{"id":"https://openalex.org/W3011292685","doi":"https://doi.org/10.1109/comsnets48256.2020.9027399","title":"Feedback-Based Keyphrase Extraction from Unstructured Text Documents","display_name":"Feedback-Based Keyphrase Extraction from Unstructured Text Documents","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3011292685","doi":"https://doi.org/10.1109/comsnets48256.2020.9027399","mag":"3011292685"},"language":"en","primary_location":{"id":"doi:10.1109/comsnets48256.2020.9027399","is_oa":false,"landing_page_url":"https://doi.org/10.1109/comsnets48256.2020.9027399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on COMmunication Systems & NETworkS (COMSNETS)","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/A5040960396","display_name":"Nishtha Madaan","orcid":"https://orcid.org/0009-0003-7706-1434"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Nishtha Madaan","raw_affiliation_strings":["IBM Research AI, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, New Delhi, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050299062","display_name":"Mudit Saxena","orcid":"https://orcid.org/0009-0009-6971-9906"},"institutions":[{"id":"https://openalex.org/I26604189","display_name":"Shiv Nadar University","ror":"https://ror.org/05aqahr97","country_code":"IN","type":"education","lineage":["https://openalex.org/I26604189"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mudit Saxena","raw_affiliation_strings":["Shiv Nadar University, Gurgaon, India"],"affiliations":[{"raw_affiliation_string":"Shiv Nadar University, Gurgaon, India","institution_ids":["https://openalex.org/I26604189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102917997","display_name":"Hima Patel","orcid":"https://orcid.org/0000-0002-0031-8428"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hima Patel","raw_affiliation_strings":["IBM Research AI, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, Bangalore, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046646390","display_name":"Sameep Mehta","orcid":"https://orcid.org/0000-0002-9599-1526"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sameep Mehta","raw_affiliation_strings":["IBM Research AI, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, Bangalore, India","institution_ids":["https://openalex.org/I4210103279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5040960396"],"corresponding_institution_ids":["https://openalex.org/I4210103279"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51294007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"674","last_page":"676"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9435999989509583,"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/T10028","display_name":"Topic Modeling","score":0.9379000067710876,"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/computer-science","display_name":"Computer science","score":0.862601637840271},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.8247779607772827},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.629953145980835},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.5784440040588379},{"id":"https://openalex.org/keywords/human-in-the-loop","display_name":"Human-in-the-loop","score":0.577155351638794},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.5711357593536377},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.5429243445396423},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4703029990196228},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4253394901752472},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38390451669692993}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.862601637840271},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.8247779607772827},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.629953145980835},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5784440040588379},{"id":"https://openalex.org/C2780626000","wikidata":"https://www.wikidata.org/wiki/Q5936775","display_name":"Human-in-the-loop","level":2,"score":0.577155351638794},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.5711357593536377},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.5429243445396423},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4703029990196228},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4253394901752472},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38390451669692993},{"id":"https://openalex.org/C157915830","wikidata":"https://www.wikidata.org/wiki/Q2928001","display_name":"Bubble","level":2,"score":0.0},{"id":"https://openalex.org/C129307140","wikidata":"https://www.wikidata.org/wiki/Q6795880","display_name":"Maximum bubble pressure method","level":3,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/comsnets48256.2020.9027399","is_oa":false,"landing_page_url":"https://doi.org/10.1109/comsnets48256.2020.9027399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on COMmunication Systems & NETworkS (COMSNETS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8100000023841858,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2925479258","https://openalex.org/W4288264487"],"related_works":["https://openalex.org/W4288099294","https://openalex.org/W2012531322","https://openalex.org/W2402761219","https://openalex.org/W2785900585","https://openalex.org/W2353730437","https://openalex.org/W2490303674","https://openalex.org/W2609066826","https://openalex.org/W2810752900","https://openalex.org/W2329000834","https://openalex.org/W2165504147"],"abstract_inverted_index":{"Machine":[0],"Learning":[1],"experts":[2],"use":[3,54],"classification":[4],"and":[5,40,63,85,135],"tagging":[6],"algorithms":[7],"considering":[8],"the":[9,43,83,99,107,114,117],"black":[10],"box":[11],"nature":[12],"of":[13,37,42,101,109,116],"these":[14,145],"algorithms.":[15],"These":[16],"algorithms,":[17],"primarily":[18],"key-tags":[19,95,110],"extraction":[20,96,111],"from":[21],"unstructured":[22],"text":[23],"documents":[24],"are":[25],"meant":[26],"to":[27,90,93],"capture":[28],"key":[29,48,133],"concepts":[30,134],"in":[31,49,57,72,82,98,112],"a":[32,80,87,94],"document.":[33],"With":[34],"increasing":[35],"amount":[36],"data,":[38,44],"size":[39],"complexity":[41],"this":[45,66,76],"problem":[46,67,108],"is":[47,68],"industrial":[50],"setup.":[51],"Different":[52],"possible":[53],"cases":[55],"being":[56],"IT":[58],"support,":[59],"conversational":[60],"systems/":[61],"chatbots":[62],"financial":[64],"domains,":[65],"important":[69],"as":[70],"shown":[71],"[1],":[73],"[2].":[74],"In":[75],"paper,":[77],"we":[78],"bring":[79],"human":[81,88],"loop,":[84],"enable":[86],"teacher":[89],"give":[91],"feedback":[92],"framework":[97],"form":[100],"natural":[102,129],"language.":[103],"We":[104],"focus":[105],"on":[106],"which":[113],"quality":[115],"output":[118],"can":[119],"easily":[120],"be":[121],"judged":[122],"by":[123],"non-experts.":[124],"Our":[125],"system":[126],"automatically":[127],"reads":[128],"language":[130],"documents,":[131],"extracts":[132],"presents":[136],"an":[137],"interactive":[138],"information":[139],"exploration":[140],"user":[141],"interface":[142],"for":[143],"analysing":[144],"documents.":[146]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}