{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/text-coherence-analysis-based-on-deep-neural","title":"Text Coherence Analysis Based on Deep Neural Network","arxiv_id":"1710.07770","date":"2017-10-21","proceeding":null,"authors":["Baiyun Cui","Yingming Li","Yaqing Zhang","Zhongfei Zhang"],"abstract":"In this paper, we propose a novel deep coherence model (DCM) using a\nconvolutional neural network architecture to capture the text coherence. The\ntext coherence problem is investigated with a new perspective of learning\nsentence distributional representation and text coherence modeling\nsimultaneously. In particular, the model captures the interactions between\nsentences by computing the similarities of their distributional\nrepresentations. Further, it can be easily trained in an end-to-end fashion.\nThe proposed model is evaluated on a standard Sentence Ordering task. The\nexperimental results demonstrate its effectiveness and promise in coherence\nassessment showing a significant improvement over the state-of-the-art by a\nwide margin.","url_abs":"http://arxiv.org/abs/1710.07770v1","url_pdf":"http://arxiv.org/pdf/1710.07770v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"text-coherence-analysis-based-on-deep-neural","repo_url":"https://github.com/geekSiddharth/DeepCoherence","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"sentence-ordering","task_name":"Sentence Ordering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1710.07770","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}