{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:4KAVZ7YOU5GOPBY66UPHUIAEAG","short_pith_number":"pith:4KAVZ7YO","schema_version":"1.0","canonical_sha256":"e2815cff0ea74ce7871ef51e7a2004019f80a1ddbcdbf70cb52afbc05322dd75","source":{"kind":"arxiv","id":"1809.04365","version":3},"attestation_state":"computed","paper":{"title":"Predicting citation counts based on deep neural network learning techniques","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SI"],"primary_cat":"cs.DL","authors_text":"Ali Abrishami, Sadegh Aliakbary","submitted_at":"2018-09-12T11:41:05Z","abstract_excerpt":"With the growing number of published scientific papers world-wide, the need to evaluation and quality assessment methods for research papers is increasing. Scientific fields such as scientometrics, informetrics and bibliometrics establish quantified analysis methods and measurements for scientific papers. In this area, an important problem is to predict the future influence of a published paper. Particularly, early discrimination between influential papers and insignificant papers may find important applications. In this regard, one of the most important metrics is the number of citations to t"},"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":"1809.04365","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DL","submitted_at":"2018-09-12T11:41:05Z","cross_cats_sorted":["cs.LG","cs.SI"],"title_canon_sha256":"7e34a4db1f96faed53ea2ccf2fcb591e619eba5bca62f7c61de761c53285c0fe","abstract_canon_sha256":"813b74ddf1920daae3ab4e99fd12ff110fd04aea1950dd8c8de06ddf78f5111b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:09.609756Z","signature_b64":"2d324jzeGxO3XRri8cpGEjpJ38S1iNvcBSYzViTmMtlJgYP+umA2hwiaxBvXyXBNUUGTKPPsEGdlPW1JbX+BCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e2815cff0ea74ce7871ef51e7a2004019f80a1ddbcdbf70cb52afbc05322dd75","last_reissued_at":"2026-05-17T23:51:09.609208Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:09.609208Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Predicting citation counts based on deep neural network learning techniques","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SI"],"primary_cat":"cs.DL","authors_text":"Ali Abrishami, Sadegh Aliakbary","submitted_at":"2018-09-12T11:41:05Z","abstract_excerpt":"With the growing number of published scientific papers world-wide, the need to evaluation and quality assessment methods for research papers is increasing. Scientific fields such as scientometrics, informetrics and bibliometrics establish quantified analysis methods and measurements for scientific papers. In this area, an important problem is to predict the future influence of a published paper. Particularly, early discrimination between influential papers and insignificant papers may find important applications. In this regard, one of the most important metrics is the number of citations to t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.04365","kind":"arxiv","version":3},"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":"1809.04365","created_at":"2026-05-17T23:51:09.609284+00:00"},{"alias_kind":"arxiv_version","alias_value":"1809.04365v3","created_at":"2026-05-17T23:51:09.609284+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.04365","created_at":"2026-05-17T23:51:09.609284+00:00"},{"alias_kind":"pith_short_12","alias_value":"4KAVZ7YOU5GO","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_16","alias_value":"4KAVZ7YOU5GOPBY6","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_8","alias_value":"4KAVZ7YO","created_at":"2026-05-18T12:32:05.422762+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/4KAVZ7YOU5GOPBY66UPHUIAEAG","json":"https://pith.science/pith/4KAVZ7YOU5GOPBY66UPHUIAEAG.json","graph_json":"https://pith.science/api/pith-number/4KAVZ7YOU5GOPBY66UPHUIAEAG/graph.json","events_json":"https://pith.science/api/pith-number/4KAVZ7YOU5GOPBY66UPHUIAEAG/events.json","paper":"https://pith.science/paper/4KAVZ7YO"},"agent_actions":{"view_html":"https://pith.science/pith/4KAVZ7YOU5GOPBY66UPHUIAEAG","download_json":"https://pith.science/pith/4KAVZ7YOU5GOPBY66UPHUIAEAG.json","view_paper":"https://pith.science/paper/4KAVZ7YO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1809.04365&json=true","fetch_graph":"https://pith.science/api/pith-number/4KAVZ7YOU5GOPBY66UPHUIAEAG/graph.json","fetch_events":"https://pith.science/api/pith-number/4KAVZ7YOU5GOPBY66UPHUIAEAG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4KAVZ7YOU5GOPBY66UPHUIAEAG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4KAVZ7YOU5GOPBY66UPHUIAEAG/action/storage_attestation","attest_author":"https://pith.science/pith/4KAVZ7YOU5GOPBY66UPHUIAEAG/action/author_attestation","sign_citation":"https://pith.science/pith/4KAVZ7YOU5GOPBY66UPHUIAEAG/action/citation_signature","submit_replication":"https://pith.science/pith/4KAVZ7YOU5GOPBY66UPHUIAEAG/action/replication_record"}},"created_at":"2026-05-17T23:51:09.609284+00:00","updated_at":"2026-05-17T23:51:09.609284+00:00"}