{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:IJQ7W7FSAW3IIYW44IW2HDLPLK","short_pith_number":"pith:IJQ7W7FS","schema_version":"1.0","canonical_sha256":"4261fb7cb205b68462dce22da38d6f5aba5ff34b3ab7499d65489a3590834b88","source":{"kind":"arxiv","id":"1811.11746","version":1},"attestation_state":"computed","paper":{"title":"Incremental Sparse TFIDF & Incremental Similarity with Bipartite Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS"],"primary_cat":"cs.IR","authors_text":"Pavel Brazdil, Rui Portocarrero Sarmento","submitted_at":"2018-11-29T15:20:32Z","abstract_excerpt":"In this report, we experimented with several concepts regarding text streams analysis.\n  We tested an implementation of Incremental Sparse TF-IDF (IS-TFIDF) and Incremental Cosine Similarity (ICS) with the use of bipartite graphs.\n  We are using bipartite graphs - one type of node are documents, and the other type of nodes are words - to know what documents are affected with a word arrival at the stream (the neighbors of the word in the graph). Thus, with this information, we leverage optimized algorithms used for graph-based applications. The concept is similar to, for example, the use of has"},"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":"1811.11746","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2018-11-29T15:20:32Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"8a00afafc441375d4ad9529e40a40c0ab0e95d8bcfbb1edbff430d0158786161","abstract_canon_sha256":"29a5dfdcfa9693f76fa9673a0ef158f6659e5500288c9f21bdcb1fbe8aad3fdf"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:37.735435Z","signature_b64":"4v0UNOhcVCV/x1a0bKoukE9BK5OcqjjkmB8TNnfQ2seK4SSIdSG4tNHGElIpRgOdhXHDRy1l86Yk3nKa4RvADQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4261fb7cb205b68462dce22da38d6f5aba5ff34b3ab7499d65489a3590834b88","last_reissued_at":"2026-05-17T23:59:37.734642Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:37.734642Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Incremental Sparse TFIDF & Incremental Similarity with Bipartite Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS"],"primary_cat":"cs.IR","authors_text":"Pavel Brazdil, Rui Portocarrero Sarmento","submitted_at":"2018-11-29T15:20:32Z","abstract_excerpt":"In this report, we experimented with several concepts regarding text streams analysis.\n  We tested an implementation of Incremental Sparse TF-IDF (IS-TFIDF) and Incremental Cosine Similarity (ICS) with the use of bipartite graphs.\n  We are using bipartite graphs - one type of node are documents, and the other type of nodes are words - to know what documents are affected with a word arrival at the stream (the neighbors of the word in the graph). Thus, with this information, we leverage optimized algorithms used for graph-based applications. The concept is similar to, for example, the use of has"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.11746","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":"1811.11746","created_at":"2026-05-17T23:59:37.734746+00:00"},{"alias_kind":"arxiv_version","alias_value":"1811.11746v1","created_at":"2026-05-17T23:59:37.734746+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.11746","created_at":"2026-05-17T23:59:37.734746+00:00"},{"alias_kind":"pith_short_12","alias_value":"IJQ7W7FSAW3I","created_at":"2026-05-18T12:32:31.084164+00:00"},{"alias_kind":"pith_short_16","alias_value":"IJQ7W7FSAW3IIYW4","created_at":"2026-05-18T12:32:31.084164+00:00"},{"alias_kind":"pith_short_8","alias_value":"IJQ7W7FS","created_at":"2026-05-18T12:32:31.084164+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/IJQ7W7FSAW3IIYW44IW2HDLPLK","json":"https://pith.science/pith/IJQ7W7FSAW3IIYW44IW2HDLPLK.json","graph_json":"https://pith.science/api/pith-number/IJQ7W7FSAW3IIYW44IW2HDLPLK/graph.json","events_json":"https://pith.science/api/pith-number/IJQ7W7FSAW3IIYW44IW2HDLPLK/events.json","paper":"https://pith.science/paper/IJQ7W7FS"},"agent_actions":{"view_html":"https://pith.science/pith/IJQ7W7FSAW3IIYW44IW2HDLPLK","download_json":"https://pith.science/pith/IJQ7W7FSAW3IIYW44IW2HDLPLK.json","view_paper":"https://pith.science/paper/IJQ7W7FS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1811.11746&json=true","fetch_graph":"https://pith.science/api/pith-number/IJQ7W7FSAW3IIYW44IW2HDLPLK/graph.json","fetch_events":"https://pith.science/api/pith-number/IJQ7W7FSAW3IIYW44IW2HDLPLK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IJQ7W7FSAW3IIYW44IW2HDLPLK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IJQ7W7FSAW3IIYW44IW2HDLPLK/action/storage_attestation","attest_author":"https://pith.science/pith/IJQ7W7FSAW3IIYW44IW2HDLPLK/action/author_attestation","sign_citation":"https://pith.science/pith/IJQ7W7FSAW3IIYW44IW2HDLPLK/action/citation_signature","submit_replication":"https://pith.science/pith/IJQ7W7FSAW3IIYW44IW2HDLPLK/action/replication_record"}},"created_at":"2026-05-17T23:59:37.734746+00:00","updated_at":"2026-05-17T23:59:37.734746+00:00"}