{"type":"ScholarlyArticle","title":"Character-Based Parsing with Convolutional Neural Network","authors":[{"name":"Xiaoqing Zheng","slug":"xiaoqing-zheng","given":"Xiaoqing","family":"Zheng","affiliation":""},{"name":"Haoyuan Peng","slug":"haoyuan-peng","given":"Haoyuan","family":"Peng","affiliation":""},{"name":"Yi Chen","slug":"yi-chen","given":"Yi","family":"Chen","affiliation":""},{"name":"Pengjing Zhang","slug":"pengjing-zhang","given":"Pengjing","family":"Zhang","affiliation":""},{"name":"Wenqiang Zhang","slug":"wenqiang-zhang","given":"Wenqiang","family":"Zhang","affiliation":""}],"abstract":"We describe a novel convolutional neural network architecture with k-max pooling layer that is able to successfully recover the structure of Chinese sentences. This network can capture active features for unseen segments of a sentence to measure how likely the segments are merged to be the constituents. Given an input sentence, after all the scores of possible segments are computed, an efficient dynamic programming parsing algorithm is used to find the globally optimal parse tree. A similar network is then applied to predict syntactic categories for every node in the parse tree. Our networks archived competitive performance to existing benchmark parsers on the CTB-5 dataset without any task-specific feature engineering.","doi":null,"url":"https://ijcai.org/proceedings/2015/153","pdf":"https://ijcai.org/proceedings/2015/0153.pdf","markdown":"https://ijcai.org/proceedings/2015/153.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/153","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Machine Learning","track":"Main Track","number":153,"pages":{"first":1054,"last":1059},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}