{"id":"https://openalex.org/W1974172222","doi":"https://doi.org/10.1109/his.2011.6122102","title":"Using NMF-based text summarization to improve supervised and unsupervised classification","display_name":"Using NMF-based text summarization to improve supervised and unsupervised classification","publication_year":2011,"publication_date":"2011-12-01","ids":{"openalex":"https://openalex.org/W1974172222","doi":"https://doi.org/10.1109/his.2011.6122102","mag":"1974172222"},"language":"en","primary_location":{"id":"doi:10.1109/his.2011.6122102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/his.2011.6122102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 11th International Conference on Hybrid Intelligent Systems (HIS)","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/A5034027886","display_name":"D. V. Tsarev","orcid":"https://orcid.org/0000-0002-9041-2708"},"institutions":[{"id":"https://openalex.org/I19880235","display_name":"Lomonosov Moscow State University","ror":"https://ror.org/010pmpe69","country_code":"RU","type":"education","lineage":["https://openalex.org/I19880235"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Dmitry Tsarev","raw_affiliation_strings":["Computer Science Department, Lomonosov Moscow State University, Moscow, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Lomonosov Moscow State University, Moscow, Russia","institution_ids":["https://openalex.org/I19880235"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074938669","display_name":"Mikhail Petrovskiy","orcid":"https://orcid.org/0000-0002-1236-398X"},"institutions":[{"id":"https://openalex.org/I19880235","display_name":"Lomonosov Moscow State University","ror":"https://ror.org/010pmpe69","country_code":"RU","type":"education","lineage":["https://openalex.org/I19880235"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Mikhail Petrovskiy","raw_affiliation_strings":["Computer Science Department, Lomonosov Moscow State University, Moscow, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Lomonosov Moscow State University, Moscow, Russia","institution_ids":["https://openalex.org/I19880235"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003416394","display_name":"\u0418. \u0412. \u041c\u0430\u0448\u0435\u0447\u043a\u0438\u043d","orcid":"https://orcid.org/0000-0002-9837-585X"},"institutions":[{"id":"https://openalex.org/I19880235","display_name":"Lomonosov Moscow State University","ror":"https://ror.org/010pmpe69","country_code":"RU","type":"education","lineage":["https://openalex.org/I19880235"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Igor Mashechkin","raw_affiliation_strings":["Computer Science Department, Lomonosov Moscow State University, Moscow, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Lomonosov Moscow State University, Moscow, Russia","institution_ids":["https://openalex.org/I19880235"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19880235"],"apc_list":null,"apc_paid":null,"fwci":0.8628,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.78872411,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"185","last_page":"189"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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/T10028","display_name":"Topic Modeling","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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9983999729156494,"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":0.8753897547721863},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8234870433807373},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.782349705696106},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6851766705513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6277686953544617},{"id":"https://openalex.org/keywords/text-graph","display_name":"Text graph","score":0.5729159712791443},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5421714186668396},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5164135098457336},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5048545002937317},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4558393657207489},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.42796117067337036},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41108042001724243},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.36778324842453003}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8753897547721863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8234870433807373},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.782349705696106},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6851766705513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6277686953544617},{"id":"https://openalex.org/C66945725","wikidata":"https://www.wikidata.org/wiki/Q18388823","display_name":"Text graph","level":3,"score":0.5729159712791443},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5421714186668396},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5164135098457336},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5048545002937317},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4558393657207489},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.42796117067337036},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41108042001724243},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.36778324842453003},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/his.2011.6122102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/his.2011.6122102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 11th International Conference on Hybrid Intelligent Systems (HIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1492327544","https://openalex.org/W1497998217","https://openalex.org/W1532325895","https://openalex.org/W1618905105","https://openalex.org/W1902027874","https://openalex.org/W1952772494","https://openalex.org/W1967082914","https://openalex.org/W2010320682","https://openalex.org/W2013029404","https://openalex.org/W2058616517","https://openalex.org/W2117569901","https://openalex.org/W2182959134","https://openalex.org/W2187974559","https://openalex.org/W2312916465","https://openalex.org/W3149942960","https://openalex.org/W4213009331","https://openalex.org/W6686386953","https://openalex.org/W6698712842"],"related_works":["https://openalex.org/W2996251560","https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2986470681","https://openalex.org/W4238363396","https://openalex.org/W4385234707","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2590756584","https://openalex.org/W2792706544"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,96,106],"new":[4],"generic":[5],"text":[6,77,92],"summarization":[7,47,93],"method":[8,44,68,94],"using":[9,36],"Non-negative":[10],"Matrix":[11],"Factorization":[12],"(NMF)":[13],"to":[14],"estimate":[15],"sentence":[16,19],"relevance.":[17],"Proposed":[18],"relevance":[20],"estimation":[21],"is":[22],"based":[23],"on":[24,57],"normalization":[25],"of":[26,33,53,73,110],"NMF":[27],"topic":[28,35,40],"space":[29],"and":[30,49,75,85,103,112],"further":[31,100],"weighting":[32],"each":[34],"sentences":[37],"representation":[38],"in":[39],"space.":[41],"The":[42],"proposed":[43],"shows":[45],"better":[46],"quality":[48,109],"performance":[50,72],"than":[51],"state":[52],"the":[54,71,108],"art":[55],"methods":[56],"DUC":[58],"2002":[59],"standard":[60],"dataset.":[61],"In":[62,80],"addition,":[63],"we":[64,89],"study":[65],"how":[66],"this":[67],"can":[69],"improve":[70],"supervised":[74],"unsupervised":[76],"classification":[78,102,111],"tasks.":[79],"our":[81],"experiments":[82],"with":[83],"Reuters-21578":[84],"Classic4":[86],"benchmark":[87],"datasets":[88],"apply":[90],"developed":[91],"as":[95],"preprocessing":[97],"step":[98],"for":[99],"multi-label":[101],"clustering.":[104],"As":[105],"result,":[107],"clustering":[113],"has":[114],"been":[115],"significantly":[116],"improved.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
