{"id":"https://openalex.org/W2113429086","doi":"https://doi.org/10.21437/interspeech.2009-457","title":"Leveraging sentence weights in a concept-based optimization framework for extractive meeting summarization","display_name":"Leveraging sentence weights in a concept-based optimization framework for extractive meeting summarization","publication_year":2009,"publication_date":"2009-09-06","ids":{"openalex":"https://openalex.org/W2113429086","doi":"https://doi.org/10.21437/interspeech.2009-457","mag":"2113429086"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2009-457","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2009-457","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2009","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/A5114860858","display_name":"Shasha Xie","orcid":"https://orcid.org/0009-0001-7808-4617"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shasha Xie","raw_affiliation_strings":["University of California at Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California at Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071505335","display_name":"Beno\u00eet Favre","orcid":"https://orcid.org/0000-0002-9777-4613"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benoit Favre","raw_affiliation_strings":["University of California at Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California at Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068709817","display_name":"Dilek Hakkani\u2010T\u00fcr","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dilek Hakkani-T\u00fcr","raw_affiliation_strings":["University of California at Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California at Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355692","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-7300-9215"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Computer Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1503","last_page":"1506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9929999709129333,"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":0.9067177772521973},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7994025945663452},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.765659749507904},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7486190795898438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6500295400619507},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4907864034175873},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.41669583320617676},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3294892907142639}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9067177772521973},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7994025945663452},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.765659749507904},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7486190795898438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6500295400619507},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4907864034175873},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.41669583320617676},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3294892907142639},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.21437/interspeech.2009-457","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2009-457","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2009","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.159.5719","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.159.5719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.icsi.berkeley.edu/~favre/papers/favre_interspeech2009a.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.501.1673","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.501.1673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.hlt.utdallas.edu/~shasha/papers/interspeech2009_xie.pdf","raw_type":"text"},{"id":"pmh:oai:HAL:hal-01194281v1","is_oa":false,"landing_page_url":"https://amu.hal.science/hal-01194281","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Interspeech, Brighton (UK), 2009, Unknown, Unknown Region","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2439194","https://openalex.org/W177307080","https://openalex.org/W1503312748","https://openalex.org/W1591607137","https://openalex.org/W1753146643","https://openalex.org/W1831406492","https://openalex.org/W2107858678","https://openalex.org/W2115230584","https://openalex.org/W2125420881","https://openalex.org/W2137161909","https://openalex.org/W2145565331","https://openalex.org/W2146959363","https://openalex.org/W2152992673","https://openalex.org/W2154652894"],"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/W1517524280","https://openalex.org/W4323520239"],"abstract_inverted_index":{"We":[0,27],"adopt":[1],"an":[2],"unsupervised":[3,103],"concept-based":[4,48,98],"global":[5,120],"optimization":[6,49,64],"framework":[7],"for":[8,53,88],"extractive":[9],"meeting":[10,76,124],"summarization,":[11],"where":[12],"a":[13],"subset":[14],"of":[15,65],"sentences":[16,52],"is":[17],"selected":[18],"to":[19,29,41,96],"cover":[20],"as":[21,25],"many":[22],"important":[23],"concepts":[24],"possible.":[26],"propose":[28],"leverage":[30],"sentence":[31,44,66,122],"importance":[32],"weights":[33,45],"in":[34,115],"this":[35,102],"model.":[36],"Three":[37],"ways":[38],"are":[39],"introduced":[40],"combine":[42],"the":[43,47,74,86,97],"within":[46],"framework:":[50],"selecting":[51],"concept":[54,68],"extraction,":[55],"pruning":[56],"unlikely":[57],"candidate":[58],"summary":[59],"sentences,":[60],"and":[61,67,92,101],"using":[62],"joint":[63],"weights.":[69],"Our":[70],"experimental":[71],"results":[72,106],"on":[73],"ICSI":[75],"corpus":[77],"show":[78],"that":[79],"our":[80],"proposed":[81],"methods":[82],"can":[83],"significantly":[84],"improve":[85],"performance":[87],"both":[89],"human":[90],"transcripts":[91],"ASR":[93],"output":[94],"compared":[95],"baseline":[99],"approach,":[100],"approach":[104],"achieves":[105],"comparable":[107],"with":[108],"those":[109],"from":[110],"supervised":[111],"learning":[112],"approaches":[113],"presented":[114],"previous":[116],"work.":[117],"Index":[118],"Terms:":[119],"optimization,":[121],"weights,":[123],"summarization":[125]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}