{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:OU2GVFTBFPUAPSJEATIYQJ2LTJ","short_pith_number":"pith:OU2GVFTB","schema_version":"1.0","canonical_sha256":"75346a96612be807c92404d188274b9a7a0b7df33e9aa9e8b26759ccebdeb0ae","source":{"kind":"arxiv","id":"1307.5894","version":1},"attestation_state":"computed","paper":{"title":"MIRAGE: An Iterative MapReduce based FrequentSubgraph Mining Algorithm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.DB","authors_text":"Mansurul A Bhuiyan, Mohammad Al Hasan","submitted_at":"2013-07-22T21:26:00Z","abstract_excerpt":"Frequent subgraph mining (FSM) is an important task for exploratory data analysis on graph data. Over the years, many algorithms have been proposed to solve this task. These algorithms assume that the data structure of the mining task is small enough to fit in the main memory of a computer. However, as the real-world graph data grows, both in size and quantity, such an assumption does not hold any longer. To overcome this, some graph database-centric methods have been proposed in recent years for solving FSM; however, a distributed solution using MapReduce paradigm has not been explored extens"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1307.5894","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2013-07-22T21:26:00Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"11366e1e93264ff1724769b989f056051556a0904e8c9ce8a4319e3cd69ee12a","abstract_canon_sha256":"0ba121cda77c0bb2bba80f1854df4dc743c10afba84f2bb759efbfcb4104844f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:17:45.859950Z","signature_b64":"tHEn8Gx2nLP9Mfk1ZzmX0emeAMuL5YhWMXV/0heY2EbFNxww06vxZ+dHZvpFxs5ziBXm4boltJjS/1DeSA/hAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"75346a96612be807c92404d188274b9a7a0b7df33e9aa9e8b26759ccebdeb0ae","last_reissued_at":"2026-05-18T03:17:45.859226Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:17:45.859226Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MIRAGE: An Iterative MapReduce based FrequentSubgraph Mining Algorithm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.DB","authors_text":"Mansurul A Bhuiyan, Mohammad Al Hasan","submitted_at":"2013-07-22T21:26:00Z","abstract_excerpt":"Frequent subgraph mining (FSM) is an important task for exploratory data analysis on graph data. Over the years, many algorithms have been proposed to solve this task. These algorithms assume that the data structure of the mining task is small enough to fit in the main memory of a computer. However, as the real-world graph data grows, both in size and quantity, such an assumption does not hold any longer. To overcome this, some graph database-centric methods have been proposed in recent years for solving FSM; however, a distributed solution using MapReduce paradigm has not been explored extens"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1307.5894","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1307.5894","created_at":"2026-05-18T03:17:45.859338+00:00"},{"alias_kind":"arxiv_version","alias_value":"1307.5894v1","created_at":"2026-05-18T03:17:45.859338+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1307.5894","created_at":"2026-05-18T03:17:45.859338+00:00"},{"alias_kind":"pith_short_12","alias_value":"OU2GVFTBFPUA","created_at":"2026-05-18T12:27:54.935989+00:00"},{"alias_kind":"pith_short_16","alias_value":"OU2GVFTBFPUAPSJE","created_at":"2026-05-18T12:27:54.935989+00:00"},{"alias_kind":"pith_short_8","alias_value":"OU2GVFTB","created_at":"2026-05-18T12:27:54.935989+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OU2GVFTBFPUAPSJEATIYQJ2LTJ","json":"https://pith.science/pith/OU2GVFTBFPUAPSJEATIYQJ2LTJ.json","graph_json":"https://pith.science/api/pith-number/OU2GVFTBFPUAPSJEATIYQJ2LTJ/graph.json","events_json":"https://pith.science/api/pith-number/OU2GVFTBFPUAPSJEATIYQJ2LTJ/events.json","paper":"https://pith.science/paper/OU2GVFTB"},"agent_actions":{"view_html":"https://pith.science/pith/OU2GVFTBFPUAPSJEATIYQJ2LTJ","download_json":"https://pith.science/pith/OU2GVFTBFPUAPSJEATIYQJ2LTJ.json","view_paper":"https://pith.science/paper/OU2GVFTB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1307.5894&json=true","fetch_graph":"https://pith.science/api/pith-number/OU2GVFTBFPUAPSJEATIYQJ2LTJ/graph.json","fetch_events":"https://pith.science/api/pith-number/OU2GVFTBFPUAPSJEATIYQJ2LTJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OU2GVFTBFPUAPSJEATIYQJ2LTJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OU2GVFTBFPUAPSJEATIYQJ2LTJ/action/storage_attestation","attest_author":"https://pith.science/pith/OU2GVFTBFPUAPSJEATIYQJ2LTJ/action/author_attestation","sign_citation":"https://pith.science/pith/OU2GVFTBFPUAPSJEATIYQJ2LTJ/action/citation_signature","submit_replication":"https://pith.science/pith/OU2GVFTBFPUAPSJEATIYQJ2LTJ/action/replication_record"}},"created_at":"2026-05-18T03:17:45.859338+00:00","updated_at":"2026-05-18T03:17:45.859338+00:00"}