{"id":"https://openalex.org/W2992316928","doi":"https://doi.org/10.1145/3368567.3368568","title":"Exploring the Ideal Depth of Neural Network when Predicting Question Deletion on Community Question Answering","display_name":"Exploring the Ideal Depth of Neural Network when Predicting Question Deletion on Community Question Answering","publication_year":2019,"publication_date":"2019-12-12","ids":{"openalex":"https://openalex.org/W2992316928","doi":"https://doi.org/10.1145/3368567.3368568","mag":"2992316928"},"language":"en","primary_location":{"id":"doi:10.1145/3368567.3368568","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3368567.3368568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th Forum for Information Retrieval Evaluation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1912.03585","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050277461","display_name":"Souvick Ghosh","orcid":"https://orcid.org/0000-0003-1610-9038"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]},{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Souvick Ghosh","raw_affiliation_strings":["Jadavpur University, Kolkata, WB, India","SC&amp;I, Rutgers University, New Brunswick, NJ, USA","Rutgers University *"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jadavpur University, Kolkata, WB, India","institution_ids":["https://openalex.org/I170979836"]},{"raw_affiliation_string":"SC&amp;I, Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"Rutgers University *","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045090722","display_name":"Satanu Ghosh","orcid":"https://orcid.org/0000-0003-4232-9931"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]},{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Satanu Ghosh","raw_affiliation_strings":["Jadavpur University, Kolkata, WB, India","SC&amp;I, Rutgers University, New Brunswick, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jadavpur University, Kolkata, WB, India","institution_ids":["https://openalex.org/I170979836"]},{"raw_affiliation_string":"SC&amp;I, Rutgers University, New Brunswick, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2207,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51505004,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"52","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.9998999834060669,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9990000128746033,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.958899974822998,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.8795986771583557},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7600956559181213},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7004229426383972},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6623689532279968},{"id":"https://openalex.org/keywords/ideal","display_name":"Ideal (ethics)","score":0.5960910320281982},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5789015889167786},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5767307877540588},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.48746275901794434},{"id":"https://openalex.org/keywords/situated","display_name":"Situated","score":0.4784948229789734},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4587628245353699},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4211249351501465},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3759780824184418},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0705600380897522}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.8795986771583557},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7600956559181213},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7004229426383972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6623689532279968},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.5960910320281982},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5789015889167786},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5767307877540588},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.48746275901794434},{"id":"https://openalex.org/C132829578","wikidata":"https://www.wikidata.org/wiki/Q581151","display_name":"Situated","level":2,"score":0.4784948229789734},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4587628245353699},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4211249351501465},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3759780824184418},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0705600380897522},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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":4,"locations":[{"id":"doi:10.1145/3368567.3368568","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3368567.3368568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th Forum for Information Retrieval Evaluation","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1912.03585","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.03585","pdf_url":"https://arxiv.org/pdf/1912.03585","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"},{"id":"mag:2992316928","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1912.03585v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1912.03585","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1912.03585","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1912.03585","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.03585","pdf_url":"https://arxiv.org/pdf/1912.03585","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.8700000047683716,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2992316928.pdf","grobid_xml":"https://content.openalex.org/works/W2992316928.