2 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.CL2019★ 1 cited
On Semi-Supervised Multiple Representation Behavior Learning
Ruqian Lu, Shengluan Hou
We propose a novel paradigm of semi-supervised learning (SSL)--the semi-supervised multiple representation behavior learning (SSMRBL). SSMRBL aims to tackle the difficulty of learn…
cs.CL2019★ 2 cited
Knowledge-guided Unsupervised Rhetorical Parsing for Text Summarization
Shengluan Hou, Ruqian Lu
Automatic text summarization (ATS) has recently achieved impressive performance thanks to recent advances in deep learning and the availability of large-scale corpora. To make the…
cs.CL2019
Attributed Rhetorical Structure Grammar for Domain Text Summarization
Ruqian Lu, Shengluan Hou, Chuanqing Wang +3
This paper presents a new approach of automatic text summarization which combines domain oriented text analysis (DoTA) and rhetorical structure theory (RST) in a grammar form: the…