{"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/hyperdoc2vec-distributed-representations-of","title":"hyperdoc2vec: Distributed Representations of Hypertext Documents","arxiv_id":"1805.03793","date":"2018-05-10","proceeding":"ACL 2018 7","authors":["Jialong Han","Yan Song","Wayne Xin Zhao","Shuming Shi","Haisong Zhang"],"abstract":"Hypertext documents, such as web pages and academic papers, are of great\nimportance in delivering information in our daily life. Although being\neffective on plain documents, conventional text embedding methods suffer from\ninformation loss if directly adapted to hyper-documents. In this paper, we\npropose a general embedding approach for hyper-documents, namely, hyperdoc2vec,\nalong with four criteria characterizing necessary information that\nhyper-document embedding models should preserve. Systematic comparisons are\nconducted between hyperdoc2vec and several competitors on two tasks, i.e.,\npaper classification and citation recommendation, in the academic paper domain.\nAnalyses and experiments both validate the superiority of hyperdoc2vec to other\nmodels w.r.t. the four criteria.","url_abs":"http://arxiv.org/abs/1805.03793v1","url_pdf":"http://arxiv.org/pdf/1805.03793v1.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":"hyperdoc2vec-distributed-representations-of","repo_url":"https://github.com/HelloRusk/hyperdoc2vec","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"citation-recommendation","task_name":"Citation Recommendation"},{"task_slug":"document-embedding","task_name":"Document Embedding"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.03793","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}