{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:66S43EIJWQ6CN5JRT3OS6J3LC4","short_pith_number":"pith:66S43EIJ","schema_version":"1.0","canonical_sha256":"f7a5cd9109b43c26f5319edd2f276b1732edc62fb55fcb53c84ec7cb5416a41c","source":{"kind":"arxiv","id":"1704.05249","version":1},"attestation_state":"computed","paper":{"title":"Hot or not? Forecasting cellular network hot spots using sector performance indicators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NI","cs.SY"],"primary_cat":"cs.LG","authors_text":"Alexandros Karatzoglou, Ilias Leontiadis, Joan Serr\\`a, Konstantina Papagiannaki","submitted_at":"2017-04-18T09:34:48Z","abstract_excerpt":"To manage and maintain large-scale cellular networks, operators need to know which sectors underperform at any given time. For this purpose, they use the so-called hot spot score, which is the result of a combination of multiple network measurements and reflects the instantaneous overall performance of individual sectors. While operators have a good understanding of the current performance of a network and its overall trend, forecasting the performance of each sector over time is a challenging task, as it is affected by both regular and non-regular events, triggered by human behavior and hardw"},"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":"1704.05249","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-04-18T09:34:48Z","cross_cats_sorted":["cs.NI","cs.SY"],"title_canon_sha256":"635b1613485659696f4c9d7c5424dc15be4279b15688e44d6314c674fabb48f8","abstract_canon_sha256":"646b1ddad371b92880acd61d4f77cbde10c9ef4cda1d944974f664ae9325e02e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:46:11.429663Z","signature_b64":"gTmmvgac8U6JIt9wy70Rk6ReiiCck0lUP0e/rLrZhsa77j/ID/uXbnuKim4DvCOUnGyQqpZPhnhTFpZJ84dTBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f7a5cd9109b43c26f5319edd2f276b1732edc62fb55fcb53c84ec7cb5416a41c","last_reissued_at":"2026-05-18T00:46:11.428989Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:46:11.428989Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Hot or not? Forecasting cellular network hot spots using sector performance indicators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NI","cs.SY"],"primary_cat":"cs.LG","authors_text":"Alexandros Karatzoglou, Ilias Leontiadis, Joan Serr\\`a, Konstantina Papagiannaki","submitted_at":"2017-04-18T09:34:48Z","abstract_excerpt":"To manage and maintain large-scale cellular networks, operators need to know which sectors underperform at any given time. For this purpose, they use the so-called hot spot score, which is the result of a combination of multiple network measurements and reflects the instantaneous overall performance of individual sectors. While operators have a good understanding of the current performance of a network and its overall trend, forecasting the performance of each sector over time is a challenging task, as it is affected by both regular and non-regular events, triggered by human behavior and hardw"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.05249","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1704.05249","created_at":"2026-05-18T00:46:11.429089+00:00"},{"alias_kind":"arxiv_version","alias_value":"1704.05249v1","created_at":"2026-05-18T00:46:11.429089+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.05249","created_at":"2026-05-18T00:46:11.429089+00:00"},{"alias_kind":"pith_short_12","alias_value":"66S43EIJWQ6C","created_at":"2026-05-18T12:31:03.183658+00:00"},{"alias_kind":"pith_short_16","alias_value":"66S43EIJWQ6CN5JR","created_at":"2026-05-18T12:31:03.183658+00:00"},{"alias_kind":"pith_short_8","alias_value":"66S43EIJ","created_at":"2026-05-18T12:31:03.183658+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/66S43EIJWQ6CN5JRT3OS6J3LC4","json":"https://pith.science/pith/66S43EIJWQ6CN5JRT3OS6J3LC4.json","graph_json":"https://pith.science/api/pith-number/66S43EIJWQ6CN5JRT3OS6J3LC4/graph.json","events_json":"https://pith.science/api/pith-number/66S43EIJWQ6CN5JRT3OS6J3LC4/events.json","paper":"https://pith.science/paper/66S43EIJ"},"agent_actions":{"view_html":"https://pith.science/pith/66S43EIJWQ6CN5JRT3OS6J3LC4","download_json":"https://pith.science/pith/66S43EIJWQ6CN5JRT3OS6J3LC4.json","view_paper":"https://pith.science/paper/66S43EIJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1704.05249&json=true","fetch_graph":"https://pith.science/api/pith-number/66S43EIJWQ6CN5JRT3OS6J3LC4/graph.json","fetch_events":"https://pith.science/api/pith-number/66S43EIJWQ6CN5JRT3OS6J3LC4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/66S43EIJWQ6CN5JRT3OS6J3LC4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/66S43EIJWQ6CN5JRT3OS6J3LC4/action/storage_attestation","attest_author":"https://pith.science/pith/66S43EIJWQ6CN5JRT3OS6J3LC4/action/author_attestation","sign_citation":"https://pith.science/pith/66S43EIJWQ6CN5JRT3OS6J3LC4/action/citation_signature","submit_replication":"https://pith.science/pith/66S43EIJWQ6CN5JRT3OS6J3LC4/action/replication_record"}},"created_at":"2026-05-18T00:46:11.429089+00:00","updated_at":"2026-05-18T00:46:11.429089+00:00"}