{"paper":{"title":"Constructing Adjacency Arrays from Incidence Arrays","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DM","math.CO"],"primary_cat":"cs.DS","authors_text":"Hayden Jananthan, Jeremy Kepner, Karia Dibert","submitted_at":"2017-02-25T04:13:22Z","abstract_excerpt":"Graph construction, a fundamental operation in a data processing pipeline, is typically done by multiplying the incidence array representations of a graph, $\\mathbf{E}_\\mathrm{in}$ and $\\mathbf{E}_\\mathrm{out}$, to produce an adjacency array of the graph, $\\mathbf{A}$, that can be processed with a variety of algorithms. This paper provides the mathematical criteria to determine if the product $\\mathbf{A} = \\mathbf{E}^{\\sf T}_\\mathrm{out}\\mathbf{E}_\\mathrm{in}$ will have the required structure of the adjacency array of the graph. The values in the resulting adjacency array are determined by the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.07832","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}