{"id":"https://openalex.org/W4280541419","doi":"https://doi.org/10.48550/arxiv.2205.05976","title":"TaDeR: A New Task Dependency Recommendation for Project Management Platform","display_name":"TaDeR: A New Task Dependency Recommendation for Project Management Platform","publication_year":2022,"publication_date":"2022-05-12","ids":{"openalex":"https://openalex.org/W4280541419","doi":"https://doi.org/10.48550/arxiv.2205.05976"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2205.05976","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.05976","pdf_url":"https://arxiv.org/pdf/2205.05976","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/2205.05976","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101906834","display_name":"Quynh Nguyen","orcid":"https://orcid.org/0000-0003-3225-5422"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nguyen, Quynh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012828087","display_name":"Dac H. Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Dac H.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110846728","display_name":"Son T. Huynh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huynh, Son T.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017181940","display_name":"Hoa Khanh Dam","orcid":"https://orcid.org/0000-0003-4246-0526"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dam, Hoa K.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5051882105","display_name":"Binh T. Nguyen","orcid":"https://orcid.org/0000-0001-5249-9702"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Binh T.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101906834"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9804999828338623,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12127","display_name":"Software System Performance and Reliability","score":0.9804999828338623,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.9660000205039978,"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/T11122","display_name":"Online Learning and Analytics","score":0.9546999931335449,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.733877420425415},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6314074397087097},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5117390155792236},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.49203893542289734},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.47217077016830444},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.46152937412261963},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.45394307374954224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44710710644721985},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4300594627857208},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4277192950248718},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.4141707122325897},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33202967047691345},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12408772110939026},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10932189226150513},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09826025366783142}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.733877420425415},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6314074397087097},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5117390155792236},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.49203893542289734},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.47217077016830444},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.46152937412261963},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.45394307374954224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44710710644721985},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4300594627857208},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4277192950248718},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.4141707122325897},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33202967047691345},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12408772110939026},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10932189226150513},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09826025366783142},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2205.05976","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.05976","pdf_url":"https://arxiv.org/pdf/2205.05976","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.2205.05976","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2205.05976","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:2205.05976","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.05976","pdf_url":"https://arxiv.org/pdf/2205.05976","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":[{"id":"https://metadata.un.org/sdg/9","score":0.6399999856948853,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W2019538911","https://openalex.org/W2467200550","https://openalex.org/W1996805379","https://openalex.org/W4234584818"],"abstract_inverted_index":{"Many":[0],"startups":[1],"and":[2,11,16,45,49,93,114,128,138,152,160,162,182,191,240,242,258,260,276,292],"companies":[3],"worldwide":[4],"have":[5],"been":[6],"using":[7,133,149,165],"project":[8],"management":[9],"software":[10,21],"tools":[12],"to":[13,30,47,54,72,99,118],"monitor,":[14],"track":[15],"manage":[17],"their":[18],"projects.":[19],"For":[20],"projects,":[22],"the":[23,28,31,51,81,120,129,188,195,213,217,223,250,265,282],"number":[24,37],"of":[25,43,57,126,144,246],"tasks":[26,74],"from":[27,112,116],"beginning":[29],"end":[32],"is":[33],"quite":[34],"a":[35,41,55,77,95],"large":[36,109],"that":[38,80,231],"sometimes":[39],"takes":[40],"lot":[42],"time":[44,214],"effort":[46],"search":[48],"link":[50],"current":[52],"task":[53,68,79],"group":[56],"previous":[58],"ones":[59],"for":[60],"further":[61],"references.":[62],"This":[63],"paper":[64],"proposes":[65],"an":[66,88],"efficient":[67,89],"dependency":[69],"recommendation":[70,224],"algorithm":[71],"suggest":[73],"dependent":[75],"on":[76,106],"given":[78],"user":[82],"has":[83],"just":[84],"created.":[85],"We":[86,102,140],"present":[87],"feature":[90],"engineering":[91],"step":[92,219],"construct":[94],"deep":[96],"neural":[97],"network":[98],"this":[100,204],"aim.":[101],"performed":[103],"extensive":[104],"experiments":[105],"two":[107,134],"different":[108],"projects":[110],"(MDLSITE":[111],"moodle.org":[113],"FLUME":[115],"apache.org)":[117],"find":[119],"best":[121,130,196],"features":[122,127],"in":[123,198,216,238,244,256,262,272,279],"28":[124],"combinations":[125],"performance":[131],"model":[132,193,205,269,286],"embedding":[135],"methods":[136],"(GloVe":[137],"FastText).":[139],"consider":[141],"three":[142],"types":[143],"models":[145,164],"(GRU,":[146],"CNN,":[147],"LSTM)":[148],"Accuracy@K,":[150],"MRR@K,":[151],"Recall@K":[153],"(where":[154],"K":[155],"=":[156],"1,":[157],"2,":[158],"3,":[159],"5)":[161],"baseline":[163],"traditional":[166],"methods:":[167],"TF-IDF":[168],"with":[169],"various":[170],"matching":[171],"score":[172],"calculating":[173],"such":[174],"as":[175,206],"cosine":[176],"similarity,":[177],"Euclidean":[178],"distance,":[179,181],"Manhattan":[180],"Chebyshev":[183],"distance.":[184],"After":[185],"many":[186],"experiments,":[187],"GloVe":[189],"Embedding":[190],"CNN":[192],"reached":[194,270],"result":[197],"our":[199,207,232,268,285],"dataset,":[200,252,284],"so":[201],"we":[202,253],"chose":[203],"proposed":[208,233],"method.":[209],"In":[210,264,281],"addition,":[211],"adding":[212],"filter":[215],"post-processing":[218],"can":[220,235],"significantly":[221],"improve":[222],"system's":[225],"performance.":[226],"The":[227],"experimental":[228],"results":[229],"show":[230],"method":[234],"reach":[236],"0.2335":[237],"Accuracy@1":[239,257],"MRR@1":[241,259],"0.2011":[243],"Recall@1":[245],"dataset":[247],"FLUME.":[248,280],"With":[249],"MDLSITE":[251,283],"obtained":[254],"0.1258":[255],"0.1141":[261],"Recall@1.":[263],"top":[266],"5,":[267],"0.3040":[271],"Accuracy@5,":[273,289],"0.2563":[274],"MRR@5,":[275,291],"0.2651":[277,293],"Recall@5":[278],"got":[287],"0.5270":[288],"0.2689":[290],"Recall@5.":[294]},"counts_by_year":[],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2022-05-22T00:00:00"}
