{"id":"https://openalex.org/W2914823529","doi":"https://doi.org/10.1109/tlt.2019.2897997","title":"Feature Engineering and Ensemble-Based Approach for Improving Automatic Short-Answer Grading Performance","display_name":"Feature Engineering and Ensemble-Based Approach for Improving Automatic Short-Answer Grading Performance","publication_year":2019,"publication_date":"2019-02-07","ids":{"openalex":"https://openalex.org/W2914823529","doi":"https://doi.org/10.1109/tlt.2019.2897997","mag":"2914823529"},"language":"en","primary_location":{"id":"doi:10.1109/tlt.2019.2897997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tlt.2019.2897997","pdf_url":null,"source":{"id":"https://openalex.org/S130363450","display_name":"IEEE Transactions on Learning Technologies","issn_l":"1939-1382","issn":["1939-1382","2372-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Learning Technologies","raw_type":"journal-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/A5014778395","display_name":"Archana Sahu","orcid":"https://orcid.org/0000-0001-8724-6158"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Archana Sahu","raw_affiliation_strings":["Centre for Educational Technology, Indian Institute of Technology Kharagpur, Kharagpur, India"],"affiliations":[{"raw_affiliation_string":"Centre for Educational Technology, Indian Institute of Technology Kharagpur, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063438965","display_name":"Plaban Kumar Bhowmick","orcid":"https://orcid.org/0000-0002-6573-0093"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Plaban Kumar Bhowmick","raw_affiliation_strings":["Centre for Educational Technology, Indian Institute of Technology Kharagpur, Kharagpur, India"],"affiliations":[{"raw_affiliation_string":"Centre for Educational Technology, Indian Institute of Technology Kharagpur, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014778395"],"corresponding_institution_ids":["https://openalex.org/I145894827"],"apc_list":null,"apc_paid":null,"fwci":3.3604,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.93882255,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"13","issue":"1","first_page":"77","last_page":"90"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"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":0.9997000098228455,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9854000210762024,"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":0.9832000136375427,"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":0.8122175931930542},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.6686074733734131},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6653145551681519},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.579582154750824},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.5548252463340759},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5400816202163696},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.5208250284194946},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5060204863548279},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4952367842197418},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4655139446258545},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4414195120334625},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4111535847187042},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39981600642204285},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3507612347602844},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.21673905849456787},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10928022861480713},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07778185606002808}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8122175931930542},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.6686074733734131},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6653145551681519},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.579582154750824},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.5548252463340759},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5400816202163696},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.5208250284194946},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5060204863548279},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4952367842197418},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4655139446258545},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4414195120334625},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4111535847187042},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39981600642204285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3507612347602844},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.21673905849456787},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10928022861480713},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07778185606002808},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tlt.2019.2897997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tlt.2019.2897997","pdf_url":null,"source":{"id":"https://openalex.org/S130363450","display_name":"IEEE Transactions on Learning