{"id":"https://openalex.org/W3187874255","doi":"https://doi.org/10.3233/jifs-211044","title":"Predicting mental disorder from noisy questionnaires: an anomaly detection approach based on keyword extraction and machine learning techniques","display_name":"Predicting mental disorder from noisy questionnaires: an anomaly detection approach based on keyword extraction and machine learning techniques","publication_year":2021,"publication_date":"2021-08-10","ids":{"openalex":"https://openalex.org/W3187874255","doi":"https://doi.org/10.3233/jifs-211044","mag":"3187874255"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-211044","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-211044","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","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/A5100763993","display_name":"Qing Zhou","orcid":"https://orcid.org/0000-0001-7712-6910"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qing Zhou","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060711016","display_name":"Xi Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Shi","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101828949","display_name":"Liang Ge","orcid":"https://orcid.org/0000-0001-6438-2341"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Ge","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100763993"],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":0.4079,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.68397046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"41","issue":"6","first_page":"7167","last_page":"7179"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9991000294685364,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9991000294685364,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9817000031471252,"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":0.745278537273407},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.710981547832489},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5914296507835388},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5779469609260559},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5751394629478455},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4547436237335205},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.380199670791626},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33073145151138306},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17217713594436646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10527849197387695}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.745278537273407},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.710981547832489},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5914296507835388},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5779469609260559},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5751394629478455},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4547436237335205},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.380199670791626},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33073145151138306},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17217713594436646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10527849197387695},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-211044","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-211044","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8500000238418579,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1560729591","https://openalex.org/W1795847264","https://openalex.org/W1860833772","https://openalex.org/W1965366178","https://openalex.org/W2035246458","https://openalex.org/W2054352680","https://openalex.org/W2058089741","https://openalex.org/W2061141931","https://openalex.org/W2061655859","https://openalex.org/W2067495470","https://openalex.org/W2092862146","https://openalex.org/W2101234009","https://openalex.org/W2119555207","https://openalex.org/W2122646361","https://openalex.org/W2145766604","https://openalex.org/W2147800946","https://openalex.org/W2483261836","https://openalex.org/W2770009055","https://openalex.org/W2802372426","https://openalex.org/W2894912426","https://openalex.org/W2912277723","https://openalex.org/W2985875790","https://openalex.org/W3011821664","https://openalex.org/W3092408845","https://openalex.org/W3093387841","https://openalex.org/W4239510810","https://openalex.org/W4243663932","https://openalex.org/W6633724138","https://openalex.org/W6675354045","https://openalex.org/W6745893125","https://openalex.org/W6755370398"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4300558037","https://openalex.org/W4377864969","https://openalex.org/W3030345572"],"abstract_inverted_index":{"The":[0,17],"early":[1],"warning":[2],"of":[3,7,14,19,88,100,107],"mental":[4,30],"disorders":[5],"is":[6,25,44],"great":[8],"importance":[9],"for":[10,85,97],"the":[11,33,39,42,86,98,105],"psychological":[12],"well-being":[13],"college":[15],"students.":[16],"accuracy":[18],"conventional":[20],"scaling":[21],"methods":[22],"on":[23,41,57],"questionnaires":[24,34,43],"generally":[26],"low":[27],"in":[28],"predicting":[29],"disorders,":[31],"as":[32,63],"contain":[35],"much":[36],"noise,":[37],"and":[38,66,70,91],"processing":[40],"rudimentary.":[45],"To":[46],"address":[47],"this":[48],"problem,":[49],"we":[50],"propose":[51,80],"a":[52,64,81],"novel":[53],"anomaly":[54],"detection":[55],"framework":[56],"questionnaires,":[58],"which":[59],"represents":[60],"each":[61],"questionnaire":[62],"document,":[65],"applies":[67],"keyword":[68,83],"extraction":[69],"machine":[71,94],"learning":[72,95],"techniques":[73],"to":[74],"detect":[75],"abnormal":[76],"questionnaires.":[77],"We":[78],"also":[79],"new":[82],"statistic":[84],"calculation":[87,99],"option":[89],"significance":[90],"three":[92],"interpretable":[93],"models":[96],"question":[101],"significance.":[102],"Experiments":[103],"demonstrate":[104],"effectiveness":[106],"our":[108],"proposed":[109],"methods.":[110]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
