{"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/dependency-based-convolutional-neural","title":"Dependency-based Convolutional Neural Networks for Sentence Embedding","arxiv_id":"1507.01839","date":"2015-07-07","proceeding":"IJCNLP 2015 7","authors":["Mingbo Ma","Liang Huang","Bing Xiang","Bo-Wen Zhou"],"abstract":"In sentence modeling and classification, convolutional neural network\napproaches have recently achieved state-of-the-art results, but all such\nefforts process word vectors sequentially and neglect long-distance\ndependencies. To exploit both deep learning and linguistic structures, we\npropose a tree-based convolutional neural network model which exploit various\nlong-distance relationships between words. Our model improves the sequential\nbaselines on all three sentiment and question classification tasks, and\nachieves the highest published accuracy on TREC.","url_abs":"http://arxiv.org/abs/1507.01839v2","url_pdf":"http://arxiv.org/pdf/1507.01839v2.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":"dependency-based-convolutional-neural","repo_url":"https://github.com/cosmmb/DCNN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"all","task_name":"All"},{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"sentence-embedding","task_name":"Sentence Embedding"},{"task_slug":"sentence-embedding-1","task_name":"Sentence-Embedding"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}