfeng Wang
Proceedings of COLING 2012: Posters


Build Chinese Emotion Lexicons Using A Graph-based Algorithm and Multiple Resources
Ge Xu | Xinfan Meng | Houfeng Wang
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)