{"id":"https://openalex.org/W4391149055","doi":"https://doi.org/10.1109/ic-nidc59918.2023.10390845","title":"Spiking Neural Network Based Text Summarization System","display_name":"Spiking Neural Network Based Text Summarization System","publication_year":2023,"publication_date":"2023-11-03","ids":{"openalex":"https://openalex.org/W4391149055","doi":"https://doi.org/10.1109/ic-nidc59918.2023.10390845"},"language":"en","primary_location":{"id":"doi:10.1109/ic-nidc59918.2023.10390845","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ic-nidc59918.2023.10390845","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 8th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108895866","display_name":"A. Xueyi Hao","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"A. Xueyi Hao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443971","display_name":"Bohan Li","orcid":"https://orcid.org/0000-0001-7766-9579"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"B. Yuze Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113862567","display_name":"Ernan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"E. Lei Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068427105","display_name":"Cunbin Li","orcid":"https://orcid.org/0000-0001-9136-9636"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]},{"id":"https://openalex.org/I4392738113","display_name":"China Electric Power Research Institute","ror":"https://ror.org/05ehpzy81","country_code":null,"type":"facility","lineage":["https://openalex.org/I17442442","https://openalex.org/I4392738113"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"C. Baofeng Li","raw_affiliation_strings":["China Electric Power Research Institute,Beijing,China,100192"],"affiliations":[{"raw_affiliation_string":"China Electric Power Research Institute,Beijing,China,100192","institution_ids":["https://openalex.org/I153473198","https://openalex.org/I4392738113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033403719","display_name":"Dalin Qin","orcid":"https://orcid.org/0000-0001-7752-023X"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]},{"id":"https://openalex.org/I4392738113","display_name":"China Electric Power Research Institute","ror":"https://ror.org/05ehpzy81","country_code":null,"type":"facility","lineage":["https://openalex.org/I17442442","https://openalex.org/I4392738113"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"D. Yu Qin","raw_affiliation_strings":["China Electric Power Research Institute,Beijing,China,100192"],"affiliations":[{"raw_affiliation_string":"China Electric Power Research Institute,Beijing,China,100192","institution_ids":["https://openalex.org/I153473198","https://openalex.org/I4392738113"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5108895866"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18290612,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"11","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.9512076377868652},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8631133437156677},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7162699699401855},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.598777174949646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5965462923049927},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5762036442756653},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.5328940153121948},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.48962074518203735},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45004332065582275},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.44230666756629944},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4123196303844452},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3887234032154083}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9512076377868652},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8631133437156677},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7162699699401855},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.598777174949646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5965462923049927},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5762036442756653},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5328940153121948},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.48962074518203735},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45004332065582275},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.44230666756629944},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4123196303844452},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3887234032154083},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic-nidc59918.2023.10390845","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ic-nidc59918.2023.10390845","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 8th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2006370340","https://openalex.org/W2911495555","https://openalex.org/W2924690340","https://openalex.org/W2972234767","https://openalex.org/W2990793844","https://openalex.org/W6749922295","https://openalex.org/W6761268247","https://openalex.org/W6875130942"],"related_works":["https://openalex.org/W2912153778","https://openalex.org/W4387163678","https://openalex.org/W4288108708","https://openalex.org/W2973430807","https://openalex.org/W4385280324","https://openalex.org/W2890685186","https://openalex.org/W2984436043","https://openalex.org/W4390245176","https://openalex.org/W2912831041","https://openalex.org/W3173606726"],"abstract_inverted_index":{"Due":[0],"to":[1,48,125],"information":[2],"overload,":[3],"ATS(Automatic":[4],"Text":[5],"Summarization)":[6],"is":[7,79,122],"becoming":[8],"increasingly":[9],"important.":[10],"However,":[11],"nowadays":[12],"DNN(Deep":[13],"Neural":[14,42,77],"Network)":[15,43,78],"and":[16,56,81,117],"pre-trained":[17],"language":[18],"models":[19],"widely":[20],"used":[21],"in":[22,32,129],"ATS":[23,45],"cannot":[24],"fully":[25],"mimic":[26],"the":[27,33,49,93],"operating":[28],"mechanism":[29],"of":[30,59,84,113],"neurons":[31],"human":[34],"brain.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39],"introduce":[40],"SNN(Spiking":[41],"into":[44],"system":[46],"due":[47],"high":[50,57,118],"biological":[51],"rationality,":[52],"low":[53,114],"power":[54,115],"consumption,":[55],"robustness":[58],"SNN.":[60],"A":[61],"new":[62],"extractive":[63],"summarization":[64],"model":[65],"called":[66],"BERT(Bidirectional":[67],"Encoder":[68],"Representation":[69],"from":[70],"Transformers)":[71],"+":[72,96,102],"LSNN(Long":[73],"short-term":[74],"memory":[75],"Spiking":[76],"proposed":[80],"a":[82],"set":[83],"experiments":[85],"on":[86],"CNN/Daily":[87],"Mail":[88],"are":[89],"implemented.":[90],"Compared":[91],"with":[92],"existing":[94],"BERT":[95,101],"LSTM(Long":[97],"Short-Term":[98],"Memory)":[99],"model,":[100],"LSNN":[103],"not":[104],"only":[105],"improves":[106],"performance,":[107],"but":[108],"also":[109],"verifies":[110],"SNN's":[111],"advantages":[112],"consumption":[116],"robustness.":[119],"This":[120],"work":[121],"very":[123],"promising":[124],"expand":[126],"related":[127],"research":[128],"text":[130],"summarization.":[131]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}