{"id":"https://openalex.org/W3198750823","doi":"https://doi.org/10.18293/seke2021-125","title":"SADA: Improved Data Symbolization and Optimization Method on HAR from Microscopic Perspective","display_name":"SADA: Improved Data Symbolization and Optimization Method on HAR from Microscopic Perspective","publication_year":2021,"publication_date":"2021-07-08","ids":{"openalex":"https://openalex.org/W3198750823","doi":"https://doi.org/10.18293/seke2021-125","mag":"3198750823"},"language":"en","primary_location":{"id":"doi:10.18293/seke2021-125","is_oa":true,"landing_page_url":"http://doi.org/10.18293/seke2021-125","pdf_url":"https://doi.org/10.18293/seke2021-125","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://doi.org/10.18293/seke2021-125","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049240970","display_name":"Huichao Men","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Men Huichao","raw_affiliation_strings":["School of Computer Science and Engineering Northeastern University Shenyang, P.R.China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering Northeastern University Shenyang, P.R.China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5049240970"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11144627,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2021","issue":null,"first_page":"481","last_page":"486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9829999804496765,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"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/perspective","display_name":"Perspective (graphical)","score":0.783353328704834},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7211711406707764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7074570059776306},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.6424664258956909},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.619879424571991},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5625733733177185},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4446507394313812},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.424209326505661},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.19787293672561646},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.06750237941741943}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.783353328704834},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7211711406707764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7074570059776306},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6424664258956909},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.619879424571991},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5625733733177185},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4446507394313812},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.424209326505661},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.19787293672561646},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.06750237941741943}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18293/seke2021-125","is_oa":true,"landing_page_url":"http://doi.org/10.18293/seke2021-125","pdf_url":"https://doi.org/10.18293/seke2021-125","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18293/seke2021-125","is_oa":true,"landing_page_url":"http://doi.org/10.18293/seke2021-125","pdf_url":"https://doi.org/10.18293/seke2021-125","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6718270789","display_name":null,"funder_award_id":"N2104002","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3198750823.pdf","grobid_xml":"https://content.openalex.org/works/W3198750823.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W101498549","https://openalex.org/W2044262006","https://openalex.org/W2123504417","https://openalex.org/W2219995598","https://openalex.org/W2522090363","https://openalex.org/W2548335893","https://openalex.org/W2552024171","https://openalex.org/W2579067088","https://openalex.org/W2751662790","https://openalex.org/W2799789318","https://openalex.org/W2911489562","https://openalex.org/W2941789077","https://openalex.org/W2963643539","https://openalex.org/W2972660824","https://openalex.org/W2998216295","https://openalex.org/W3001960185","https://openalex.org/W3174602460","https://openalex.org/W4285719527","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2145836866","https://openalex.org/W2803255133"],"abstract_inverted_index":{"Nowadays,":[0],"human":[1],"activity":[2,111],"recognition(HAR)":[3],"becomes":[4],"a":[5,80,82,89],"hot":[6],"topic":[7],"with":[8,38,97],"broad":[9],"applications.":[10],"Some":[11],"researches":[12],"have":[13],"conducted":[14],"HAR":[15],"from":[16],"microscopic":[17],"perspective":[18],"and":[19,61,106,114,131],"achieved":[20],"good":[21],"results.":[22],"In":[23,73],"this":[24,71],"article,":[25],"two":[26],"methods":[27,102],"are":[28,103,124],"proposed":[29,43,54],"for":[30,44,66],"further":[31,56],"improvement.":[32],"Firstly,":[33],"an":[34,49],"improved":[35,50],"symbolization":[36],"method":[37],"stacked":[39],"sparse":[40],"autoencoder":[41],"is":[42,53,63],"better":[45],"data":[46],"symbolization.":[47],"Secondly,":[48],"multi-classification":[51],"Adaboost":[52],"to":[55,126],"optimize":[57],"the":[58,67,74,128],"recognition":[59],"effect,":[60],"it":[62],"more":[64],"suitable":[65],"application":[68],"scenario":[69],"of":[70],"article.":[72],"experiments":[75,96],"section,":[76],"firstly,":[77],"e":[78],"xperiments":[79],"nd":[81],"nalysis":[83],"about":[84],"various":[85],"influencing":[86],"p":[87],"arameters":[88],"re":[90],"c":[91],"onducted,":[92],"t":[93],"hen":[94],"comparison":[95],"several":[98],"new":[99],"or":[100],"representative":[101,109],"carried":[104],"out,":[105],"finally":[107],"five":[108],"sensor":[110],"datasets(UCI":[112],"Sports":[113],"Daily":[115],"dataset,":[116,119,121],"Wisdm":[117],"Phoneacc&Watchacc":[118],"Skoda":[120],"HAPT":[122],"dataset)":[123],"used":[125],"prove":[127],"universal":[129],"applicability":[130],"achieve":[132],"satisfactory":[133],"effect.":[134]},"counts_by_year":[],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
