{"id":"https://openalex.org/W4312827643","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892263","title":"A Deep Neural Approach to KGQA via SPARQL Silhouette Generation","display_name":"A Deep Neural Approach to KGQA via SPARQL Silhouette Generation","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312827643","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892263"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892263","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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/A5090787541","display_name":"Sukannya Purkayastha","orcid":"https://orcid.org/0000-0002-7559-0522"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sukannya Purkayastha","raw_affiliation_strings":["TCS Research,India","TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research,India","institution_ids":["https://openalex.org/I55215948"]},{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084895231","display_name":"Saswati Dana","orcid":null},"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":"Saswati Dana","raw_affiliation_strings":["IBM Research,India","IBM Research, India"],"affiliations":[{"raw_affiliation_string":"IBM Research,India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM Research, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109547753","display_name":"Dinesh Garg","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dinesh Garg","raw_affiliation_strings":["TCS Research,India","TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research,India","institution_ids":["https://openalex.org/I55215948"]},{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000408974","display_name":"Dinesh Khandelwal","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dinesh Khandelwal","raw_affiliation_strings":["TCS Research,India","TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research,India","institution_ids":["https://openalex.org/I55215948"]},{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114026317","display_name":"G P Shrivatsa Bhargav","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"G.P Shrivatsa Bhargav","raw_affiliation_strings":["TCS Research,India","TCS Research, India"],"affiliations":[{"raw_affiliation_string":"TCS Research,India","institution_ids":["https://openalex.org/I55215948"]},{"raw_affiliation_string":"TCS Research, India","institution_ids":["https://openalex.org/I55215948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5090787541"],"corresponding_institution_ids":["https://openalex.org/I55215948"],"apc_list":null,"apc_paid":null,"fwci":1.0394,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.78813833,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9972000122070312,"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/sparql","display_name":"SPARQL","score":0.8830999135971069},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8806546926498413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5862223505973816},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.562730610370636},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5200733542442322},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.44763267040252686},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.44352227449417114},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.437439501285553},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4297715127468109},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.36964279413223267},{"id":"https://openalex.org/keywords/rdf","display_name":"RDF","score":0.345861554145813},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.2632198929786682},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20779478549957275}],"concepts":[{"id":"https://openalex.org/C41009113","wikidata":"https://www.wikidata.org/wiki/Q54871","display_name":"SPARQL","level":4,"score":0.8830999135971069},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8806546926498413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5862223505973816},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.562730610370636},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5200733542442322},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.44763267040252686},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.44352227449417114},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.437439501285553},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4297715127468109},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.36964279413223267},{"id":"https://openalex.org/C147497476","wikidata":"https://www.wikidata.org/wiki/Q54872","display_name":"RDF","level":3,"score":0.345861554145813},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.2632198929786682},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20779478549957275},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892263","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W580074167","https://openalex.org/W1496189301","https