Similar to ( Li et al. , 2013a ) , our summarization system is , which consists of three key components : an initial sentence pre-selection module to select some important sentence candidates ; the above compression model to generate n-best compressions for each sentence ; and then an ILP summarization method to select the best summary sentences from the multiple compressed sentences .
document summarization via guided sentence compression
Chen Li Fei Liu Fuliang Weng Yang Liu
Similar to ( Li et al. , 2013a ) , our summarization system is , which consists of three key components : an initial sentence pre-selection module to select some important sentence candidates ; the above compression model to generate n-best compressions for each sentence ; and then an ILP summarization method to select the best summary sentences from the multiple compressed sentences . The sentence pre-selection model is a simple supervised support vector regression ( SVR ) model that predicts a salience score for each sentence and selects the top ranked sentences for further processing ( compression and summarization ) .
Similar to ( @@CITATIONa ) , our summarization system is , which consists of three key components : an initial sentence pre-selection module to select some important sentence candidates ; the above compression model to generate n-best compressions for each sentence ; and then an ILP summarization method to select the best summary sentences from the multiple compressed sentences .