{"doi":"10.1109/csse.2008.667","title":"Automatic SVM Kernel Function Construction Based on Gene Expression Programming","abstract":null,"journal":"2008 International Conference on Computer Science and Software Engineering","year":2008,"id":607869,"datarank":0.24141568686511508,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.0,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"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":1560950,"name":"Changjie Tang","orcid":null,"position":1,"is_corresponding":false},{"id":964009,"name":"Chuan Li","orcid":"0000-0002-2730-7278","position":2,"is_corresponding":false},{"id":1560951,"name":"Shengzhi Li","orcid":null,"position":3,"is_corresponding":false},{"id":1560952,"name":"Shangyu Ye","orcid":null,"position":4,"is_corresponding":false},{"id":1560953,"name":"Taiyong Li","orcid":null,"position":5,"is_corresponding":false},{"id":1560954,"name":"Haichun Zheng","orcid":null,"position":6,"is_corresponding":false},{"id":1159064,"name":"Yue Jiang","orcid":"0000-0003-0024-0605","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Automatic SVM Kernel Function Construction Based on Gene Expression Programming","abstract":"Traditional support vector machine needs pre-assumed kernel functions. This paper proposes a method via gene expression programming to automatically construct the kernel. The contributions of this paper include: (1) proposing the concepts of GEP kernel and kernel tree; (2) proposing the properties of GEP kernel and the kernel relation theorem; (3) proposing GEP based support vector machine (KGEP-SVM), (4) decoding kernel individual algorithm (DKIA) and kernel operators operating algorithm (KOOA), and (5) extensive experiments show that the average accuracy of the method is increased by 4% and generation of GEP kernel is about 150.","is_dataset_classified":null,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"23304386","pmcid":null,"openalex_id":"https://openalex.org/W2096302783","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2012,"count":1},{"year":2014,"count":1},{"year":2015,"count":1},{"year":2020,"count":1}],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://xplorestaging.ieee.org/ielx5/4721667/4722542/04722647.pdf?arnumber=4722647","host_type":"publisher"},{"url":"https://doi.org/10.1109/csse.2008.667","host_type":""}],"fields_of_study":["Evolutionary Algorithms and Applications","Advanced Algorithms and Applications","Technology and Security Systems"],"mesh_terms":[],"keywords":["Polynomial kernel","Kernel (algebra)","Tree kernel","Gene expression programming","Radial basis function kernel","Support vector machine","Computer science","Variable kernel density estimation","Least squares support vector machine","Kernel method","Kernel embedding of distributions","String kernel","Graph kernel","Artificial intelligence","Pattern recognition (psychology)","Mathematics","Discrete mathematics"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-30T07:08:39.581282Z","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":[]}