{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:AQM7MUVXDFWV25IFN4QCJAS6MK","short_pith_number":"pith:AQM7MUVX","canonical_record":{"source":{"id":"1709.06599","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2017-09-19T18:37:42Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ec563cf0d4d7c756154fdf3dfb77bb16105c00aa0d50dd5f4f19b2a936f8c457","abstract_canon_sha256":"5e20ad9ff61cde4c4710162f1fb53d63f98b1ec893aa8ab6f444d1ea4dedcc5d"},"schema_version":"1.0"},"canonical_sha256":"0419f652b7196d5d75056f2024825e62bbf7167cd07baf165b3302536ed10b69","source":{"kind":"arxiv","id":"1709.06599","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.06599","created_at":"2026-05-18T00:34:41Z"},{"alias_kind":"arxiv_version","alias_value":"1709.06599v1","created_at":"2026-05-18T00:34:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.06599","created_at":"2026-05-18T00:34:41Z"},{"alias_kind":"pith_short_12","alias_value":"AQM7MUVXDFWV","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_16","alias_value":"AQM7MUVXDFWV25IF","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_8","alias_value":"AQM7MUVX","created_at":"2026-05-18T12:31:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:AQM7MUVXDFWV25IFN4QCJAS6MK","target":"record","payload":{"canonical_record":{"source":{"id":"1709.06599","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2017-09-19T18:37:42Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ec563cf0d4d7c756154fdf3dfb77bb16105c00aa0d50dd5f4f19b2a936f8c457","abstract_canon_sha256":"5e20ad9ff61cde4c4710162f1fb53d63f98b1ec893aa8ab6f444d1ea4dedcc5d"},"schema_version":"1.0"},"canonical_sha256":"0419f652b7196d5d75056f2024825e62bbf7167cd07baf165b3302536ed10b69","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:34:41.028028Z","signature_b64":"39y3+9G1kY+j+5fUBLgvF9tAhLKRgSXwyj/td2yDHKmhmKNNI11XvZu7ghs4tvmPeKiMvlpxENrP2pIckpiLDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0419f652b7196d5d75056f2024825e62bbf7167cd07baf165b3302536ed10b69","last_reissued_at":"2026-05-18T00:34:41.027308Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:34:41.027308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.06599","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":"2026-05-18T00:34:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YL+rTtaSpnR10aZkf8SuDGlPcKKk15Dm3Gls9kZjoj+QcxsJ4qf5dGlNPZ1dDfpb7hH6hEYG7H1ZTSjUT8XwAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T13:25:10.588907Z"},"content_sha256":"482cadaf8d40af45e4eee5bcf74450029ac00274f67c12166c507d3c0df852b2","schema_version":"1.0","event_id":"sha256:482cadaf8d40af45e4eee5bcf74450029ac00274f67c12166c507d3c0df852b2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:AQM7MUVXDFWV25IFN4QCJAS6MK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.NI","authors_text":"Ala Al-Fuqaha, Amir Hussain, Aunn Raza, Hunain Arif, Junaid Qadir, Kok-Lim Alvin Yau, Muhammad Usama, Yehia Elkhatib","submitted_at":"2017-09-19T18:37:42Z","abstract_excerpt":"While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services such as traffic engineering, anomaly detection, Internet traffic classification, and quality of service optimization. The interest in applying unsupervised learning techniques in networking emerges from their great success in other fields such as computer vision, natural l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.06599","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":"2026-05-18T00:34:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7BbFIB+7hdET4u/aGgTCWg5ClhrnJPuT8p6ZFNdOtg3/T6zCOW2eAH21/eAyTxxIndBcDOU5YIwV9gwF6VD0AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T13:25:10.589254Z"},"content_sha256":"2c8e338f1809b914b91a88d07d7de9f677c584c8ed2cd82a090ac84c713b0f54","schema_version":"1.0","event_id":"sha256:2c8e338f1809b914b91a88d07d7de9f677c584c8ed2cd82a090ac84c713b0f54"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AQM7MUVXDFWV25IFN4QCJAS6MK/bundle.json","state_url":"https://pith.science/pith/AQM7MUVXDFWV25IFN4QCJAS6MK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AQM7MUVXDFWV25IFN4QCJAS6MK/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":"2026-06-02T13:25:10Z","links":{"resolver":"https://pith.science/pith/AQM7MUVXDFWV25IFN4QCJAS6MK","bundle":"https://pith.science/pith/AQM7MUVXDFWV25IFN4QCJAS6MK/bundle.json","state":"https://pith.science/pith/AQM7MUVXDFWV25IFN4QCJAS6MK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AQM7MUVXDFWV25IFN4QCJAS6MK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:AQM7MUVXDFWV25IFN4QCJAS6MK","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":"5e20ad9ff61cde4c4710162f1fb53d63f98b1ec893aa8ab6f444d1ea4dedcc5d","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2017-09-19T18:37:42Z","title_canon_sha256":"ec563cf0d4d7c756154fdf3dfb77bb16105c00aa0d50dd5f4f19b2a936f8c457"},"schema_version":"1.0","source":{"id":"1709.06599","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.06599","created_at":"2026-05-18T00:34:41Z"},{"alias_kind":"arxiv_version","alias_value":"1709.06599v1","created_at":"2026-05-18T00:34:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.06599","created_at":"2026-05-18T00:34:41Z"},{"alias_kind":"pith_short_12","alias_value":"AQM7MUVXDFWV","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_16","alias_value":"AQM7MUVXDFWV25IF","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_8","alias_value":"AQM7MUVX","created_at":"2026-05-18T12:31:05Z"}],"graph_snapshots":[{"event_id":"sha256:2c8e338f1809b914b91a88d07d7de9f677c584c8ed2cd82a090ac84c713b0f54","target":"graph","created_at":"2026-05-18T00:34:41Z","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":"While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services such as traffic engineering, anomaly detection, Internet traffic classification, and quality of service optimization. The interest in applying unsupervised learning techniques in networking emerges from their great success in other fields such as computer vision, natural l","authors_text":"Ala Al-Fuqaha, Amir Hussain, Aunn Raza, Hunain Arif, Junaid Qadir, Kok-Lim Alvin Yau, Muhammad Usama, Yehia Elkhatib","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2017-09-19T18:37:42Z","title":"Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.06599","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":"sha256:482cadaf8d40af45e4eee5bcf74450029ac00274f67c12166c507d3c0df852b2","target":"record","created_at":"2026-05-18T00:34:41Z","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":"5e20ad9ff61cde4c4710162f1fb53d63f98b1ec893aa8ab6f444d1ea4dedcc5d","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2017-09-19T18:37:42Z","title_canon_sha256":"ec563cf0d4d7c756154fdf3dfb77bb16105c00aa0d50dd5f4f19b2a936f8c457"},"schema_version":"1.0","source":{"id":"1709.06599","kind":"arxiv","version":1}},"canonical_sha256":"0419f652b7196d5d75056f2024825e62bbf7167cd07baf165b3302536ed10b69","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0419f652b7196d5d75056f2024825e62bbf7167cd07baf165b3302536ed10b69","first_computed_at":"2026-05-18T00:34:41.027308Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:34:41.027308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"39y3+9G1kY+j+5fUBLgvF9tAhLKRgSXwyj/td2yDHKmhmKNNI11XvZu7ghs4tvmPeKiMvlpxENrP2pIckpiLDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:34:41.028028Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.06599","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:482cadaf8d40af45e4eee5bcf74450029ac00274f67c12166c507d3c0df852b2","sha256:2c8e338f1809b914b91a88d07d7de9f677c584c8ed2cd82a090ac84c713b0f54"],"state_sha256":"97677957a2fdf72ecaf61359da1f6a54aa16563e2121ca402b2bb9f3b60c0ed4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NLnGobKuV7JenNVFEeTp9jb+4mnLVZwjGAsHlHlzkZtDgqDnizl+7vdNUEoGftNhI2Nz89XG/R/y2tJYA8kOBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T13:25:10.591220Z","bundle_sha256":"63f620a8c1d6c1792313a41c1982a2c8a0c6a63169ccd8cb503a923c4fb807f7"}}