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1594098193","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1690739335","https://openalex.org/W1730818938","https://openalex.org/W1969340322","https://openalex.org/W1974311367","https://openalex.org/W1987068266","https://openalex.org/W2003570745","https://openalex.org/W2036226015","https://openalex.org/W2037858832","https://openalex.org/W2075196988","https://openalex.org/W2086530517","https://openalex.org/W2089947415","https://openalex.org/W2100495367","https://openalex.org/W2104593788","https://openalex.org/W2116875384","https://openalex.org/W2129251351","https://openalex.org/W2134797427","https://openalex.org/W2153579005","https://openalex.org/W2159133636","https://openalex.org/W2281746805","https://openalex.org/W2286400365","https://openalex.org/W2292929658","https://openalex.org/W2401231614","https://openalex.org/W2407712691","https://openalex.org/W2594497365","https://openalex.org/W2950577311","https://openalex.org/W2950621961","https://openalex.org/W2951603627","https://openalex.org/W4312801880"],"related_works":["https://openalex.org/W2759281352","https://openalex.org/W2963897632","https://openalex.org/W3104846002","https://openalex.org/W2997733093","https://openalex.org/W76722536","https://openalex.org/W2945798043","https://openalex.org/W3103101828","https://openalex.org/W2950112473","https://openalex.org/W3093770962","https://openalex.org/W2558580397","https://openalex.org/W3127967581","https://openalex.org/W2921105605","https://openalex.org/W2739349903","https://openalex.org/W2735240643","https://openalex.org/W13680522","https://openalex.org/W2976395159","https://openalex.org/W3133671113","https://openalex.org/W3092238785","https://openalex.org/W3189711158","https://openalex.org/W3207199967"],"abstract_inverted_index":{"In":[0,38],"recent":[1],"years,":[2],"Community":[3],"Question":[4],"Answering":[5],"(CQA)":[6],"has":[7],"emerged":[8],"as":[9],"a":[10,184],"popular":[11],"platform":[12],"for":[13,70,197,220],"knowledge":[14],"curation":[15],"and":[16,35,67,72,82,150,180,194,222],"archival.":[17],"An":[18],"interesting":[19],"aspect":[20],"of":[21,47,54,56,78,116,130,139,161,176],"question":[22,199],"answering":[23],"is":[24,156,171],"that":[25,88,113],"it":[26],"combines":[27],"aspects":[28],"from":[29],"natural":[30],"language":[31],"processing,":[32],"information":[33,178],"retrieval,":[34],"machine":[36],"learning.":[37],"this":[39],"paper,":[40],"we":[41],"have":[42,63],"explored":[43],"how":[44,187],"the":[45,48,52,74,103,114,117,137,140,147,162,167,174],"depth":[46,104,138],"neural":[49,119,177,189],"network":[50,120],"influences":[51],"accuracy":[53,143,148,209],"prediction":[55,71],"deleted":[57,203],"questions":[58,204],"in":[59,97,159,173],"question-answering":[60],"forums.":[61],"We":[62,111,201],"used":[64,196],"different":[65],"shallow":[66,95],"deep":[68,90,118,188],"models":[69],"analyzed":[73],"relationships":[75],"between":[76],"number":[77,129],"hidden":[79,131,214],"layers,":[80,215],"accuracy,":[81],"computational":[83],"time.":[84],"The":[85],"results":[86,219],"suggest":[87],"while":[89],"networks":[91,96,190],"perform":[92],"better":[93],"than":[94,207],"modeling":[98],"complex":[99],"non-linear":[100],"functions,":[101],"increasing":[102,136],"may":[105],"not":[106],"always":[107],"produce":[108],"desired":[109],"results.":[110],"observe":[112],"performance":[115],"suffers":[121],"significantly":[122],"due":[123],"to":[124,165,212],"vanishing":[125],"gradients":[126],"when":[127],"large":[128],"layers":[132],"are":[133],"present.":[134],"Constantly":[135],"model":[141],"increases":[142],"initially,":[144],"after":[145],"which":[146],"plateaus,":[149],"finally":[151],"drops.":[152],"Adding":[153],"each":[154],"layer":[155],"also":[157],"expensive":[158],"terms":[160],"time":[163],"required":[164],"train":[166],"model.":[168],"This":[169],"research":[170],"situated":[172],"domain":[175],"retrieval":[179],"contributes":[181],"towards":[182],"building":[183],"theory":[185],"on":[186],"can":[191],"be":[192],"efficiently":[193],"accurately":[195],"predicting":[198],"deletion.":[200],"predict":[202],"with":[205,216],"more":[206],"90%":[208],"using":[210],"two":[211],"ten":[213],"less":[217],"accurate":[218],"shallower":[221],"deeper":[223],"architectures.":[224]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}
