{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:WCDA66DP6KNE2QLBDONCV6PJY2","short_pith_number":"pith:WCDA66DP","canonical_record":{"source":{"id":"1503.03168","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2015-03-10T10:34:06Z","cross_cats_sorted":[],"title_canon_sha256":"5ed7936f214865ea39bc585080620c9e4a13e9bb03f73c8e862c1b23d165bb57","abstract_canon_sha256":"c7c3ec485c9fc538a4e6e20d420a7f1bbe437cbc02ebd87019f4e5796ed91644"},"schema_version":"1.0"},"canonical_sha256":"b0860f786ff29a4d41611b9a2af9e9c6a574e3505feae250ce65ad00aef03050","source":{"kind":"arxiv","id":"1503.03168","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.03168","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"arxiv_version","alias_value":"1503.03168v1","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.03168","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"pith_short_12","alias_value":"WCDA66DP6KNE","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"WCDA66DP6KNE2QLB","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"WCDA66DP","created_at":"2026-05-18T12:29:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:WCDA66DP6KNE2QLBDONCV6PJY2","target":"record","payload":{"canonical_record":{"source":{"id":"1503.03168","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2015-03-10T10:34:06Z","cross_cats_sorted":[],"title_canon_sha256":"5ed7936f214865ea39bc585080620c9e4a13e9bb03f73c8e862c1b23d165bb57","abstract_canon_sha256":"c7c3ec485c9fc538a4e6e20d420a7f1bbe437cbc02ebd87019f4e5796ed91644"},"schema_version":"1.0"},"canonical_sha256":"b0860f786ff29a4d41611b9a2af9e9c6a574e3505feae250ce65ad00aef03050","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:25:04.171928Z","signature_b64":"FuXDeKRCny4u4x3T5/vAI12t6ig3XoztVhs357aZP4+XAmL7lx5VW+Jlo81R3HTGKHUpxfub3Nj9tQ5mZCHLAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b0860f786ff29a4d41611b9a2af9e9c6a574e3505feae250ce65ad00aef03050","last_reissued_at":"2026-05-18T02:25:04.171561Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:25:04.171561Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1503.03168","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":"2026-05-18T02:25:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xlogbCjLamnphUwLhG7ugv9CBPhrU+LkBCpKqnyvO2ia6Gm3zmvEe/mbydFxB4nhaD4qGCK5TDA/1dfpbd08Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T04:39:29.673274Z"},"content_sha256":"075e8c6fef1da9ee527f2d2470ce27f0a98d094b5c285963224d55986cdb4b08","schema_version":"1.0","event_id":"sha256:075e8c6fef1da9ee527f2d2470ce27f0a98d094b5c285963224d55986cdb4b08"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:WCDA66DP6KNE2QLBDONCV6PJY2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Experimental Estimation of Number of Clusters Based on Cluster Quality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"G. Hannah Grace, Kalyani Desikan","submitted_at":"2015-03-10T10:34:06Z","abstract_excerpt":"Text Clustering is a text mining technique which divides the given set of text documents into significant clusters. It is used for organizing a huge number of text documents into a well-organized form. In the majority of the clustering algorithms, the number of clusters must be specified apriori, which is a drawback of these algorithms. The aim of this paper is to show experimentally how to determine the number of clusters based on cluster quality. Since partitional clustering algorithms are well-suited for clustering large document datasets, we have confined our analysis to a partitional clus"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.03168","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":"2026-05-18T02:25:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TJxsS3ZsXKLHJW1z8S91G3Q+eurWTeQIPwL0rQVZ2O3YOb5PfVgIwYxfQQ8UAaRci0/YMOZUa+Vpnc5JqUE2Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T04:39:29.673665Z"},"content_sha256":"b52d86b88fb23f3078ad167d7a8c53e91850688203baba8e1928e2d77423aa02","schema_version":"1.0","event_id":"sha256:b52d86b88fb23f3078ad167d7a8c53e91850688203baba8e1928e2d77423aa02"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WCDA66DP6KNE2QLBDONCV6PJY2/bundle.json","state_url":"https://pith.science/