{"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/biasedwalk-biased-sampling-for-representation","title":"BiasedWalk: Biased Sampling for Representation Learning on Graphs","arxiv_id":"1809.02482","date":"2018-09-07","proceeding":null,"authors":["Duong Nguyen","Fragkiskos D. Malliaros"],"abstract":"Network embedding algorithms are able to learn latent feature representations\nof nodes, transforming networks into lower dimensional vector representations.\nTypical key applications, which have effectively been addressed using network\nembeddings, include link prediction, multilabel classification and community\ndetection. In this paper, we propose BiasedWalk, a scalable, unsupervised\nfeature learning algorithm that is based on biased random walks to sample\ncontext information about each node in the network. Our random-walk based\nsampling can behave as Breath-First-Search (BFS) and Depth-First-Search (DFS)\nsamplings with the goal to capture homophily and role equivalence between the\nnodes in the network. We have performed a detailed experimental evaluation\ncomparing the performance of the proposed algorithm against various baseline\nmethods, on several datasets and learning tasks. The experiment results show\nthat the proposed method outperforms the baseline ones in most of the tasks and\ndatasets.","url_abs":"http://arxiv.org/abs/1809.02482v1","url_pdf":"http://arxiv.org/pdf/1809.02482v1.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":"biasedwalk-biased-sampling-for-representation","repo_url":"https://github.com/duong18/BiasedWalk","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"community-detection","task_name":"Community Detection"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"link-prediction","task_name":"Link Prediction"},{"task_slug":"network-embedding","task_name":"Network Embedding"},{"task_slug":"node-classification","task_name":"Node Classification"},{"task_slug":"representation-learning","task_name":"Representation Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}