{"id":"https://openalex.org/W2966697108","doi":"https://doi.org/10.24963/ijcai.2019/718","title":"Aligning Learning Outcomes to Learning Resources: A Lexico-Semantic Spatial Approach","display_name":"Aligning Learning Outcomes to Learning Resources: A Lexico-Semantic Spatial Approach","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2966697108","doi":"https://doi.org/10.24963/ijcai.2019/718","mag":"2966697108"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/718","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/718","pdf_url":"https://www.ijcai.org/proceedings/2019/0718.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0718.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057314288","display_name":"Swarnadeep Saha","orcid":"https://orcid.org/0000-0002-6972-3448"},"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":"Swarnadeep Saha","raw_affiliation_strings":["IBM Research - India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research - India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086802034","display_name":"Malolan Chetlur","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":"Malolan Chetlur","raw_affiliation_strings":["IBM Research - India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research - India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017064237","display_name":"Tejas I. Dhamecha","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":"Tejas Indulal Dhamecha","raw_affiliation_strings":["IBM Research - India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research - India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064925471","display_name":"W M Gayathri K Wijayarathna","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"W M Gayathri K Wijayarathna","raw_affiliation_strings":["Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033763863","display_name":"Red Mendoza","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Red Mendoza","raw_affiliation_strings":["Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091032782","display_name":"Paul Gagnon","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Paul Gagnon","raw_affiliation_strings":["Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022181308","display_name":"Nabil Zary","orcid":"https://orcid.org/0000-0001-8999-6999"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Nabil Zary","raw_affiliation_strings":["Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033214720","display_name":"Shantanu Godbole","orcid":"https://orcid.org/0009-0001-7071-9438"},"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":"Shantanu Godbole","raw_affiliation_strings":["IBM Research - India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research - India","institution_ids":["https://openalex.org/I4210103279"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2187,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51477672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"5168","last_page":"5174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9872000217437744,"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":0.9872000217437744,"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/T12171","display_name":"Open Education and E-Learning","score":0.9829999804496765,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T12478","display_name":"Wikis in Education and Collaboration","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/3315","display_name":"Communication"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8400617837905884},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6538131833076477},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5924317240715027},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5665069222450256},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5431647896766663},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5288309454917908},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5256448984146118},{"id":"https://openalex.org/keywords/lexico","display_name":"Lexico","score":0.5110455751419067},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4804915189743042},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.14775598049163818}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8400617837905884},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6538131833076477},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5924317240715027},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5665069222450256},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5431647896766663},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5288309454917908},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5256448984146118},{"id":"https://openalex.org/C2777776507","wikidata":"https://www.wikidata.org/wiki/Q4807054","display_name":"Lexico","level":3,"score":0.5110455751419067},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4804915189743042},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.14775598049163818},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/718","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/718","pdf_url":"https://www.ijcai.org/proceedings/2019/0718.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/718","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/718","pdf_url":"https://www.ijcai.org/proceedings/2019/0718.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2966697108.pdf","grobid_xml":"https://content.openalex.org/works/W2966697108.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1862888253","https://openalex.org/W1906276607","https://openalex.org/W2122876878","https://openalex.org/W2402477247","https://openalex.org/W2415204069","https://openalex.org/W2508865106","https://openalex.org/W2512217112","https://openalex.org/W2515248967","https://openalex.org/W2539671052","https://openalex.org/W2572137549","https://openalex.org/W2597655663","https://openalex.org/W2962716111","https://openalex.org/W2963918774","https://openalex.org/W3028046543","https://openalex.org/W4299606006","https://openalex.org/W4300874613"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"Aligning":[0],"Learning":[1,8],"Outcomes":[2],"(LO)":[3],"to":[4,13,42,65,110,152,183,214,235],"relevant":[5,33,66,84,109,216],"portions":[6],"of":[7,35,55,68,75,83,89,98,104,131,140,149,178,194],"Resources":[9],"(LR)":[10,38],"is":[11,40,59,94],"necessary":[12],"help":[14],"students":[15],"quickly":[16],"navigate":[17,213],"within":[18,201,227],"the":[19,25,32,52,73,81,101,125,132,137,147,173,176,181,186,192,195,202,219],"recommended":[20],"learning":[21],"material.":[22],"In":[23,47],"general,":[24],"problem":[26,54],"can":[27,86,212],"be":[28,87,108],"viewed":[29],"as":[30,233],"finding":[31],"sections":[34],"a":[36,43,61,95,118,150,169,210,215,228],"document":[37],"that":[39,80,123],"pertinent":[41],"broad":[44],"question":[45],"(LO).":[46],"this":[48,114],"paper,":[49],"we":[50,116],"introduce":[51],"novel":[53,119],"aligning":[56],"LOs":[57],"(LO":[58],"usually":[60],"sentence":[62],"long":[63],"text)":[64],"pages":[67,85,179],"LRs":[69],"(LRs":[70],"are":[71],"in":[72,180],"form":[74],"slide":[76,231],"decks).":[77],"We":[78,189,205],"observe":[79],"set":[82,97],"composed":[88],"multiple":[90,111],"chunks":[91],"(a":[92],"chunk":[93],"contiguous":[96],"pages)":[99],"and":[100,128,134,158,198],"same":[102],"page":[103,151,163,217,222,230],"an":[105,153],"LR":[106,182],"might":[107],"LOs.":[112],"To":[113],"end,":[115],"develop":[117],"Lexico-Semantic":[120],"Spatial":[121],"approach":[122,144],"captures":[124],"lexical,":[126,196],"semantic,":[127,197],"spatial":[129,166,199],"aspects":[130],"task,":[133],"also":[135],"alleviates":[136],"limited":[138],"availability":[139],"training":[141],"data.":[142],"Our":[143],"first":[145,220],"identifies":[146],"relevancy":[148],"LO":[154],"by":[155,223,238],"using":[156],"lexical":[157],"semantic":[159],"features":[160],"from":[161,218],"each":[162],"independently.":[164],"The":[165],"model":[167],"at":[168],"later":[170],"stage":[171],"exploits":[172],"dependencies":[174],"between":[175],"sequence":[177],"further":[184],"improve":[185],"alignment":[187],"task.":[188],"empirically":[190],"establish":[191],"importance":[193],"models":[200],"proposed":[203],"approach.":[204],"show":[206],"that,":[207],"on":[208],"average,":[209],"student":[211],"predicted":[221],"about":[224],"four":[225],"clicks":[226,237],"38":[229],"deck,":[232],"compared":[234],"two":[236],"human":[239],"experts.":[240]},"counts_by_year":[{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}