pith/WCDA66DP6KNE2QLBDONCV6PJY2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WCDA66DP6KNE2QLBDONCV6PJY2/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":"2026-05-21T04:39:29Z","links":{"resolver":"https://pith.science/pith/WCDA66DP6KNE2QLBDONCV6PJY2","bundle":"https://pith.science/pith/WCDA66DP6KNE2QLBDONCV6PJY2/bundle.json","state":"https://pith.science/pith/WCDA66DP6KNE2QLBDONCV6PJY2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WCDA66DP6KNE2QLBDONCV6PJY2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:WCDA66DP6KNE2QLBDONCV6PJY2","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":"c7c3ec485c9fc538a4e6e20d420a7f1bbe437cbc02ebd87019f4e5796ed91644","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2015-03-10T10:34:06Z","title_canon_sha256":"5ed7936f214865ea39bc585080620c9e4a13e9bb03f73c8e862c1b23d165bb57"},"schema_version":"1.0","source":{"id":"1503.03168","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.03168","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"arxiv_version","alias_value":"1503.03168v1","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.03168","created_at":"2026-05-18T02:25:04Z"},{"alias_kind":"pith_short_12","alias_value":"WCDA66DP6KNE","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"WCDA66DP6KNE2QLB","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"WCDA66DP","created_at":"2026-05-18T12:29:47Z"}],"graph_snapshots":[{"event_id":"sha256:b52d86b88fb23f3078ad167d7a8c53e91850688203baba8e1928e2d77423aa02","target":"graph","created_at":"2026-05-18T02:25:04Z","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":"Text Clustering is a text mining technique which divides the given set of text documents into significant clusters. It is used for organizing a huge number of text documents into a well-organized form. In the majority of the clustering algorithms, the number of clusters must be specified apriori, which is a drawback of these algorithms. The aim of this paper is to show experimentally how to determine the number of clusters based on cluster quality. Since partitional clustering algorithms are well-suited for clustering large document datasets, we have confined our analysis to a partitional clus","authors_text":"G. Hannah Grace, Kalyani Desikan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2015-03-10T10:34:06Z","title":"Experimental Estimation of Number of Clusters Based on Cluster Quality"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.03168","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":"sha256:075e8c6fef1da9ee527f2d2470ce27f0a98d094b5c285963224d55986cdb4b08","target":"record","created_at":"2026-05-18T02:25:04Z","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":"c7c3ec485c9fc538a4e6e20d420a7f1bbe437cbc02ebd87019f4e5796ed91644","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2015-03-10T10:34:06Z","title_canon_sha256":"5ed7936f214865ea39bc585080620c9e4a13e9bb03f73c8e862c1b23d165bb57"},"schema_version":"1.0","source":{"id":"1503.03168","kind":"arxiv","version":1}},"canonical_sha256":"b0860f786ff29a4d41611b9a2af9e9c6a574e3505feae250ce65ad00aef03050","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b0860f786ff29a4d41611b9a2af9e9c6a574e3505feae250ce65ad00aef03050","first_computed_at":"2026-05-18T02:25:04.171561Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:25:04.171561Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FuXDeKRCny4u4x3T5/vAI12t6ig3XoztVhs357aZP4+XAmL7lx5VW+Jlo81R3HTGKHUpxfub3Nj9tQ5mZCHLAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:25:04.171928Z","signed_message":"canonical_sha256_bytes"},"source_id":"1503.03168","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:075e8c6fef1da9ee527f2d2470ce27f0a98d094b5c285963224d55986cdb4b08","sha256:b52d86b88fb23f3078ad167d7a8c53e91850688203baba8e1928e2d77423aa02"],"state_sha256":"bef666496e9a3a817598f131857b14f4388cc60b52f59e9014f7a77b327218a2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nl19W4Fd59B7qW8cMaCUbv4WMKa67q4PCdszCG0P1TWcbwpp0ztqXwTjpbwgTwan4gmmuByqKIC++aVblsEiBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T04:39:29.675943Z","bundle_sha256":"397566f91d63ff3cf8fd1d8c544aa1c1debbed9bbc6002983f13073fac42ca83"}}