{"id":"https://openalex.org/W3185848858","doi":"https://doi.org/10.1145/3459104.3459148","title":"A Framework for Leveraging Contextual Information in Automated Domain Specific Comprehension","display_name":"A Framework for Leveraging Contextual Information in Automated Domain Specific Comprehension","publication_year":2021,"publication_date":"2021-02-19","ids":{"openalex":"https://openalex.org/W3185848858","doi":"https://doi.org/10.1145/3459104.3459148","mag":"3185848858"},"language":"en","primary_location":{"id":"doi:10.1145/3459104.3459148","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459104.3459148","pdf_url":null,"source":{"id":"https://openalex.org/S4306498858","display_name":"2021 International Symposium on Electrical, Electronics and Information Engineering","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Electrical, Electronics and Information Engineering","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/A5067691672","display_name":"Ayush Pradhan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ayush Pradhan","raw_affiliation_strings":["AI Centre of Excellence Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"AI Centre of Excellence Bengaluru, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083673682","display_name":"Eldhose Joy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eldhose Joy","raw_affiliation_strings":["AI Centre of Excellence Mumbai, India"],"affiliations":[{"raw_affiliation_string":"AI Centre of Excellence Mumbai, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060773583","display_name":"Harsha Jawagal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Harsha Jawagal","raw_affiliation_strings":["AI Centre of Excellence Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"AI Centre of Excellence Bengaluru, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060881785","display_name":"Sundar Prasad Jayaraman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sundar Prasad Jayaraman","raw_affiliation_strings":["AI Centre of Excellence Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"AI Centre of Excellence Bengaluru, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067691672"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09889227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"263","last_page":"270"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10260","display_name":"Software Engineering Research","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9936000108718872,"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":0.8410492539405823},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.6989440321922302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5418747663497925},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5417433977127075},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5392016768455505},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4934152662754059},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4835231304168701},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4655004143714905},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.42644497752189636},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.4251851737499237},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4197835922241211},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3536258935928345}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8410492539405823},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6989440321922302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5418747663497925},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5417433977127075},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5392016768455505},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4934152662754059},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4835231304168701},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4655004143714905},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.42644497752189636},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.4251851737499237},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4197835922241211},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3536258935928345},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","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},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459104.3459148","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459104.3459148","pdf_url":null,"source":{"id":"https://openalex.org/S4306498858","display_name":"2021 International Symposium on Electrical, Electronics and Information Engineering","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Electrical, Electronics and Information Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2043147031","https://openalex.org/W2116261113","https://openalex.org/W2250539671","https://openalex.org/W2275056699","https://openalex.org/W2416987009","https://openalex.org/W2564256581","https://openalex.org/W4214717370"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W4381058564","https://openalex.org/W2964413124"],"abstract_inverted_index":{"When":[0],"it":[1,16,132],"comes":[2],"to":[3,22,37,68,90,101,141,196,219,256,265],"information,":[4],"Enterprises":[5],"today":[6],"are":[7,114],"seen":[8],"as":[9,181],"a":[10,13,53,66,81,94,117,124,148,165,205,258,267],"black":[11],"hole,":[12],"mass":[14,41],"of":[15,28,42,60,119,126,170,204,277],"goes":[17],"in":[18,56,74,176,273],"but":[19],"gets":[20],"difficult":[21],"extract":[23],"the":[24,35,58,70,135,161,171,184,198,209,215,221,227,243,246,271,283,287],"practical":[25],"knowledge":[26,218],"out":[27],"it.":[29],"An":[30],"automated":[31,144,185],"system":[32,146,248],"that":[33,87],"has":[34,213],"ability":[36],"consume":[38],"this":[39,61],"large":[40],"information":[43,137],"and":[44,108,128,159,201,225,229,234,286],"provide":[45,266],"specific,":[46],"knowledgeable,":[47],"domain-oriented":[48],"responses":[49],"back,":[50],"will":[51],"go":[52],"long":[54],"way":[55],"unlocking":[57],"value":[59],"large-scale":[62],"unstructured":[63],"information.":[64],"In":[65],"bid":[67],"enrich":[69,220],"answering":[71,222],"system's":[72],"accuracy":[73],"Machine":[75],"Reading":[76],"Comprehension":[77],"(MRC),":[78],"we":[79],"propose":[80],"domain-specific":[82],"Question":[83],"Answers":[84],"(QuAns)":[85],"framework":[86,158],"specifically":[88],"aims":[89,264],"auto-generate":[91],"questions":[92,113],"from":[93,155],"domain-based":[95],"document":[96],"using":[97,123,147],"an":[98,143],"improvised":[99],"Sequence":[100,102],"(Seq2Seq)":[103],"technique":[104,212],"equipped":[105,250],"with":[106,178,251],"Attention":[107],"Copy":[109],"mechanism.":[110],"The":[111,168],"generated":[112,206],"conditioned":[115],"on":[116],"set":[118],"candidate":[120],"answers,":[121],"derived":[122],"combination":[125,177],"heuristic-driven":[127],"graph-based":[129],"techniques.":[130],"Further,":[131],"also":[133],"leverages":[134],"contextual":[136],"by":[138,232,280],"pooling":[139],"strategy":[140],"build":[142],"response":[145,223],"deep":[149],"custom":[150],"fine-tuned":[151],"Bidirectional":[152],"Encoder":[153],"Representations":[154],"Transformers":[156],"(BERT)":[157],"retrieving":[160],"top-k":[162],"contexts":[163],"for":[164,270],"user":[166,244],"query.":[167],"evaluation":[169],"QuAns":[172],"architecture":[173],"is":[174,249],"performed":[175],"human":[179,284],"supervision":[180],"at":[182],"times,":[183],"metrics":[186],"like":[187],"BLEU,":[188],"Exact":[189],"Match":[190],"(EM),":[191],"F1":[192,230],"score,":[193],"etc.":[194],"fail":[195],"gauge":[197],"diverse":[199],"semantic":[200],"structural":[202],"aspects":[203],"response.":[207,260],"Primarily,":[208],"proffered":[210],"ensemble":[211],"leveraged":[214],"augmented":[216],"domain":[217],"efficacy":[224],"improving":[226],"EM":[228],"score":[231],"14.86%":[233],"12.76%":[235],"respectively":[236],"over":[237],"Vanilla":[238],"BERT":[239],"architecture.":[240],"To":[241],"enhance":[242],"experience,":[245],"conversational":[247],"Natural":[252],"Language":[253],"Generation":[254],"(NLG)":[255],"present":[257],"human-readable":[259],"Our":[261],"architectural":[262],"pipeline":[263],"one-stop":[268],"solution":[269],"organizations":[272],"processing":[274],"huge":[275],"volumes":[276],"multidisciplinary":[278],"data":[279],"significantly":[281],"reducing":[282],"introspection":[285],"overhead":[288],"cost.":[289]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
