{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:BEWDQWAZL3LOUC2H2DG7ASBTCA","short_pith_number":"pith:BEWDQWAZ","schema_version":"1.0","canonical_sha256":"092c3858195ed6ea0b47d0cdf04833102adc992037867a2f9c5c8d3c5473417a","source":{"kind":"arxiv","id":"1903.04489","version":1},"attestation_state":"computed","paper":{"title":"SPMF: A Social Trust and Preference Segmentation-based Matrix Factorization Recommendation Algorithm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.IR","authors_text":"Baogui Xin, Wei Peng","submitted_at":"2019-03-11T14:18:43Z","abstract_excerpt":"The traditional social recommendation algorithm ignores the following fact: the preferences of users with trust relationships are not necessarily similar, and the consideration of user preference similarity should be limited to specific areas. A social trust and preference segmentation-based matrix factorization (SPMF) recommendation system is proposed to solve the above-mentioned problems. Experimental results based on the Ciao and Epinions datasets show that the accuracy of the SPMF algorithm is significantly higher than that of some state-of-the-art recommendation algorithms. The proposed S"},"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":"1903.04489","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2019-03-11T14:18:43Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"5a31dbad12f8b3d86bf411d91de12ee8c71d17e465d4f2832468e662cce72d86","abstract_canon_sha256":"c4123f0defcdb07f06afd148311cef363099ddb89bdb4a7d305f7d0eca254456"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:29.454829Z","signature_b64":"nVvBGpXycrl3nDVSR3+UawqBCvyI5Fxr0TsHotg/IMFLxXodTOYR6GcUAWnk62hwiEg1FqdffhIgNMagXTPjCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"092c3858195ed6ea0b47d0cdf04833102adc992037867a2f9c5c8d3c5473417a","last_reissued_at":"2026-05-17T23:51:29.454472Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:29.454472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SPMF: A Social Trust and Preference Segmentation-based Matrix Factorization Recommendation Algorithm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.IR","authors_text":"Baogui Xin, Wei Peng","submitted_at":"2019-03-11T14:18:43Z","abstract_excerpt":"The traditional social recommendation algorithm ignores the following fact: the preferences of users with trust relationships are not necessarily similar, and the consideration of user preference similarity should be limited to specific areas. A social trust and preference segmentation-based matrix factorization (SPMF) recommendation system is proposed to solve the above-mentioned problems. Experimental results based on the Ciao and Epinions datasets show that the accuracy of the SPMF algorithm is significantly higher than that of some state-of-the-art recommendation algorithms. The proposed S"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.04489","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":"1903.04489","created_at":"2026-05-17T23:51:29.454531+00:00"},{"alias_kind":"arxiv_version","alias_value":"1903.04489v1","created_at":"2026-05-17T23:51:29.454531+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.04489","created_at":"2026-05-17T23:51:29.454531+00:00"},{"alias_kind":"pith_short_12","alias_value":"BEWDQWAZL3LO","created_at":"2026-05-18T12:33:12.712433+00:00"},{"alias_kind":"pith_short_16","alias_value":"BEWDQWAZL3LOUC2H","created_at":"2026-05-18T12:33:12.712433+00:00"},{"alias_kind":"pith_short_8","alias_value":"BEWDQWAZ","created_at":"2026-05-18T12:33:12.712433+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/BEWDQWAZL3LOUC2H2DG7ASBTCA","json":"https://pith.science/pith/BEWDQWAZL3LOUC2H2DG7ASBTCA.json","graph_json":"https://pith.science/api/pith-number/BEWDQWAZL3LOUC2H2DG7ASBTCA/graph.json","events_json":"https://pith.science/api/pith-number/BEWDQWAZL3LOUC2H2DG7ASBTCA/events.json","paper":"https://pith.science/paper/BEWDQWAZ"},"agent_actions":{"view_html":"https://pith.science/pith/BEWDQWAZL3LOUC2H2DG7ASBTCA","download_json":"https://pith.science/pith/BEWDQWAZL3LOUC2H2DG7ASBTCA.json","view_paper":"https://pith.science/paper/BEWDQWAZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1903.04489&json=true","fetch_graph":"https://pith.science/api/pith-number/BEWDQWAZL3LOUC2H2DG7ASBTCA/graph.json","fetch_events":"https://pith.science/api/pith-number/BEWDQWAZL3LOUC2H2DG7ASBTCA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BEWDQWAZL3LOUC2H2DG7ASBTCA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BEWDQWAZL3LOUC2H2DG7ASBTCA/action/storage_attestation","attest_author":"https://pith.science/pith/BEWDQWAZL3LOUC2H2DG7ASBTCA/action/author_attestation","sign_citation":"https://pith.science/pith/BEWDQWAZL3LOUC2H2DG7ASBTCA/action/citation_signature","submit_replication":"https://pith.science/pith/BEWDQWAZL3LOUC2H2DG7ASBTCA/action/replication_record"}},"created_at":"2026-05-17T23:51:29.454531+00:00","updated_at":"2026-05-17T23:51:29.454531+00:00"}