Technologies","issn_l":"1939-1382","issn":["1939-1382","2372-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Learning Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W43048615","https://openalex.org/W46659105","https://openalex.org/W331959685","https://openalex.org/W975464243","https://openalex.org/W1566018662","https://openalex.org/W1592081640","https://openalex.org/W1594588104","https://openalex.org/W1614298861","https://openalex.org/W1714665356","https://openalex.org/W1880262756","https://openalex.org/W1930624869","https://openalex.org/W1988790447","https://openalex.org/W2016023958","https://openalex.org/W2016210396","https://openalex.org/W2025595753","https://openalex.org/W2028718222","https://openalex.org/W2028742638","https://openalex.org/W2044434631","https://openalex.org/W2061082730","https://openalex.org/W2072284402","https://openalex.org/W2100495367","https://openalex.org/W2115584598","https://openalex.org/W2122825543","https://openalex.org/W2133436118","https://openalex.org/W2135046866","https://openalex.org/W2137226992","https://openalex.org/W2142120379","https://openalex.org/W2147152072","https://openalex.org/W2154652894","https://openalex.org/W2164547069","https://openalex.org/W2180016317","https://openalex.org/W2185606683","https://openalex.org/W2200480317","https://openalex.org/W2250874787","https://openalex.org/W2251456640","https://openalex.org/W2251803266","https://openalex.org/W2293665254","https://openalex.org/W2474948357","https://openalex.org/W2523104597","https://openalex.org/W2585847175","https://openalex.org/W2613678836","https://openalex.org/W2739522917","https://openalex.org/W2950577311","https://openalex.org/W2963000584","https://openalex.org/W4213175497","https://openalex.org/W4229781220","https://openalex.org/W4240294902","https://openalex.org/W6602002561","https://openalex.org/W6633661181","https://openalex.org/W6636510571","https://openalex.org/W6639619044","https://openalex.org/W6677506011","https://openalex.org/W6679642630","https://openalex.org/W6682631176","https://openalex.org/W6684151790","https://openalex.org/W6685745461","https://openalex.org/W6687774679","https://openalex.org/W6691268816","https://openalex.org/W6691654054","https://openalex.org/W6727156156","https://openalex.org/W7036024786"],"related_works":["https://openalex.org/W2794896638","https://openalex.org/W1807784185","https://openalex.org/W4390905871","https://openalex.org/W3202800081","https://openalex.org/W1909207154","https://openalex.org/W3124390867","https://openalex.org/W3101614107","https://openalex.org/W3204228978","https://openalex.org/W1514365828","https://openalex.org/W4390971112"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,49,116],"studied":[4],"different":[5,81,142],"automatic":[6],"short":[7,126],"answer":[8],"grading":[9,63,88,191],"(ASAG)":[10],"systems":[11],"to":[12,59,94],"provide":[13],"a":[14,139],"comprehensive":[15],"view":[16],"of":[17,37,141,161,172,195,217],"the":[18,26,38,66,72,159,166,175,233],"feature":[19,46,214],"spaces":[20],"explored":[21],"by":[22,204],"previous":[23,30],"works.":[24],"While":[25],"performance":[27,64,192,231],"reported":[28],"in":[29,69,74,98,170,193,226,230,236],"works":[31],"have":[32,55,117,185,223],"been":[33,56,90,136,156,186,224],"encouraging,":[34],"systematic":[35,45],"study":[36,79],"features":[39,82,107,120],"is":[40,198],"lacking.":[41],"Apart":[42,101],"from":[43,102,201],"providing":[44],"space":[47],"exploration,":[48],"also":[50],"presented":[51],"ensemble":[52],"methods":[53,235],"that":[54,202,213],"experimentally":[57],"validated":[58],"exhibit":[60],"significantly":[61],"higher":[62],"over":[65,80,232],"existing":[67,234],"papers":[68],"almost":[70],"all":[71],"datasets":[73],"ASAG":[75,154,197,237],"domain.":[76,238],"A":[77],"comparative":[78],"and":[83,114,182,220],"regression":[84,143,167,207],"models":[85,123,144],"toward":[86],"short-answer":[87],"has":[89,135,155,211],"performed":[91],"with":[92,145],"respect":[93],"evaluation":[95],"metrics":[96],"used":[97,187],"evaluating":[99],"ASAG.":[100],"traditional":[103],"text":[104],"similarity":[105],"based":[106,130,148,180],"like":[108,121],"WordNet":[109],"similarity,":[110],"latent":[111],"semantic":[112],"analysis,":[113],"others,":[115],"introduced":[118],"novel":[119,218],"topic":[122],"suited":[124],"for":[125,165,188],"text,":[127],"relevance":[128],"feedback":[129],"features.":[131],"An":[132],"ensemble-based":[133,196],"model":[134],"built":[137],"using":[138],"combination":[140],"an":[146,205],"approach":[147],"on":[149,158],"stacked":[150],"regression.":[151],"The":[152,190],"proposed":[153],"tested":[157],"University":[160],"North":[162],"Texas":[163],"dataset":[164],"task,":[168,174],"whereas":[169],"case":[171,194],"classification":[173],"student":[176],"response":[177],"analysis":[178],"(SRA)":[179],"ScientsBank":[181],"Beetle":[183],"corpus":[184],"evaluation.":[189],"highly":[199],"boosted":[200],"exhibited":[203],"individual":[206],"model.":[208],"Extensive":[209],"experimentation":[210],"revealed":[212],"selection,":[215],"introduction":[216],"features,":[219],"regressor":[221],"stacking":[222],"instrumental":[225],"achieving":[227],"considerable":[228],"improvement":[229]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":4}],"updated_date":"2026-02-25T08:12:03.925757","created_date":"2025-10-10T00:00:00"}