{"schema":"pith.reference-change-event.v1","doi":"10.1007/978-3-030-86383-8_12","canonical_url":"https://pith.science/event/10.1007/978-3-030-86383-8_12","json_url":"https://pith.science/event/10.1007/978-3-030-86383-8_12.json","not_a_judgment":"This page records that a citing paper's bibliography includes a work with a published notice. It is not a judgment on the citing paper.","primary":{"event_id":336132,"doi":"10.1007/978-3-030-86383-8_12","event_type":"correction","event_type_label":"Correction","source":"crossref","source_label":"Crossref","event_date":"2022-01-17","title":"Correction to: Short Text Clustering with a Deep Multi-embedded Self-supervised Model","work_title":"Short Text Clustering with a Deep Multi-embedded Self-supervised Model","work_doi":"10.1007/978-3-030-86383-8_12","work_arxiv_id":null,"notice_doi":"10.1007/978-3-030-86383-8_55","flag_count":0,"flags_open":0,"flags_disputed":0,"latest_flag_at":null,"human_href":"/event/10.1007/978-3-030-86383-8_12","json_href":"/event/10.1007/978-3-030-86383-8_12.json"},"events":[{"event_id":336132,"doi":"10.1007/978-3-030-86383-8_12","event_type":"correction","event_type_label":"Correction","source":"crossref","source_label":"Crossref","event_date":"2022-01-17","title":"Correction to: Short Text Clustering with a Deep Multi-embedded Self-supervised Model","work_title":"Short Text Clustering with a Deep Multi-embedded Self-supervised Model","work_doi":"10.1007/978-3-030-86383-8_12","work_arxiv_id":null,"notice_doi":"10.1007/978-3-030-86383-8_55","flag_count":0,"flags_open":0,"flags_disputed":0,"latest_flag_at":null,"human_href":"/event/10.1007/978-3-030-86383-8_12","json_href":"/event/10.1007/978-3-030-86383-8_12.json"}],"flags":[{"id":9269,"status":"open","status_label":"Open","citing_arxiv_id":"2502.08496","citing_title":"Fine-Tuning Topics through Weighting Aspect Keywords","ref_index":5,"evidence_raw":"Zhang K, Lian Z, Li J, Li H, Hu X. Short Text Clustering with a Deep Multi-embedded Self-supervised Model. In: Farkaš I, Masulli P, Otte S, Wermter S, editors. Artificial Neural Networks and Machine Learning – ICANN 2021. Cham: Springer International Publishing; 2021. p. 150–61. (Lecture Notes in Computer Science; vol. 12895). Available from: https://link.springer.com/10.1007/978-3-030-86383-8_12","evidence_cleaned":null,"evidence_source_label":"bibliography line","event_type":"correction","event_type_label":"Correction","source_label":"Crossref","event_date":"2022-01-17","work_title":"Short Text Clustering with a Deep Multi-embedded Self-supervised Model","work_doi":"10.1007/978-3-030-86383-8_12","event_doi":"10.1007/978-3-030-86383-8_12","flag_href":"/flags/9269","event_href":"/event/10.1007/978-3-030-86383-8_12","paper_href":"/paper/2502.08496","created_at":"2026-08-08T06:17:50.932862Z","dispute_note":null,"disputed_at":null,"disputed_by":null}],"flag_count":1,"flags_open":1,"flags_disputed":0,"desk_url":"https://pith.science/flags"}