{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:MGQR5M5VSTSC4VCXOJTY2FU6WB","short_pith_number":"pith:MGQR5M5V","schema_version":"1.0","canonical_sha256":"61a11eb3b594e42e545772678d169eb06fa616ceb6bc8fdeecd7e51eeb26b6fb","source":{"kind":"arxiv","id":"2001.04825","version":1},"attestation_state":"computed","paper":{"title":"Enabling the Analysis of Personality Aspects in Recommender Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CY","cs.LG","stat.ML"],"primary_cat":"cs.IR","authors_text":"Amin Beheshti (1), Mehmet Orgun (1) ((1) Macquarie University- Sydney-Australia), Seyed Mohssen Ghafari (1), Shahpar Yakhchi (1)","submitted_at":"2020-01-07T23:02:07Z","abstract_excerpt":"Existing Recommender Systems mainly focus on exploiting users' feedback, e.g., ratings, and reviews on common items to detect similar users. Thus, they might fail when there are no common items of interest among users. We call this problem the Data Sparsity With no Feedback on Common Items (DSW-n-FCI). Personality-based recommender systems have shown a great success to identify similar users based on their personality types. However, there are only a few personality-based recommender systems in the literature which either discover personality explicitly through filling a questionnaire that is "},"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":"2001.04825","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2020-01-07T23:02:07Z","cross_cats_sorted":["cs.CY","cs.LG","stat.ML"],"title_canon_sha256":"dd1deff6a5af6d32a47b34a1180e3090a3f8efb970d8597f8011f12b072bc39d","abstract_canon_sha256":"639165509f58cb41715c7c7f71b9ff91d9ba41fed6bbaef0d1a08dbb2d219a5e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:33:29.994800Z","signature_b64":"TOQZuL1EdgO0BzzkBR+sSVDirisQ+p+f3hBC/bwtumwXWamlTAw8n5CYN6ESyQNWqq9UA5LzeOFpuu9pHiDTAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61a11eb3b594e42e545772678d169eb06fa616ceb6bc8fdeecd7e51eeb26b6fb","last_reissued_at":"2026-07-05T00:33:29.994220Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:33:29.994220Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Enabling the Analysis of Personality Aspects in Recommender Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CY","cs.LG","stat.ML"],"primary_cat":"cs.IR","authors_text":"Amin Beheshti (1), Mehmet Orgun (1) ((1) Macquarie University- Sydney-Australia), Seyed Mohssen Ghafari (1), Shahpar Yakhchi (1)","submitted_at":"2020-01-07T23:02:07Z","abstract_excerpt":"Existing Recommender Systems mainly focus on exploiting users' feedback, e.g., ratings, and reviews on common items to detect similar users. Thus, they might fail when there are no common items of interest among users. We call this problem the Data Sparsity With no Feedback on Common Items (DSW-n-FCI). Personality-based recommender systems have shown a great success to identify similar users based on their personality types. However, there are only a few personality-based recommender systems in the literature which either discover personality explicitly through filling a questionnaire that is "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.04825","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2001.04825/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2001.04825","created_at":"2026-07-05T00:33:29.994285+00:00"},{"alias_kind":"arxiv_version","alias_value":"2001.04825v1","created_at":"2026-07-05T00:33:29.994285+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.04825","created_at":"2026-07-05T00:33:29.994285+00:00"},{"alias_kind":"pith_short_12","alias_value":"MGQR5M5VSTSC","created_at":"2026-07-05T00:33:29.994285+00:00"},{"alias_kind":"pith_short_16","alias_value":"MGQR5M5VSTSC4VCX","created_at":"2026-07-05T00:33:29.994285+00:00"},{"alias_kind":"pith_short_8","alias_value":"MGQR5M5V","created_at":"2026-07-05T00:33:29.994285+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/MGQR5M5VSTSC4VCXOJTY2FU6WB","json":"https://pith.science/pith/MGQR5M5VSTSC4VCXOJTY2FU6WB.json","graph_json":"https://pith.science/api/pith-number/MGQR5M5VSTSC4VCXOJTY2FU6WB/graph.json","events_json":"https://pith.science/api/pith-number/MGQR5M5VSTSC4VCXOJTY2FU6WB/events.json","paper":"https://pith.science/paper/MGQR5M5V"},"agent_actions":{"view_html":"https://pith.science/pith/MGQR5M5VSTSC4VCXOJTY2FU6WB","download_json":"https://pith.science/pith/MGQR5M5VSTSC4VCXOJTY2FU6WB.json","view_paper":"https://pith.science/paper/MGQR5M5V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2001.04825&json=true","fetch_graph":"https://pith.science/api/pith-number/MGQR5M5VSTSC4VCXOJTY2FU6WB/graph.json","fetch_events":"https://pith.science/api/pith-number/MGQR5M5VSTSC4VCXOJTY2FU6WB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MGQR5M5VSTSC4VCXOJTY2FU6WB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MGQR5M5VSTSC4VCXOJTY2FU6WB/action/storage_attestation","attest_author":"https://pith.science/pith/MGQR5M5VSTSC4VCXOJTY2FU6WB/action/author_attestation","sign_citation":"https://pith.science/pith/MGQR5M5VSTSC4VCXOJTY2FU6WB/action/citation_signature","submit_replication":"https://pith.science/pith/MGQR5M5VSTSC4VCXOJTY2FU6WB/action/replication_record"}},"created_at":"2026-07-05T00:33:29.994285+00:00","updated_at":"2026-07-05T00:33:29.994285+00:00"}