{"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-matching-as-image-recognition","title":"Text Matching as Image Recognition","arxiv_id":"1602.06359","date":"2016-02-20","proceeding":null,"authors":["Liang Pang","Yanyan Lan","Jiafeng Guo","Jun Xu","Shengxian Wan","Xue-Qi Cheng"],"abstract":"Matching two texts is a fundamental problem in many natural language\nprocessing tasks. An effective way is to extract meaningful matching patterns\nfrom words, phrases, and sentences to produce the matching score. Inspired by\nthe success of convolutional neural network in image recognition, where neurons\ncan capture many complicated patterns based on the extracted elementary visual\npatterns such as oriented edges and corners, we propose to model text matching\nas the problem of image recognition. Firstly, a matching matrix whose entries\nrepresent the similarities between words is constructed and viewed as an image.\nThen a convolutional neural network is utilized to capture rich matching\npatterns in a layer-by-layer way. We show that by resembling the compositional\nhierarchies of patterns in image recognition, our model can successfully\nidentify salient signals such as n-gram and n-term matchings. Experimental\nresults demonstrate its superiority against the baselines.","url_abs":"http://arxiv.org/abs/1602.06359v1","url_pdf":"http://arxiv.org/pdf/1602.06359v1.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-matching-as-image-recognition","repo_url":"https://github.com/NTMC-Community/MatchZoo","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"text-matching-as-image-recognition","repo_url":"https://github.com/SJHBXShub/Question_pair","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"text-matching-as-image-recognition","repo_url":"https://github.com/jastfkjg/semantic-matching","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"text-matching-as-image-recognition","repo_url":"https://github.com/pl8787/DeepRank_PyTorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"text-matching-as-image-recognition","repo_url":"https://github.com/pl8787/MatchPyramid-TensorFlow","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"text-matching-as-image-recognition","repo_url":"https://github.com/super-zhangchao/learning-to-match","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"text-matching-as-image-recognition","repo_url":"https://github.com/PaddlePaddle/PaddleRec/tree/release/2.1.0/models/match/match-pyramid","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"paddle","reach":null}],"tasks":[{"task_slug":"ad-hoc-information-retrieval","task_name":"Ad-Hoc Information Retrieval"},{"task_slug":"text-matching","task_name":"Text Matching"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1602.06359","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}