://openalex.org/W1539162551","https://openalex.org/W1552847225","https://openalex.org/W1895891284","https://openalex.org/W2011992920","https://openalex.org/W2094728533","https://openalex.org/W2111742432","https://openalex.org/W2126170172","https://openalex.org/W2133564696","https://openalex.org/W2148721079","https://openalex.org/W2194775991","https://openalex.org/W2250225488","https://openalex.org/W2251079237","https://openalex.org/W2251287417","https://openalex.org/W2252136820","https://openalex.org/W2493916176","https://openalex.org/W2495998536","https://openalex.org/W2567070169","https://openalex.org/W2572289264","https://openalex.org/W2613904329","https://openalex.org/W2751448157","https://openalex.org/W2763039547","https://openalex.org/W2766209926","https://openalex.org/W2806451918","https://openalex.org/W2915836468","https://openalex.org/W2962713807","https://openalex.org/W2962745909","https://openalex.org/W2963617989","https://openalex.org/W2963794306","https://openalex.org/W2963900171","https://openalex.org/W2963993485","https://openalex.org/W2970293467","https://openalex.org/W2978030033","https://openalex.org/W2980401255","https://openalex.org/W2980737818","https://openalex.org/W2988898811","https://openalex.org/W3028709955","https://openalex.org/W3034273250","https://openalex.org/W3034963999","https://openalex.org/W3104616515","https://openalex.org/W3104748221","https://openalex.org/W3107803811","https://openalex.org/W3118511871","https://openalex.org/W3120503433","https://openalex.org/W3190271517","https://openalex.org/W6610080458","https://openalex.org/W6617055948","https://openalex.org/W6629631241","https://openalex.org/W6632425215","https://openalex.org/W6639582993","https://openalex.org/W6676848125","https://openalex.org/W6679434410","https://openalex.org/W6691476020","https://openalex.org/W6723646743","https://openalex.org/W6732282177","https://openalex.org/W6737778391","https://openalex.org/W6743367031","https://openalex.org/W6745201480","https://openalex.org/W6746308314","https://openalex.org/W6768079693","https://openalex.org/W6778608065","https://openalex.org/W6779914344","https://openalex.org/W6786294978"],"related_works":["https://openalex.org/W2615202182","https://openalex.org/W4206665951","https://openalex.org/W2904139343","https://openalex.org/W2529794967","https://openalex.org/W2604011835","https://openalex.org/W2978246852","https://openalex.org/W3139465322","https://openalex.org/W2484233589","https://openalex.org/W2528203718","https://openalex.org/W4241483715"],"abstract_inverted_index":{"Knowledge":[0,21],"Graph":[1,145],"Question":[2],"Answering":[3],"(KGQA)":[4],"has":[5],"become":[6],"a":[7,44,102,118,124,127,135,143],"prominent":[8],"area":[9],"in":[10,61,164],"natural":[11,38,65],"language":[12,39,66],"processing":[13],"due":[14],"to":[15,32,63,68,108,151,184,203],"the":[16,29,34,74,110,130,153,156,161,165,185],"emergence":[17],"of":[18,79,114,129,139,155],"large":[19],"scale":[20],"Graphs":[22],"(KGs).":[23],"Semantic":[24],"parsing":[25],"based":[26,56],"approach":[27,116,141,197],"is":[28,41,198],"predominant":[30],"direction":[31],"solve":[33,109],"KGQA":[35,75,111,205],"task":[36],"where":[37,86],"question":[40,125],"translated":[42],"into":[43,126],"logic":[45],"form":[46],"such":[47],"as":[48],"SPARQL":[49,132,136,157],"query.":[50],"Recently":[51],"Neural":[52,144],"Machine":[53],"Translation":[54],"(NMT)":[55],"approaches":[57],"are":[58,91,208],"gaining":[59],"momentum":[60],"order":[62],"translate":[64],"query":[67,70,133],"structured":[69],"languages":[71],"thereby":[72],"solving":[73],"task.":[76,112],"However,":[77],"most":[78],"these":[80],"methods":[81],"struggle":[82],"with":[83],"out-of-vocabulary":[84],"words":[85],"test":[87],"entities":[88],"and":[89,177,200],"relations":[90,163],"not":[92],"seen":[93],"during":[94],"training":[95],"time.":[96],"In":[97],"this":[98],"work,":[99],"we":[100,173],"propose":[101],"modular":[103],"two":[104,190],"stage":[105],"neural":[106],"architecture":[107],"Stage-I":[113],"our":[115,140,195],"comprises":[117,142],"NMT-based":[119],"seq2seq":[120],"module":[121,148],"that":[122,172,207],"translates":[123],"sketch":[128],"desired":[131],"called":[134],"silhouette.":[137],"Stage-II":[138],"Search":[146],"(NGS)":[147],"which":[149],"aims":[150],"improve":[152],"quality":[154],"silhouette":[158],"by":[159],"detecting":[160],"right":[162],"underlying":[166],"knowledge":[167],"graph.":[168],"Experimental":[169],"results":[170,183],"show":[171],"achieve":[174],"substantial":[175],"improvements":[176],"obtain":[178],"state-of-the-art":[179],"performance":[180],"or":[181],"comparable":[182],"best":[186],"performing":[187],"systems":[188],"on":[189],"benchmark":[191],"datasets.":[192],"We":[193],"believe,":[194],"proposed":[196],"novel":[199],"will":[201],"lead":[202],"dynamic":[204],"solutions":[206],"well-suited":[209],"for":[210],"practical":[211],"applications.":[212]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
