{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:47PZ6TYJ47D5DKVCOPSB363B62","short_pith_number":"pith:47PZ6TYJ","schema_version":"1.0","canonical_sha256":"e7df9f4f09e7c7d1aaa273e41dfb61f6a10815582b3797b1a77b1a7dc97fef00","source":{"kind":"arxiv","id":"1806.04900","version":2},"attestation_state":"computed","paper":{"title":"A Machine-Learning Item Recommendation System for Video Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"\\'Africa Peri\\'a\\~nez, Anna Guitart, Paul Bertens, Pei Pei Chen","submitted_at":"2018-06-13T09:00:36Z","abstract_excerpt":"Video-game players generate huge amounts of data, as everything they do within a game is recorded. In particular, among all the stored actions and behaviors, there is information on the in-game purchases of virtual products. Such information is of critical importance in modern free-to-play titles, where gamers can select or buy a profusion of items during the game in order to progress and fully enjoy their experience.\n  To try to maximize these kind of purchases, one can use a recommendation system so as to present players with items that might be interesting for them. Such systems can better "},"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":"1806.04900","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-13T09:00:36Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"846bc33bf1b9a4408d493e819dc34b993be6b4ac328ff372dd965235c6e3e374","abstract_canon_sha256":"f323785bbfba26647cb8a0735d2b1ad8e62099bd5d60095f8799e7168aa755a4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:43.600126Z","signature_b64":"Z6Jyq1hpc4Hz7KChXcHaomJO6bk1AQnB4jilPBPoq7GK601GF9BwqW+FlIjpOKL2MVYwBxe+ZuQ4vOR31jmzCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e7df9f4f09e7c7d1aaa273e41dfb61f6a10815582b3797b1a77b1a7dc97fef00","last_reissued_at":"2026-05-17T23:59:43.599575Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:43.599575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Machine-Learning Item Recommendation System for Video Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"\\'Africa Peri\\'a\\~nez, Anna Guitart, Paul Bertens, Pei Pei Chen","submitted_at":"2018-06-13T09:00:36Z","abstract_excerpt":"Video-game players generate huge amounts of data, as everything they do within a game is recorded. In particular, among all the stored actions and behaviors, there is information on the in-game purchases of virtual products. Such information is of critical importance in modern free-to-play titles, where gamers can select or buy a profusion of items during the game in order to progress and fully enjoy their experience.\n  To try to maximize these kind of purchases, one can use a recommendation system so as to present players with items that might be interesting for them. Such systems can better "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04900","kind":"arxiv","version":2},"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":"1806.04900","created_at":"2026-05-17T23:59:43.599672+00:00"},{"alias_kind":"arxiv_version","alias_value":"1806.04900v2","created_at":"2026-05-17T23:59:43.599672+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04900","created_at":"2026-05-17T23:59:43.599672+00:00"},{"alias_kind":"pith_short_12","alias_value":"47PZ6TYJ47D5","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_16","alias_value":"47PZ6TYJ47D5DKVC","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_8","alias_value":"47PZ6TYJ","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/47PZ6TYJ47D5DKVCOPSB363B62","json":"https://pith.science/pith/47PZ6TYJ47D5DKVCOPSB363B62.json","graph_json":"https://pith.science/api/pith-number/47PZ6TYJ47D5DKVCOPSB363B62/graph.json","events_json":"https://pith.science/api/pith-number/47PZ6TYJ47D5DKVCOPSB363B62/events.json","paper":"https://pith.science/paper/47PZ6TYJ"},"agent_actions":{"view_html":"https://pith.science/pith/47PZ6TYJ47D5DKVCOPSB363B62","download_json":"https://pith.science/pith/47PZ6TYJ47D5DKVCOPSB363B62.json","view_paper":"https://pith.science/paper/47PZ6TYJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1806.04900&json=true","fetch_graph":"https://pith.science/api/pith-number/47PZ6TYJ47D5DKVCOPSB363B62/graph.json","fetch_events":"https://pith.science/api/pith-number/47PZ6TYJ47D5DKVCOPSB363B62/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/47PZ6TYJ47D5DKVCOPSB363B62/action/timestamp_anchor","attest_storage":"https://pith.science/pith/47PZ6TYJ47D5DKVCOPSB363B62/action/storage_attestation","attest_author":"https://pith.science/pith/47PZ6TYJ47D5DKVCOPSB363B62/action/author_attestation","sign_citation":"https://pith.science/pith/47PZ6TYJ47D5DKVCOPSB363B62/action/citation_signature","submit_replication":"https://pith.science/pith/47PZ6TYJ47D5DKVCOPSB363B62/action/replication_record"}},"created_at":"2026-05-17T23:59:43.599672+00:00","updated_at":"2026-05-17T23:59:43.599672+00:00"}