{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:BBHQT6DDHVAWGFGPMGARQEU3N7","short_pith_number":"pith:BBHQT6DD","schema_version":"1.0","canonical_sha256":"084f09f8633d416314cf618118129b6ffbe4c559d6d59cd231f68f15c9e111ae","source":{"kind":"arxiv","id":"1806.00571","version":1},"attestation_state":"computed","paper":{"title":"Efficient Interactive Search for Geo-tagged Multimedia Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.MM","authors_text":"Chengyuan Zhang, Jun Long, Lei Zhu, Ruipeng Chen, Yunwu Lin, Zhan Yang","submitted_at":"2018-06-02T02:11:50Z","abstract_excerpt":"Due to the advances in mobile computing and multimedia techniques, there are vast amount of multimedia data with geographical information collected in multifarious applications. In this paper, we propose a novel type of image search named interactive geo-tagged image search which aims to find out a set of images based on geographical proximity and similarity of visual content, as well as the preference of users. Existing approaches for spatial keyword query and geo-image query cannot address this problem effectively since they do not consider these three type of information together for query."},"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":"1806.00571","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2018-06-02T02:11:50Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"bc2dbc16d89f505a03e02ea38f55d2dc6d1638f1fab4dba4e79a4fb18262a40f","abstract_canon_sha256":"4bd8c342f896e1446911e7183f3e04deec6455a4536051c5a7faf6edfb2222f3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:19.040409Z","signature_b64":"Iga67+7O8Sfjtydu3hJxSiDVbXlgIQoj23ErHvM3xQDQ/ksePP28b/1BTDEqIMrW2eJCAlhrs9id2C20oggyAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"084f09f8633d416314cf618118129b6ffbe4c559d6d59cd231f68f15c9e111ae","last_reissued_at":"2026-05-18T00:14:19.039891Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:19.039891Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient Interactive Search for Geo-tagged Multimedia Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.MM","authors_text":"Chengyuan Zhang, Jun Long, Lei Zhu, Ruipeng Chen, Yunwu Lin, Zhan Yang","submitted_at":"2018-06-02T02:11:50Z","abstract_excerpt":"Due to the advances in mobile computing and multimedia techniques, there are vast amount of multimedia data with geographical information collected in multifarious applications. In this paper, we propose a novel type of image search named interactive geo-tagged image search which aims to find out a set of images based on geographical proximity and similarity of visual content, as well as the preference of users. Existing approaches for spatial keyword query and geo-image query cannot address this problem effectively since they do not consider these three type of information together for query."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.00571","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":"1806.00571","created_at":"2026-05-18T00:14:19.039995+00:00"},{"alias_kind":"arxiv_version","alias_value":"1806.00571v1","created_at":"2026-05-18T00:14:19.039995+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.00571","created_at":"2026-05-18T00:14:19.039995+00:00"},{"alias_kind":"pith_short_12","alias_value":"BBHQT6DDHVAW","created_at":"2026-05-18T12:32:13.499390+00:00"},{"alias_kind":"pith_short_16","alias_value":"BBHQT6DDHVAWGFGP","created_at":"2026-05-18T12:32:13.499390+00:00"},{"alias_kind":"pith_short_8","alias_value":"BBHQT6DD","created_at":"2026-05-18T12:32:13.499390+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/BBHQT6DDHVAWGFGPMGARQEU3N7","json":"https://pith.science/pith/BBHQT6DDHVAWGFGPMGARQEU3N7.json","graph_json":"https://pith.science/api/pith-number/BBHQT6DDHVAWGFGPMGARQEU3N7/graph.json","events_json":"https://pith.science/api/pith-number/BBHQT6DDHVAWGFGPMGARQEU3N7/events.json","paper":"https://pith.science/paper/BBHQT6DD"},"agent_actions":{"view_html":"https://pith.science/pith/BBHQT6DDHVAWGFGPMGARQEU3N7","download_json":"https://pith.science/pith/BBHQT6DDHVAWGFGPMGARQEU3N7.json","view_paper":"https://pith.science/paper/BBHQT6DD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1806.00571&json=true","fetch_graph":"https://pith.science/api/pith-number/BBHQT6DDHVAWGFGPMGARQEU3N7/graph.json","fetch_events":"https://pith.science/api/pith-number/BBHQT6DDHVAWGFGPMGARQEU3N7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BBHQT6DDHVAWGFGPMGARQEU3N7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BBHQT6DDHVAWGFGPMGARQEU3N7/action/storage_attestation","attest_author":"https://pith.science/pith/BBHQT6DDHVAWGFGPMGARQEU3N7/action/author_attestation","sign_citation":"https://pith.science/pith/BBHQT6DDHVAWGFGPMGARQEU3N7/action/citation_signature","submit_replication":"https://pith.science/pith/BBHQT6DDHVAWGFGPMGARQEU3N7/action/replication_record"}},"created_at":"2026-05-18T00:14:19.039995+00:00","updated_at":"2026-05-18T00:14:19.039995+00:00"}