{"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/cross-device-matching-for-online-advertising","title":"Cross Device Matching for Online Advertising with Neural Feature Ensembles : First Place Solution at CIKM Cup 2016","arxiv_id":"1610.07119","date":"2016-10-23","proceeding":null,"authors":["Minh C. Phan","Yi Tay","Tuan-Anh Nguyen Pham"],"abstract":"We describe the 1st place winning approach for the CIKM Cup 2016 Challenge.\nIn this paper, we provide an approach to reasonably identify same users across\nmultiple devices based on browsing logs. Our approach regards a candidate\nranking problem as pairwise classification and utilizes an unsupervised neural\nfeature ensemble approach to learn latent features of users. Combined with\ntraditional hand crafted features, each user pair feature is fed into a\nsupervised classifier in order to perform pairwise classification. Lastly, we\npropose supervised and unsupervised inference techniques.","url_abs":"http://arxiv.org/abs/1610.07119v2","url_pdf":"http://arxiv.org/pdf/1610.07119v2.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":"cross-device-matching-for-online-advertising","repo_url":"https://github.com/vanzytay/cikm_cup","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}