{"id":"https://openalex.org/W2767236822","doi":"https://doi.org/10.1145/3132847.3133127","title":"Hybrid MemNet for Extractive Summarization","display_name":"Hybrid MemNet for Extractive Summarization","publication_year":2017,"publication_date":"2017-11-06","ids":{"openalex":"https://openalex.org/W2767236822","doi":"https://doi.org/10.1145/3132847.3133127","mag":"2767236822"},"language":"en","primary_location":{"id":"doi:10.1145/3132847.3133127","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132847.3133127","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1912.11701","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Abhishek Kumar Singh","orcid":null},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Abhishek Kumar Singh","raw_affiliation_strings":["International Institute of Information Technology, Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"International Institute of Information Technology, Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I64189192"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Manish Gupta","orcid":null},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manish Gupta","raw_affiliation_strings":["International Institute of Information Technology, Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"International Institute of Information Technology, Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I64189192"]}]},{"author_position":"last","author":{"id":null,"display_name":"Vasudeva Varma","orcid":null},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vasudeva Varma","raw_affiliation_strings":["International Institute of Information Technology, Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"International Institute of Information Technology, Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I64189192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I64189192"],"apc_list":null,"apc_paid":null,"fwci":0.2077,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.65436101,"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":"2303","last_page":"2306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.995199978351593,"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":0.9108999967575073},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.536899983882904},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.490200012922287},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4666999876499176},{"id":"https://openalex.org/keywords/multi-document-summarization","display_name":"Multi-document summarization","score":0.4535999894142151},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.3628999888896942},{"id":"https://openalex.org/keywords/natural-language-understanding","display_name":"Natural language understanding","score":0.35370001196861267}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9108999967575073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7908999919891357},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6653000116348267},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5446000099182129},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.536899983882904},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.490200012922287},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4666999876499176},{"id":"https://openalex.org/C134714966","wikidata":"https://www.wikidata.org/wiki/Q6934448","display_name":"Multi-document summarization","level":3,"score":0.4535999894142151},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.35370001196861267},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.3314000070095062},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.31189998984336853},{"id":"https://openalex.org/C66945725","wikidata":"https://www.wikidata.org/wiki/Q18388823","display_name":"Text graph","level":3,"score":0.28529998660087585},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26669999957084656},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25450000166893005},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3132847.3133127","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3132847.3133127","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1912.11701","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.11701","pdf_url":"https://arxiv.org/pdf/1912.11701","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1912.11701","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.11701","pdf_url":"https://arxiv.org/pdf/1912.11701","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2054211469","https://openalex.org/W2067619114","https://openalex.org/W2101390659","https://openalex.org/W2115221470","https://openalex.org/W2122497354","https://openalex.org/W2140440594","https://openalex.org/W2150824314","https://openalex.org/W2952138241","https://openalex.org/W2997617958"],"related_works":[],"abstract_inverted_index":{"Extractive":[0],"text":[1],"summarization":[2,62],"has":[3],"been":[4,33],"an":[5],"extensive":[6],"research":[7],"problem":[8],"in":[9,35],"the":[10,17,28,67,88,110],"field":[11],"of":[12,71,90],"natural":[13],"language":[14],"understanding.":[15],"While":[16],"conventional":[18],"approaches":[19],"rely":[20],"mostly":[21],"on":[22,96],"manually":[23],"compiled":[24],"features":[25],"to":[26],"generate":[27],"summary,":[29],"few":[30],"attempts":[31],"have":[32],"made":[34],"developing":[36],"data-driven":[37,49],"systems":[38],"for":[39,59],"extractive":[40],"summarization.":[41],"To":[42],"this":[43],"end,":[44],"we":[45,54],"present":[46],"a":[47,72],"fully":[48],"end-to-end":[50],"deep":[51],"network":[52,65],"which":[53],"call":[55],"as":[56],"Hybrid":[57],"MemNet":[58],"single":[60],"document":[61,73],"task.":[63],"The":[64],"learns":[66],"continuous":[68],"unified":[69],"representation":[70],"before":[74],"generating":[75],"its":[76],"summary.":[77],"It":[78],"jointly":[79],"captures":[80],"local":[81],"and":[82],"global":[83],"sentential":[84],"information":[85],"along":[86],"with":[87,109],"notion":[89],"summary":[91],"worthy":[92],"sentences.":[93],"Experimental":[94],"results":[95],"two":[97],"different":[98],"corpora":[99],"confirm":[100],"that":[101],"our":[102],"model":[103],"shows":[104],"significant":[105],"performance":[106],"gains":[107],"compared":[108],"state-of-the-art":[111],"baselines.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2017-11-17T00:00:00"}