{"id":"https://openalex.org/W2591140323","doi":"https://doi.org/10.1109/icci-cc.2016.7862087","title":"A novel method for document summarization using Word2Vec","display_name":"A novel method for document summarization using Word2Vec","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2591140323","doi":"https://doi.org/10.1109/icci-cc.2016.7862087","mag":"2591140323"},"language":"en","primary_location":{"id":"doi:10.1109/icci-cc.2016.7862087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2016.7862087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","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/A5100422345","display_name":"Zhibo Wang","orcid":"https://orcid.org/0000-0002-5804-3279"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhibo Wang","raw_affiliation_strings":["Department of Computer Science, Georgia State University, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia State University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101487902","display_name":"Long Ma","orcid":"https://orcid.org/0000-0002-8357-424X"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Long Ma","raw_affiliation_strings":["Department of Computer Science, Georgia State University, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia State University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100612105","display_name":"Yanqing Zhang","orcid":"https://orcid.org/0000-0003-2349-1925"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanqing Zhang","raw_affiliation_strings":["Department of Computer Science, Georgia State University, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Georgia State University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I181565077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100422345"],"corresponding_institution_ids":["https://openalex.org/I181565077"],"apc_list":null,"apc_paid":null,"fwci":0.8569,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.85285336,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"523","last_page":"529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9990000128746033,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.9015684127807617},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.8332223892211914},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7952136397361755},{"id":"https://openalex.org/keywords/multi-document-summarization","display_name":"Multi-document summarization","score":0.6714286804199219},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5707355737686157},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36657580733299255},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3351770043373108}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9015684127807617},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.8332223892211914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7952136397361755},{"id":"https://openalex.org/C134714966","wikidata":"https://www.wikidata.org/wiki/Q6934448","display_name":"Multi-document summarization","level":3,"score":0.6714286804199219},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5707355737686157},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36657580733299255},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3351770043373108},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icci-cc.2016.7862087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2016.7862087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/16"},{"display_name":"Reduced inequalities","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W100623710","https://openalex.org/W168564468","https://openalex.org/W2101234009","https://openalex.org/W2131744502","https://openalex.org/W2153579005","https://openalex.org/W2202042777","https://openalex.org/W2250539671","https://openalex.org/W2882319491","https://openalex.org/W6675354045","https://openalex.org/W6679775712"],"related_works":["https://openalex.org/W2093597205","https://openalex.org/W2389846579","https://openalex.org/W2392495745","https://openalex.org/W2361032643","https://openalex.org/W132250100","https://openalex.org/W1539478205","https://openalex.org/W2334535520","https://openalex.org/W1488460679","https://openalex.org/W1526736613","https://openalex.org/W2725657302"],"abstract_inverted_index":{"Texting":[0],"mining":[1],"is":[2,36,160],"a":[3,60,81,152],"process":[4],"to":[5,40,71,88,110,121,132,164],"extract":[6],"useful":[7],"patterns":[8],"and":[9,55,75],"information":[10],"from":[11],"large":[12],"volume":[13],"of":[14,83,105],"unstructured":[15,22],"text":[16,23],"data.":[17],"Unlike":[18],"other":[19],"quantitative":[20],"data,":[21],"data":[24,34,45,58],"cannot":[25],"be":[26],"directly":[27],"utilized":[28],"in":[29,52,59,155],"machine":[30],"learning":[31],"models.":[32],"Hence,":[33],"pre-processing":[35,79],"an":[37,118],"essential":[38],"step":[39],"remove":[41,123],"vague":[42],"or":[43],"redundant":[44],"such":[46],"as":[47],"punctuations,":[48],"stop-words,":[49],"low-frequency":[50],"words":[51,84,95,126],"the":[53,57,78,90,99,103,133,145,148],"corpus,":[54],"re-organize":[56],"format":[61],"that":[62,101,139],"computers":[63],"can":[64],"understand.":[65],"Though":[66],"existing":[67],"approaches":[68],"are":[69,85,128],"able":[70],"eliminate":[72],"some":[73],"symbols":[74],"stop-words":[76],"during":[77],"step,":[80],"portion":[82],"not":[86,96,129],"used":[87],"describe":[89],"documents'":[91,134],"topics.":[92,135],"These":[93],"irrelevant":[94,125],"only":[97],"waste":[98],"storage":[100,159],"lessen":[102],"efficiency":[104],"computing,":[106],"but":[107],"also":[108],"lead":[109],"confounding":[111],"results.":[112],"In":[113],"this":[114],"paper,":[115],"we":[116],"propose":[117],"optimization":[119],"method":[120,142],"further":[122],"these":[124],"which":[127],"highly":[130],"correlated":[131],"Experimental":[136],"results":[137],"indicate":[138],"our":[140],"proposed":[141],"significantly":[143],"compresses":[144],"documents,":[146],"while":[147],"resulting":[149],"documents":[150],"remain":[151],"high":[153],"discrimination":[154],"classification":[156],"tasks;":[157],"additionally,":[158],"greatly":[161],"reduced":[162],"according":[163],"various":[165],"criteria.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}