{"url":"/method/grlia","slug":"grlia","name":"GRLIA","full_name":"GRLIA","full_name_withheld":false,"description_markdown":"**GRLIA** is an incident aggregation framework for online service systems based on graph representation learning over the cascading graph of cloud failures. A representation vector is learned for each unique type of incident in an unsupervised and unified manner, which is able to simultaneously encode the topological and temporal correlations among incidents.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"https://arxiv.org/abs/2108.12179v1","title":"Graph-based Incident Aggregation for Large-Scale Online Service Systems","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Incident Aggregation Models","url":"/methods/category/incident-aggregation-models","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":null,"papers_newest_first":[{"paper":"/paper/graph-based-incident-aggregation-for-large","title":"Graph-based Incident Aggregation for Large-Scale Online Service Systems","date":"2021-08-27","arxiv_id":"2108.12179","n_code_links":1,"syntology":null}],"papers_shown":1,"tasks":[{"task":"/task/graph-representation-learning","name":"Graph Representation Learning","papers":1},{"task":"/task/management","name":"Management","papers":1},{"task":"/task/representation-learning","name":"Representation Learning","papers":1}],"tasks_shown":3,"n_tasks":3,"usage_by_year":[{"year":"2021","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/grlia"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}