{"id":"https://openalex.org/W2145657314","doi":"https://doi.org/10.1145/1065385.1065418","title":"Automatic extraction of titles from general documents using machine learning","display_name":"Automatic extraction of titles from general documents using machine learning","publication_year":2005,"publication_date":"2005-06-07","ids":{"openalex":"https://openalex.org/W2145657314","doi":"https://doi.org/10.1145/1065385.1065418","mag":"2145657314"},"language":"en","primary_location":{"id":"doi:10.1145/1065385.1065418","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1065385.1065418","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries","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/A5110380262","display_name":"Yunhua Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhua Hu","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455135","display_name":"Hang Li","orcid":"https://orcid.org/0000-0002-3464-3245"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Li","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China","Microsoft research Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011542448","display_name":"Yunbo Cao","orcid":"https://orcid.org/0009-0005-2558-5206"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunbo Cao","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China","Microsoft research Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076637714","display_name":"Dmitriy Meyerzon","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dmitriy Meyerzon","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041083459","display_name":"Qinghua Zheng","orcid":"https://orcid.org/0000-0002-8436-4754"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Zheng","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.422,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.96635112,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"145","last_page":"154"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9991999864578247,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9991999864578247,"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":0.9987999796867371,"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":0.9980000257492065,"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/disk-formatting","display_name":"Disk formatting","score":0.8982325196266174},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8630727529525757},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6772943735122681},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5695566534996033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5480093359947205},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5426952242851257},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.5398536920547485},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5312780141830444},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5118269324302673},{"id":"https://openalex.org/keywords/keyword-extraction","display_name":"Keyword extraction","score":0.5007369518280029},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4807133972644806},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.44703829288482666},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.4141214191913605},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3450600206851959}],"concepts":[{"id":"https://openalex.org/C88006597","wikidata":"https://www.wikidata.org/wiki/Q690117","display_name":"Disk formatting","level":2,"score":0.8982325196266174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8630727529525757},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6772943735122681},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5695566534996033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5480093359947205},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5426952242851257},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.5398536920547485},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5312780141830444},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5118269324302673},{"id":"https://openalex.org/C2780288562","wikidata":"https://www.wikidata.org/wiki/Q25053353","display_name":"Keyword extraction","level":2,"score":0.5007369518280029},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4807133972644806},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.44703829288482666},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.4141214191913605},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3450600206851959},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1065385.1065418","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1065385.1065418","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1525460779","https://openalex.org/W1528012351","https://openalex.org/W1528056001","https://openalex.org/W1534730506","https://openalex.org/W1934019294","https://openalex.org/W1994485670","https://openalex.org/W1998839545","https://openalex.org/W2008652694","https://openalex.org/W2034797903","https://openalex.org/W2038124402","https://openalex.org/W2039231973","https://openalex.org/W2046325278","https://openalex.org/W2062159222","https://openalex.org/W2080928448","https://openalex.org/W2085030399","https://openalex.org/W2096175520","https://openalex.org/W2119821739","https://openalex.org/W2123028711","https://openalex.org/W2124303864","https://openalex.org/W2129311323","https://openalex.org/W2140479099","https://openalex.org/W2147880316","https://openalex.org/W2158511245","https://openalex.org/W2158755884","https://openalex.org/W2165696355","https://openalex.org/W2295081780"],"related_works":["https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W2352298027","https://openalex.org/W2092919065","https://openalex.org/W3138801416","https://openalex.org/W4236762297","https://openalex.org/W2444550338","https://openalex.org/W2169232658","https://openalex.org/W2369351710","https://openalex.org/W2594363579"],"abstract_inverted_index":{"In":[0,86],"this":[1,194],"paper,":[2],"we":[3,18,77,89,124,198,214,229],"propose":[4],"a":[5,28,74],"machine":[6,107],"learning":[7,108],"approach":[8],"to":[9,24,65,149,208,225],"title":[10,50,68,112,160,174],"extraction":[11,51,69,79,113,152,161,175],"from":[12,52,70,80,153,162,176],"general":[13,16,71,154],"documents.":[14,72,155],"By":[15],"documents,":[17],"mean":[19],"documents":[20,94],"that":[21,123,141,197],"can":[22,147,199,215,230],"belong":[23],"any":[25],"one":[26,203,220],"of":[27,30,144],"number":[29],"specific":[31],"genres,":[32],"including":[33,82],"presentations,":[34],"book":[35],"chapters,":[36],"technical":[37],"papers,":[38],"brochures,":[39],"reports,":[40],"and":[41,84,97,100,110,157,166,169,171,180,205,211,222],"letters.":[42],"Previously,":[43],"methods":[44],"have":[45],"been":[46,58],"proposed":[47],"mainly":[48,125],"for":[49,159,173],"research":[53],"papers.":[54],"It":[55,138],"has":[56],"not":[57],"clear":[59],"whether":[60],"it":[61],"could":[62],"be":[63],"possible":[64],"conduct":[66],"automatic":[67],"As":[73],"case":[75],"study,":[76],"consider":[78],"Office":[81],"Word":[83,96,163],"PowerPoint.":[85],"our":[87],"approach,":[88],"annotate":[90],"titles":[91],"in":[92,122,135,183,193,202,219,236],"sample":[93],"(for":[95],"PowerPoint":[98,177],"respectively)":[99],"take":[101],"them":[102,207,224],"as":[103,130,133],"training":[104],"data,":[105],"train":[106,200,217],"models,":[109],"perform":[111],"using":[114,240],"the":[115,136,142,241],"trained":[116],"models.":[117,137],"Our":[118],"method":[119],"is":[120,164,178],"unique":[121],"utilize":[126],"formatting":[127,145],"information":[128,146],"such":[129],"font":[131],"size":[132],"features":[134],"turns":[139],"out":[140],"use":[143],"lead":[148],"quite":[150],"accurate":[151],"Precision":[156],"recall":[158,172],"0.810":[165],"0.837":[167],"respectively,":[168],"precision":[170],"0.875":[179],"0.895":[181],"respectively":[182],"an":[184],"experiment":[185],"on":[186],"intranet":[187],"data.":[188],"Other":[189],"important":[190],"new":[191],"findings":[192],"work":[195],"include":[196],"models":[201,218],"domain":[204],"apply":[206,223],"another":[209,226],"domain,":[210],"more":[212],"surprisingly":[213],"even":[216],"language":[221],"language.":[227],"Moreover,":[228],"significantly":[231],"improve":[232],"search":[233],"ranking":[234],"results":[235],"document":[237],"retrieval":[238],"by":[239],"extracted":[242],"titles.":[243]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}