{"type":"ScholarlyArticle","title":"Exploring Segment Representations for Neural Segmentation Models","authors":[{"name":"Yijia Liu","slug":"yijia-liu","given":"Yijia","family":"Liu","affiliation":""},{"name":"Wanxiang Che","slug":"wanxiang-che","given":"Wanxiang","family":"Che","affiliation":""},{"name":"Jiang Guo","slug":"jiang-guo","given":"Jiang","family":"Guo","affiliation":""},{"name":"Bing Qin","slug":"bing-qin","given":"Bing","family":"Qin","affiliation":""},{"name":"Ting Liu","slug":"ting-liu","given":"Ting","family":"Liu","affiliation":""}],"abstract":"Many natural language processing (NLP) tasks can be generalized into segmentation problem. In this paper, we combine semi-CRF with neural network to solve NLP segmentation tasks. Our model represents a segment both by composing the input units and embedding the entire segment. We thoroughly study different composition functions and different segment embeddings. We conduct extensive experiments on two typical segmentation tasks: named entity recognition (NER) and Chinese word segmentation (CWS). Experimental results show that our neural semi-CRF model benefits from representing the entire segment and achieves the state-of-the-art performance on CWS benchmark dataset and competitive results on the CoNLL03 NER dataset.","doi":null,"url":"https://ijcai.org/proceedings/2016/409","pdf":"https://ijcai.org/proceedings/2016/0409.pdf","markdown":"https://ijcai.org/proceedings/2016/409.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/409","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":409,"pages":{"first":2880,"last":2885},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}