Coreferential information of a candidate, such as the properties of its antecedents, is important for pronoun resolution because it reflects the salience of the candidate in the l...
Xiaofeng Yang, Jian Su, Guodong Zhou, Chew Lim Tan
We introduce a new method for disambiguating word senses that exploits a nonlinear Kernel Principal Component Analysis (KPCA) technique to achieve accuracy superior to the best pu...
Convolution kernels, such as sequence and tree kernels, are advantageous for both the concept and accuracy of many natural language processing (NLP) tasks. Experiments have, howev...
We discuss Feature Latent Semantic Analysis (FLSA), an extension to Latent Semantic Analysis (LSA). LSA is a statistical method that is ordinarily trained on words only; FLSA adds...
Exploiting unannotated natural language data is hard largely because unsupervised parameter estimation is hard. We describe deterministic annealing (Rose et al., 1990) as an appea...
We present an algorithm for generating referring expressions in open domains. Existing algorithms work at the semantic level and assume the availability of a classification for at...
We present an approach using syntactosemantic rules for the extraction of relational information from biomedical abstracts. The results show that by overcoming the hurdle of techn...
Jasmin Saric, Lars Juhl Jensen, Peer Bork, Rossitz...
This paper presents a multi-layered Question Answering (Q.A.) architecture suitable for enhancing current Q.A. capabilities with the possibility of processing complex questions. T...
In this paper, we propose a multi-criteriabased active learning approach and effectively apply it to named entity recognition. Active learning targets to minimize the human annota...
Dan Shen, Jie Zhang, Jian Su, Guodong Zhou, Chew L...