{"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/an-information-theoretic-framework-for-the","title":"An Information-theoretic Framework for the Lossy Compression of Link Streams","arxiv_id":"1807.06874","date":"2018-07-18","proceeding":null,"authors":["Robin Lamarche-Perrin"],"abstract":"Graph compression is a data analysis technique that consists in the\nreplacement of parts of a graph by more general structural patterns in order to\nreduce its description length. It notably provides interesting exploration\ntools for the study of real, large-scale, and complex graphs which cannot be\ngrasped at first glance. This article proposes a framework for the compression\nof temporal graphs, that is for the compression of graphs that evolve with\ntime. This framework first builds on a simple and limited scheme, exploiting\nstructural equivalence for the lossless compression of static graphs, then\ngeneralises it to the lossy compression of link streams, a recent formalism for\nthe study of temporal graphs. Such generalisation relies on the natural\nextension of (bidimensional) relational data by the addition of a third\ntemporal dimension. Moreover, we introduce an information-theoretic measure to\nquantify and to control the information that is lost during compression, as\nwell as an algebraic characterisation of the space of possible compression\npatterns to enhance the expressiveness of the initial compression scheme. These\ncontributions lead to the definition of a combinatorial optimisation problem,\nthat is the Lossy Multistream Compression Problem, for which we provide an\nexact algorithm.","url_abs":"http://arxiv.org/abs/1807.06874v1","url_pdf":"http://arxiv.org/pdf/1807.06874v1.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":"an-information-theoretic-framework-for-the","repo_url":"https://github.com/Lamarche-Perrin/greedy-graph-compression","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"an-information-theoretic-framework-for-the","repo_url":"https://github.com/Lamarche-Perrin/multidimensional_compression","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}