{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:CZMTUUVA7KV3MKLBKXRL254IDO","short_pith_number":"pith:CZMTUUVA","canonical_record":{"source":{"id":"2005.12439","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-05-25T23:24:24Z","cross_cats_sorted":["cs.IR","cs.MM"],"title_canon_sha256":"f0e17bc5b2ea6df2170e0dcf0e12f757051a1201d9e466d63f4069db6439a94d","abstract_canon_sha256":"c8b4d03deaa15e6ebf61964d93888fdf91841fbca7c62ab9845b980fd259f4a6"},"schema_version":"1.0"},"canonical_sha256":"16593a52a0faabb6296155e2bd77881baa04c08e191f246d565fe75c14f6ddd2","source":{"kind":"arxiv","id":"2005.12439","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.12439","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"arxiv_version","alias_value":"2005.12439v1","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.12439","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"pith_short_12","alias_value":"CZMTUUVA7KV3","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"pith_short_16","alias_value":"CZMTUUVA7KV3MKLB","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"pith_short_8","alias_value":"CZMTUUVA","created_at":"2026-07-05T01:05:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:CZMTUUVA7KV3MKLBKXRL254IDO","target":"record","payload":{"canonical_record":{"source":{"id":"2005.12439","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-05-25T23:24:24Z","cross_cats_sorted":["cs.IR","cs.MM"],"title_canon_sha256":"f0e17bc5b2ea6df2170e0dcf0e12f757051a1201d9e466d63f4069db6439a94d","abstract_canon_sha256":"c8b4d03deaa15e6ebf61964d93888fdf91841fbca7c62ab9845b980fd259f4a6"},"schema_version":"1.0"},"canonical_sha256":"16593a52a0faabb6296155e2bd77881baa04c08e191f246d565fe75c14f6ddd2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:05:54.285051Z","signature_b64":"EEXDdT0qWkM9VMVV1zlFj2RzNpwJQQjmOZcTsFXh9OBlZpBPRwO9TiOfMFIImbDNVA7gyaaxDgciOS7YGp2OCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"16593a52a0faabb6296155e2bd77881baa04c08e191f246d565fe75c14f6ddd2","last_reissued_at":"2026-07-05T01:05:54.284658Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:05:54.284658Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2005.12439","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:05:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RBljZxbg4lJuLTJWcOGJIynitL5F801adC1wDKNXt6Ugltc5mHdFHPqjLQ4B0phx82k0WtyAWzPBqgk0J5f2Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T20:50:42.077535Z"},"content_sha256":"81e546a6c9923cc1091919d1a496b5b017dd0e54d677857c4d27a74c1cdf9b29","schema_version":"1.0","event_id":"sha256:81e546a6c9923cc1091919d1a496b5b017dd0e54d677857c4d27a74c1cdf9b29"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:CZMTUUVA7KV3MKLBKXRL254IDO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","cs.MM"],"primary_cat":"cs.CV","authors_text":"Haitian Zheng, Jiebo Luo, Jong-Hwi Park, Kefei Wu, Wei Zhu","submitted_at":"2020-05-25T23:24:24Z","abstract_excerpt":"With the growth of online shopping for fashion products, accurate fashion recommendation has become a critical problem. Meanwhile, social networks provide an open and new data source for personalized fashion analysis. In this work, we study the problem of personalized fashion recommendation from social media data, i.e. recommending new outfits to social media users that fit their fashion preferences. To this end, we present an item-to-set metric learning framework that learns to compute the similarity between a set of historical fashion items of a user to a new fashion item. To extract feature"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.12439","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/2005.12439/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:05:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OpUeO0jjy6FKP7/BvZtttCKsy4sB5eCjEZ8nO6HdxZbeFABc9b0kEyiZMyJw3VELCmu+gk0HyftIID51XO98Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T20:50:42.078125Z"},"content_sha256":"289502517b7d2ad69650989ff6ffaf730a3c0cf629f589855f31a9012d57234b","schema_version":"1.0","event_id":"sha256:289502517b7d2ad69650989ff6ffaf730a3c0cf629f589855f31a9012d57234b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CZMTUUVA7KV3MKLBKXRL254IDO/bundle.json","state_url":"https://pith.science/pith/CZMTUUVA7KV3MKLBKXRL254IDO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CZMTUUVA7KV3MKLBKXRL254IDO/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T20:50:42Z","links":{"resolver":"https://pith.science/pith/CZMTUUVA7KV3MKLBKXRL254IDO","bundle":"https://pith.science/pith/CZMTUUVA7KV3MKLBKXRL254IDO/bundle.json","state":"https://pith.science/pith/CZMTUUVA7KV3MKLBKXRL254IDO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CZMTUUVA7KV3MKLBKXRL254IDO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:CZMTUUVA7KV3MKLBKXRL254IDO","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"c8b4d03deaa15e6ebf61964d93888fdf91841fbca7c62ab9845b980fd259f4a6","cross_cats_sorted":["cs.IR","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-05-25T23:24:24Z","title_canon_sha256":"f0e17bc5b2ea6df2170e0dcf0e12f757051a1201d9e466d63f4069db6439a94d"},"schema_version":"1.0","source":{"id":"2005.12439","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.12439","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"arxiv_version","alias_value":"2005.12439v1","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.12439","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"pith_short_12","alias_value":"CZMTUUVA7KV3","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"pith_short_16","alias_value":"CZMTUUVA7KV3MKLB","created_at":"2026-07-05T01:05:54Z"},{"alias_kind":"pith_short_8","alias_value":"CZMTUUVA","created_at":"2026-07-05T01:05:54Z"}],"graph_snapshots":[{"event_id":"sha256:289502517b7d2ad69650989ff6ffaf730a3c0cf629f589855f31a9012d57234b","target":"graph","created_at":"2026-07-05T01:05:54Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2005.12439/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the growth of online shopping for fashion products, accurate fashion recommendation has become a critical problem. Meanwhile, social networks provide an open and new data source for personalized fashion analysis. In this work, we study the problem of personalized fashion recommendation from social media data, i.e. recommending new outfits to social media users that fit their fashion preferences. To this end, we present an item-to-set metric learning framework that learns to compute the similarity between a set of historical fashion items of a user to a new fashion item. To extract feature","authors_text":"Haitian Zheng, Jiebo Luo, Jong-Hwi Park, Kefei Wu, Wei Zhu","cross_cats":["cs.IR","cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-05-25T23:24:24Z","title":"Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.12439","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:81e546a6c9923cc1091919d1a496b5b017dd0e54d677857c4d27a74c1cdf9b29","target":"record","created_at":"2026-07-05T01:05:54Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"c8b4d03deaa15e6ebf61964d93888fdf91841fbca7c62ab9845b980fd259f4a6","cross_cats_sorted":["cs.IR","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-05-25T23:24:24Z","title_canon_sha256":"f0e17bc5b2ea6df2170e0dcf0e12f757051a1201d9e466d63f4069db6439a94d"},"schema_version":"1.0","source":{"id":"2005.12439","kind":"arxiv","version":1}},"canonical_sha256":"16593a52a0faabb6296155e2bd77881baa04c08e191f246d565fe75c14f6ddd2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"16593a52a0faabb6296155e2bd77881baa04c08e191f246d565fe75c14f6ddd2","first_computed_at":"2026-07-05T01:05:54.284658Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:05:54.284658Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EEXDdT0qWkM9VMVV1zlFj2RzNpwJQQjmOZcTsFXh9OBlZpBPRwO9TiOfMFIImbDNVA7gyaaxDgciOS7YGp2OCg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:05:54.285051Z","signed_message":"canonical_sha256_bytes"},"source_id":"2005.12439","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:81e546a6c9923cc1091919d1a496b5b017dd0e54d677857c4d27a74c1cdf9b29","sha256:289502517b7d2ad69650989ff6ffaf730a3c0cf629f589855f31a9012d57234b"],"state_sha256":"36ad5246a8354e3a5fe5067df6f8ecd6e31306338e0c84313adfef7733991850"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NhnLDJ1ToPObDehYZfYtrgmQDr6V6K0ZPBnSfwMtCrMC3Qvbsk2cpZ/UVyy4tfXq4gUzyigGuBpCHVL8QIWFAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T20:50:42.083429Z","bundle_sha256":"383c3b0a37b889c5a91abfbf682498825494f5ad89e9dcf8b229811f0eff6e2a"}}