{"id":"https://openalex.org/W4283449588","doi":"https://doi.org/10.48550/arxiv.2206.11848","title":"Obj2Sub: Unsupervised Conversion of Objective to Subjective Questions","display_name":"Obj2Sub: Unsupervised Conversion of Objective to Subjective Questions","publication_year":2022,"publication_date":"2022-05-25","ids":{"openalex":"https://openalex.org/W4283449588","doi":"https://doi.org/10.48550/arxiv.2206.11848"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2206.11848","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.11848","pdf_url":"https://arxiv.org/pdf/2206.11848","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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2206.11848","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032546196","display_name":"Aarish Chhabra","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chhabra, Aarish","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007262591","display_name":"Nandini Bansal","orcid":"https://orcid.org/0000-0002-1849-0170"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bansal, Nandini","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004960177","display_name":"V Venktesh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"V, Venktesh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047987914","display_name":"Mukesh Mohania","orcid":"https://orcid.org/0000-0003-4429-1412"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohania, Mukesh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5000205227","display_name":"Deep Dwivedi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dwivedi, Deep","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032546196"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14025","display_name":"Educational Technology and Assessment","score":0.9422000050544739,"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"}},"topics":[{"id":"https://openalex.org/T14025","display_name":"Educational Technology and Assessment","score":0.9422000050544739,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9057000279426575,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/task","display_name":"Task (project management)","score":0.7180424928665161},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7053229808807373},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.5810806751251221},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5764856338500977},{"id":"https://openalex.org/keywords/gauge","display_name":"Gauge (firearms)","score":0.5331757664680481},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.5257859230041504},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4829941987991333},{"id":"https://openalex.org/keywords/subject","display_name":"Subject (documents)","score":0.4801611304283142},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4342314600944519},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3940183222293854},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.20945057272911072},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.17918777465820312},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06256574392318726}],"concepts":[{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7180424928665161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7053229808807373},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.5810806751251221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5764856338500977},{"id":"https://openalex.org/C40976572","wikidata":"https://www.wikidata.org/wiki/Q2330873","display_name":"Gauge (firearms)","level":2,"score":0.5331757664680481},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5257859230041504},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4829941987991333},{"id":"https://openalex.org/C2777855551","wikidata":"https://www.wikidata.org/wiki/Q12310021","display_name":"Subject (documents)","level":2,"score":0.4801611304283142},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4342314600944519},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3940183222293854},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.20945057272911072},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.17918777465820312},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06256574392318726},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C161191863","wikidata":"https://www.wikidata.org/wiki/Q199655","display_name":"Library science","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2206.11848","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.11848","pdf_url":"https://arxiv.org/pdf/2206.11848","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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2206.11848","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2206.11848","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2206.11848","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.11848","pdf_url":"https://arxiv.org/pdf/2206.11848","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":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.8500000238418579,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4388258507","https://openalex.org/W2392013855","https://openalex.org/W4318064328","https://openalex.org/W2357926602","https://openalex.org/W3200517220","https://openalex.org/W2374569605","https://openalex.org/W2386062718","https://openalex.org/W4393047559","https://openalex.org/W899618282"],"abstract_inverted_index":{"Exams":[0],"are":[1],"conducted":[2],"to":[3,73],"test":[4],"the":[5,9,13,20,34,38,64,70,82],"learner's":[6],"understanding":[7],"of":[8,22,67],"subject.":[10],"To":[11],"prevent":[12],"learners":[14],"from":[15],"guessing":[16],"or":[17],"exchanging":[18],"solutions,":[19],"mode":[21],"tests":[23],"administered":[24],"must":[25],"have":[26],"sufficient":[27],"subjective":[28,74],"questions":[29,72],"that":[30,78],"can":[31],"gauge":[32],"whether":[33],"learner":[35],"has":[36],"understood":[37],"concept":[39],"by":[40,86,90],"mandating":[41],"a":[42,51],"detailed":[43],"answer.":[44],"Hence,":[45],"in":[46],"this":[47],"paper,":[48],"we":[49],"propose":[50],"novel":[52,65],"hybrid":[53],"unsupervised":[54],"approach":[55,80],"leveraging":[56],"rule-based":[57],"methods":[58],"and":[59,92],"pre-trained":[60],"dense":[61],"retrievers":[62],"for":[63],"task":[66],"automatically":[68],"converting":[69],"objective":[71],"questions.":[75],"We":[76],"observe":[77],"our":[79],"outperforms":[81],"existing":[83],"data-driven":[84],"approaches":[85],"36.45%":[87],"as":[88],"measured":[89],"Recall@k":[91],"Precision@k.":[93]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}