{"id":"https://openalex.org/W1969938708","doi":"https://doi.org/10.1145/1088622.1088662","title":"A learning based model for headline extraction of news articles to find explanatory sentences for events","display_name":"A learning based model for headline extraction of news articles to find explanatory sentences for events","publication_year":2005,"publication_date":"2005-10-02","ids":{"openalex":"https://openalex.org/W1969938708","doi":"https://doi.org/10.1145/1088622.1088662","mag":"1969938708"},"language":"en","primary_location":{"id":"doi:10.1145/1088622.1088662","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1088622.1088662","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd international conference on Knowledge capture","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/A5103340284","display_name":"Sandip Debnath","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sandip Debnath","raw_affiliation_strings":["Penn State University, University Park, PA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Penn State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001294898","display_name":"C. Lee Giles","orcid":"https://orcid.org/0000-0002-1931-585X"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"C. Lee Giles","raw_affiliation_strings":["Penn State University, University Park, PA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Penn State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":0.7428,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70269826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"189","last_page":"190"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.998199999332428,"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":0.998199999332428,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9819999933242798,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/headline","display_name":"Headline","score":0.987281084060669},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.8306207060813904},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.775023341178894},{"id":"https://openalex.org/keywords/theme","display_name":"Theme (computing)","score":0.5346483588218689},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.505756139755249},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4767683148384094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4758151173591614},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.46365484595298767},{"id":"https://openalex.org/keywords/explanatory-model","display_name":"Explanatory model","score":0.41215765476226807},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2762144207954407},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.23047110438346863}],"concepts":[{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.987281084060669},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.8306207060813904},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.775023341178894},{"id":"https://openalex.org/C33566652","wikidata":"https://www.wikidata.org/wiki/Q1065927","display_name":"Theme (computing)","level":2,"score":0.5346483588218689},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.505756139755249},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4767683148384094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4758151173591614},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.46365484595298767},{"id":"https://openalex.org/C2778638050","wikidata":"https://www.wikidata.org/wiki/Q5421252","display_name":"Explanatory model","level":2,"score":0.41215765476226807},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2762144207954407},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.23047110438346863},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1088622.1088662","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1088622.1088662","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd international conference on Knowledge capture","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.392.8930","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.392.8930","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.svms.org/finance/DebnathGiles2005.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W91182363","https://openalex.org/W2081687495","https://openalex.org/W2086790337","https://openalex.org/W2093390569","https://openalex.org/W2160984494","https://openalex.org/W2952067053","https://openalex.org/W4206765718","https://openalex.org/W6603697625"],"related_works":["https://openalex.org/W4285135530","https://openalex.org/W2380567098","https://openalex.org/W2035489689","https://openalex.org/W906669285","https://openalex.org/W1553197492","https://openalex.org/W85886512","https://openalex.org/W1586468330","https://openalex.org/W1514610457","https://openalex.org/W3173716828","https://openalex.org/W2515595154"],"abstract_inverted_index":{"Metadata":[0],"information":[1,26],"plays":[2],"a":[3,71,107,124],"crucial":[4],"role":[5],"in":[6,63],"augmenting":[7],"document":[8],"organising":[9],"efficiency":[10],"and":[11,19,123],"archivability.":[12],"News":[13],"metadata":[14],"includes":[15],"DateLine,":[16],"ByLine,":[17],"HeadLine":[18,25,45,81],"many":[20],"others.":[21],"We":[22,83,99],"found":[23,43],"that":[24,44,85],"is":[27,129],"useful":[28],"for":[29,38,55,117,136],"guessing":[30],"the":[31,34,80,86,91,102,114],"theme":[32,122],"of":[33,89,110],"news":[35,40],"article.":[36],"Particularly":[37],"financial":[39],"articles,":[41],"we":[42,69],"can":[46],"thus":[47],"be":[48],"specially":[49],"helpful":[50],"to":[51,77,105,112,131],"locate":[52,132],"explanatory":[53,134],"sentences":[54,115,135],"any":[56,133,137],"major":[57],"events":[58],"such":[59],"as":[60],"significant":[61,138],"changes":[62],"stock":[64],"prices.":[65],"In":[66],"this":[67,121],"paper":[68],"explore":[70],"support":[72],"vector":[73],"based":[74],"learning":[75],"approach":[76],"automatically":[78],"extract":[79],"metadata.":[82],"find":[84,113],"classification":[87],"accuracy":[88],"finding":[90],"HeadLines":[92,104],"improves":[93],"if":[94],"DateLines":[95],"are":[96],"identified":[97],"first.":[98],"then":[100],"used":[101],"extracted":[103],"initiate":[106],"pattern":[108],"matching":[109],"keywords":[111],"responsible":[116],"story":[118],"theme.":[119],"Using":[120],"simple":[125],"language":[126],"model":[127],"it":[128],"possible":[130],"price":[139],"change.":[140]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}