{"doi":"10.1016/j.jocs.2023.102011","title":"Impact learning: A learning method from feature’s impact and competition","abstract":null,"journal":"Journal of Computational Science","year":2023,"id":588601,"datarank":0.35638923596676825,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"self_citation_contribution":0.31191623125197543,"citation_network_contribution":0.04447300471479283,"self_endowment_contribution":0.31191623125197543,"citer_contribution":0.04447300471479283,"corpus_percentile":null,"corpus_rank":null,"citation_count":7,"citer_count":5,"citers_with_citation_signal":3,"citers_with_endowment":3,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1505868,"name":"Saydul Akbar Murad","orcid":null,"position":1,"is_corresponding":false},{"id":1505869,"name":"Abu Jafar Md Muzahid","orcid":null,"position":2,"is_corresponding":false},{"id":1505870,"name":"Masud Rana","orcid":null,"position":3,"is_corresponding":false},{"id":1505871,"name":"Md Kowsher","orcid":null,"position":4,"is_corresponding":false},{"id":1505872,"name":"Apurba Adhikary","orcid":null,"position":5,"is_corresponding":false},{"id":554721,"name":"Sujit Biswas","orcid":"0000-0002-6770-9845","position":6,"is_corresponding":false},{"id":1505873,"name":"Anupam Kumar Bairagi","orcid":null,"position":7,"is_corresponding":false},{"id":1505867,"name":"Nusrat Jahan Prottasha","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Impact learning: A learning method from feature’s impact and competition","abstract":null,"is_dataset_classified":null,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"26657633","pmcid":null,"openalex_id":"https://openalex.org/W4362673197","authors":[],"funders":[],"total_grants":0,"fwci":1.1104,"citation_percentile":0.80512165,"influential_citations":0,"citation_trend":[{"year":2023,"count":3},{"year":2024,"count":1},{"year":2025,"count":3}],"oa_status":"closed","license":"cc-by-nc-nd","oa_locations":[{"url":"https://api.elsevier.com/content/article/PII:S1877750323000716?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S1877750323000716?httpAccept=text/plain","host_type":"publisher"},{"url":"https://doi.org/10.1016/j.jocs.2023.102011","host_type":"journal"}],"fields_of_study":["Machine Learning and Data Classification","Big Data and Business Intelligence","Data Stream Mining Techniques"],"mesh_terms":[],"keywords":["Machine learning","Artificial intelligence","Computer science","Online machine learning","Instance-based learning","Competitive learning","Semi-supervised learning","Computational learning theory","Competition (biology)","Active learning (machine learning)","Unsupervised learning","Field (mathematics)","Feature (linguistics)","Wake-sleep algorithm","Algorithmic learning theory","Learning classifier system","Supervised learning","Sample (material)","Artificial neural network","Mathematics"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-22T04:01:05.191717Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}