{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:ZQLELHSJUDM3CHEXD2BKOHODVH","short_pith_number":"pith:ZQLELHSJ","canonical_record":{"source":{"id":"1706.06783","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-21T08:16:47Z","cross_cats_sorted":["cs.AI","cs.SI"],"title_canon_sha256":"4776f4c884f524e64cf4e7ae071eea53c961f8d67d7b6a1c211f9d4e784c8c34","abstract_canon_sha256":"fc043503cdfea2397cd1ead675b4e6d21f9ad7763ce9ee6fd80f3c13e3a9fdfc"},"schema_version":"1.0"},"canonical_sha256":"cc16459e49a0d9b11c971e82a71dc3a9e902b275a2659e09d0a697500cc54cd9","source":{"kind":"arxiv","id":"1706.06783","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.06783","created_at":"2026-05-18T00:41:56Z"},{"alias_kind":"arxiv_version","alias_value":"1706.06783v1","created_at":"2026-05-18T00:41:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.06783","created_at":"2026-05-18T00:41:56Z"},{"alias_kind":"pith_short_12","alias_value":"ZQLELHSJUDM3","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZQLELHSJUDM3CHEX","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZQLELHSJ","created_at":"2026-05-18T12:31:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:ZQLELHSJUDM3CHEXD2BKOHODVH","target":"record","payload":{"canonical_record":{"source":{"id":"1706.06783","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-21T08:16:47Z","cross_cats_sorted":["cs.AI","cs.SI"],"title_canon_sha256":"4776f4c884f524e64cf4e7ae071eea53c961f8d67d7b6a1c211f9d4e784c8c34","abstract_canon_sha256":"fc043503cdfea2397cd1ead675b4e6d21f9ad7763ce9ee6fd80f3c13e3a9fdfc"},"schema_version":"1.0"},"canonical_sha256":"cc16459e49a0d9b11c971e82a71dc3a9e902b275a2659e09d0a697500cc54cd9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:41:56.866081Z","signature_b64":"q7TZiQeEGbin++FxYsIR74CBCHaeDFvwC7qxRwivlRDnR51FlplxdHVzzqJ52p5zwVLS3m+/ouujPBn+JyU9Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cc16459e49a0d9b11c971e82a71dc3a9e902b275a2659e09d0a697500cc54cd9","last_reissued_at":"2026-05-18T00:41:56.865492Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:41:56.865492Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1706.06783","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":"2026-05-18T00:41:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SDSoT3bNr2x8F+W72LK5JEbFSjxkohoYdj3c2m1ryKYlUo+oNvtzHXgbX/9ZXU891X5yiTAA+N9h+nX+LFxkBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T06:33:57.115679Z"},"content_sha256":"cbe67e97aa0bbe9ad2f14a3a1ce7bcc6414d225d5ccd3e5433b35c68714e78e1","schema_version":"1.0","event_id":"sha256:cbe67e97aa0bbe9ad2f14a3a1ce7bcc6414d225d5ccd3e5433b35c68714e78e1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:ZQLELHSJUDM3CHEXD2BKOHODVH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NPGLM: A Non-Parametric Method for Temporal Link Prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.SI"],"primary_cat":"cs.LG","authors_text":"Hamid R. Rabiee, Jiawei Zhang, Sina Sajadmanesh","submitted_at":"2017-06-21T08:16:47Z","abstract_excerpt":"In this paper, we try to solve the problem of temporal link prediction in information networks. This implies predicting the time it takes for a link to appear in the future, given its features that have been extracted at the current network snapshot. To this end, we introduce a probabilistic non-parametric approach, called \"Non-Parametric Generalized Linear Model\" (NP-GLM), which infers the hidden underlying probability distribution of the link advent time given its features. We then present a learning algorithm for NP-GLM and an inference method to answer time-related queries. Extensive exper"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.06783","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:41:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8whcZaI25fH5HyFX/XdOUMskd421+0k+Zwx6p/RfdQOBtF/X6EEOqZyuzMGFZLKDRLhi+LqVJenS5z/EGc0gDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T06:33:57.116040Z"},"content_sha256":"18642e8cdfd664d2018eeb8d41f3f1bb9587c70996d6fd9505784537c9667da1","schema_version":"1.0","event_id":"sha256:18642e8cdfd664d2018eeb8d41f3f1bb9587c70996d6fd9505784537c9667da1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZQLELHSJUDM3CHEXD2BKOHODVH/bundle.json","state_url":"https://pith.science/pith/ZQLELHSJUDM3CHEXD2BKOHODVH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZQLELHSJUDM3CHEXD2BKOHODVH/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":"2026-05-30T06:33:57Z","links":{"resolver":"https://pith.science/pith/ZQLELHSJUDM3CHEXD2BKOHODVH","bundle":"https://pith.science/pith/ZQLELHSJUDM3CHEXD2BKOHODVH/bundle.json","state":"https://pith.science/pith/ZQLELHSJUDM3CHEXD2BKOHODVH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZQLELHSJUDM3CHEXD2BKOHODVH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:ZQLELHSJUDM3CHEXD2BKOHODVH","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":"fc043503cdfea2397cd1ead675b4e6d21f9ad7763ce9ee6fd80f3c13e3a9fdfc","cross_cats_sorted":["cs.AI","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-21T08:16:47Z","title_canon_sha256":"4776f4c884f524e64cf4e7ae071eea53c961f8d67d7b6a1c211f9d4e784c8c34"},"schema_version":"1.0","source":{"id":"1706.06783","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.06783","created_at":"2026-05-18T00:41:56Z"},{"alias_kind":"arxiv_version","alias_value":"1706.06783v1","created_at":"2026-05-18T00:41:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.06783","created_at":"2026-05-18T00:41:56Z"},{"alias_kind":"pith_short_12","alias_value":"ZQLELHSJUDM3","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZQLELHSJUDM3CHEX","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZQLELHSJ","created_at":"2026-05-18T12:31:59Z"}],"graph_snapshots":[{"event_id":"sha256:18642e8cdfd664d2018eeb8d41f3f1bb9587c70996d6fd9505784537c9667da1","target":"graph","created_at":"2026-05-18T00:41:56Z","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"},"paper":{"abstract_excerpt":"In this paper, we try to solve the problem of temporal link prediction in information networks. This implies predicting the time it takes for a link to appear in the future, given its features that have been extracted at the current network snapshot. To this end, we introduce a probabilistic non-parametric approach, called \"Non-Parametric Generalized Linear Model\" (NP-GLM), which infers the hidden underlying probability distribution of the link advent time given its features. We then present a learning algorithm for NP-GLM and an inference method to answer time-related queries. Extensive exper","authors_text":"Hamid R. Rabiee, Jiawei Zhang, Sina Sajadmanesh","cross_cats":["cs.AI","cs.SI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-21T08:16:47Z","title":"NPGLM: A Non-Parametric Method for Temporal Link Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.06783","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:cbe67e97aa0bbe9ad2f14a3a1ce7bcc6414d225d5ccd3e5433b35c68714e78e1","target":"record","created_at":"2026-05-18T00:41:56Z","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":"fc043503cdfea2397cd1ead675b4e6d21f9ad7763ce9ee6fd80f3c13e3a9fdfc","cross_cats_sorted":["cs.AI","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-21T08:16:47Z","title_canon_sha256":"4776f4c884f524e64cf4e7ae071eea53c961f8d67d7b6a1c211f9d4e784c8c34"},"schema_version":"1.0","source":{"id":"1706.06783","kind":"arxiv","version":1}},"canonical_sha256":"cc16459e49a0d9b11c971e82a71dc3a9e902b275a2659e09d0a697500cc54cd9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc16459e49a0d9b11c971e82a71dc3a9e902b275a2659e09d0a697500cc54cd9","first_computed_at":"2026-05-18T00:41:56.865492Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:41:56.865492Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q7TZiQeEGbin++FxYsIR74CBCHaeDFvwC7qxRwivlRDnR51FlplxdHVzzqJ52p5zwVLS3m+/ouujPBn+JyU9Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:41:56.866081Z","signed_message":"canonical_sha256_bytes"},"source_id":"1706.06783","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cbe67e97aa0bbe9ad2f14a3a1ce7bcc6414d225d5ccd3e5433b35c68714e78e1","sha256:18642e8cdfd664d2018eeb8d41f3f1bb9587c70996d6fd9505784537c9667da1"],"state_sha256":"4f5a4ca0ac3588c7e12cd8926afbd5c3f9bf1a852fc838c963abf7681290479f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p0/WBvT38WXW8qhdSXONvgGGknTww5NWVdQtIm2vmjNjKtV/ZrQ1f32wDNDkaOSEqyQk9Cv5DwCTg+pGh9edDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T06:33:57.118093Z","bundle_sha256":"6e6a1751bf745fd49179986414904074bade02ab1a8dbb00588e9faf2d86deb3"}}