{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:S7ACWAMJLKBU24W5VACS76LXIT","short_pith_number":"pith:S7ACWAMJ","schema_version":"1.0","canonical_sha256":"97c02b01895a834d72dda8052ff97744c0d872eb255a8ab98bd4742f155b07b1","source":{"kind":"arxiv","id":"2409.02856","version":2},"attestation_state":"computed","paper":{"title":"Building a Scalable, Effective, and Steerable Search and Ranking Platform","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.IR","authors_text":"Alexey Kurennoy, Ana Peleteiro Ramallo, Andrii Dzhoha, Danilo Ascione, Evgeny Labzin, G\\'eraud Le Falher, Ian Harris, Jacek Wasilewski, Marjan Celikik, Tural Gurbanov","submitted_at":"2024-09-04T16:29:25Z","abstract_excerpt":"Modern e-commerce platforms offer vast product selections, making it difficult for customers to find items that they like and that are relevant to their current session intent. This is why it is key for e-commerce platforms to have near real-time scalable and adaptable personalized ranking and search systems. While numerous methods exist in the scientific literature for building such systems, many are unsuitable for large-scale industrial use due to complexity and performance limitations. Consequently, industrial ranking systems often resort to computationally efficient yet simplistic retrieva"},"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":"2409.02856","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-09-04T16:29:25Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ad4a9805ac62d64192b7e527e967d5228d23571b4a2c60bd3868872e5417420d","abstract_canon_sha256":"337962c40f099abfed6a80bd273af804bb2c404a112b2617a4a059dbcdb025ea"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:27:58.707780Z","signature_b64":"NwpfBaME3KpAgCf1xj2wPeHIRGUrWVOXzpG6KWZHaKKc8hSBOSeA5jC7RmZCvRktpphHsNxy9TzZKmvwTDTmCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97c02b01895a834d72dda8052ff97744c0d872eb255a8ab98bd4742f155b07b1","last_reissued_at":"2026-07-05T09:27:58.707281Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:27:58.707281Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Building a Scalable, Effective, and Steerable Search and Ranking Platform","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.IR","authors_text":"Alexey Kurennoy, Ana Peleteiro Ramallo, Andrii Dzhoha, Danilo Ascione, Evgeny Labzin, G\\'eraud Le Falher, Ian Harris, Jacek Wasilewski, Marjan Celikik, Tural Gurbanov","submitted_at":"2024-09-04T16:29:25Z","abstract_excerpt":"Modern e-commerce platforms offer vast product selections, making it difficult for customers to find items that they like and that are relevant to their current session intent. This is why it is key for e-commerce platforms to have near real-time scalable and adaptable personalized ranking and search systems. While numerous methods exist in the scientific literature for building such systems, many are unsuitable for large-scale industrial use due to complexity and performance limitations. Consequently, industrial ranking systems often resort to computationally efficient yet simplistic retrieva"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.02856","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2409.02856/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":"2409.02856","created_at":"2026-07-05T09:27:58.707343+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.02856v2","created_at":"2026-07-05T09:27:58.707343+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.02856","created_at":"2026-07-05T09:27:58.707343+00:00"},{"alias_kind":"pith_short_12","alias_value":"S7ACWAMJLKBU","created_at":"2026-07-05T09:27:58.707343+00:00"},{"alias_kind":"pith_short_16","alias_value":"S7ACWAMJLKBU24W5","created_at":"2026-07-05T09:27:58.707343+00:00"},{"alias_kind":"pith_short_8","alias_value":"S7ACWAMJ","created_at":"2026-07-05T09:27:58.707343+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2604.19269","citing_title":"CS3: Efficient Online Capability Synergy for Two-Tower Recommendation","ref_index":4,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/S7ACWAMJLKBU24W5VACS76LXIT","json":"https://pith.science/pith/S7ACWAMJLKBU24W5VACS76LXIT.json","graph_json":"https://pith.science/api/pith-number/S7ACWAMJLKBU24W5VACS76LXIT/graph.json","events_json":"https://pith.science/api/pith-number/S7ACWAMJLKBU24W5VACS76LXIT/events.json","paper":"https://pith.science/paper/S7ACWAMJ"},"agent_actions":{"view_html":"https://pith.science/pith/S7ACWAMJLKBU24W5VACS76LXIT","download_json":"https://pith.science/pith/S7ACWAMJLKBU24W5VACS76LXIT.json","view_paper":"https://pith.science/paper/S7ACWAMJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.02856&json=true","fetch_graph":"https://pith.science/api/pith-number/S7ACWAMJLKBU24W5VACS76LXIT/graph.json","fetch_events":"https://pith.science/api/pith-number/S7ACWAMJLKBU24W5VACS76LXIT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/S7ACWAMJLKBU24W5VACS76LXIT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/S7ACWAMJLKBU24W5VACS76LXIT/action/storage_attestation","attest_author":"https://pith.science/pith/S7ACWAMJLKBU24W5VACS76LXIT/action/author_attestation","sign_citation":"https://pith.science/pith/S7ACWAMJLKBU24W5VACS76LXIT/action/citation_signature","submit_replication":"https://pith.science/pith/S7ACWAMJLKBU24W5VACS76LXIT/action/replication_record"}},"created_at":"2026-07-05T09:27:58.707343+00:00","updated_at":"2026-07-05T09:27:58.707343+00:00"}