{"id":"https://openalex.org/W3201835111","doi":"https://doi.org/10.1145/3469968.3469987","title":"Distributed Hierarchical Sentence Embeddings for Unsupervised Extractive Text Summarization","display_name":"Distributed Hierarchical Sentence Embeddings for Unsupervised Extractive Text Summarization","publication_year":2021,"publication_date":"2021-05-22","ids":{"openalex":"https://openalex.org/W3201835111","doi":"https://doi.org/10.1145/3469968.3469987","mag":"3201835111"},"language":"en","primary_location":{"id":"doi:10.1145/3469968.3469987","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469968.3469987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 6th International Conference on Big Data and Computing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5053986669","display_name":"Guanjie Huang","orcid":"https://orcid.org/0000-0002-9343-5534"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanjie Huang","raw_affiliation_strings":["Sun Yat-Sen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101878399","display_name":"Hong Shen","orcid":"https://orcid.org/0000-0003-0587-4818"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Shen","raw_affiliation_strings":["Sun Yat-Sen University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"86","last_page":"92"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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":0.9995999932289124,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9987999796867371,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9927999973297119,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.9403390884399414},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8015729188919067},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6793496608734131},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5419339537620544},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5262326598167419},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3839530050754547}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9403390884399414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8015729188919067},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6793496608734131},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5419339537620544},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5262326598167419},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3839530050754547}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3469968.3469987","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469968.3469987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 6th International Conference on Big Data and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2010320682","https://openalex.org/W2064675550","https://openalex.org/W2785910460","https://openalex.org/W2896070522","https://openalex.org/W2950342809","https://openalex.org/W2952857865","https://openalex.org/W2970641574","https://openalex.org/W2970830889","https://openalex.org/W3034999214","https://openalex.org/W3100053428","https://openalex.org/W3158986179"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W2973759123","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Unsupervised":[0],"text":[1],"summarization":[2],"is":[3,16],"a":[4,28,178],"promising":[5],"approach":[6],"that":[7,33,147,168],"avoids":[8],"human":[9],"efforts":[10],"in":[11,160,182],"generating":[12],"reference":[13],"summaries,":[14],"which":[15],"particularly":[17],"important":[18],"for":[19,58,117],"large-scale":[20],"datasets.":[21],"To":[22,132],"improve":[23],"its":[24],"performance,":[25],"we":[26,89,107,140,163],"propose":[27],"hierarchical":[29],"BERT":[30,50,138],"[1]":[31],"model":[32,82,95,145,150,171],"contains":[34],"both":[35],"word-level":[36,53,81],"and":[37,55,68,74,101,114,176],"sentence-level":[38,60,94],"training":[39,61,72,135,158,183],"processes":[40],"to":[41,83,96,122,155],"achieve":[42],"semantic-rich":[43],"sentence":[44,86,112],"embeddings.":[45],"We":[46,78],"use":[47],"the":[48,52,59,63,93,109,118,130,134,137,142,149,157],"vanilla":[49],"as":[51],"training,":[54],"redesign":[56],"it":[57],"with":[62],"new":[64],"\u201cSentence":[65],"Token":[66],"Prediction\u201d":[67],"\u201cLocal":[69],"Shuffle":[70],"Recovery\u201d":[71],"tasks":[73],"suitable":[75],"input":[76,90],"format.":[77],"first":[79],"train":[80],"get":[84],"preliminary":[85],"embeddings,":[87],"then":[88],"them":[91,116],"into":[92],"further":[97],"extract":[98],"higher":[99],"level":[100],"inter-sentence":[102],"semantic":[103],"information.":[104],"After":[105],"that,":[106],"obtain":[108],"context":[110],"sensitive":[111],"embeddings":[113],"utilize":[115],"KMeans":[119],"cluster":[120],"algorithm":[121],"finally":[123],"generate":[124],"summaries":[125],"by":[126],"extracting":[127],"sentences":[128],"from":[129],"document.":[131],"accelerate":[133],"of":[136,180],"model,":[139],"adopt":[141],"PipeDream":[143],"[2]":[144],"parallelism":[146],"distributes":[148],"layers":[151],"among":[152],"multiple":[153],"machines":[154],"conduct":[156],"process":[159],"parallel.":[161],"Finally,":[162],"show":[164],"through":[165],"experimental":[166],"results":[167],"our":[169],"proposed":[170],"outperforms":[172],"most":[173],"popular":[174],"models":[175],"achieves":[177],"speedup":[179],"2.7":[181],"time":[184],"on":[185],"4":[186],"machines.":[187]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}