{"id":"https://openalex.org/W4319586187","doi":"https://doi.org/10.1109/dsaa54385.2022.10032424","title":"H4M: Heterogeneous, Multi-source, Multi-modal, Multi-view and Multi-distributional Dataset for Socioeconomic Analytics in the Case of Beijing","display_name":"H4M: Heterogeneous, Multi-source, Multi-modal, Multi-view and Multi-distributional Dataset for Socioeconomic Analytics in the Case of Beijing","publication_year":2022,"publication_date":"2022-10-13","ids":{"openalex":"https://openalex.org/W4319586187","doi":"https://doi.org/10.1109/dsaa54385.2022.10032424"},"language":"en","primary_location":{"id":"doi:10.1109/dsaa54385.2022.10032424","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/dsaa54385.2022.10032424","pdf_url":null,"source":{"id":"https://openalex.org/S4363608340","display_name":"2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5005262130","display_name":"Yaping Zhao","orcid":"https://orcid.org/0000-0002-3482-0942"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yaping Zhao","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021242955","display_name":"Shuhui Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shuhui Shi","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029130916","display_name":"Ramgopal Ravi","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ramgopal Ravi","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090042508","display_name":"Zhongrui Wang","orcid":"https://orcid.org/0000-0003-2264-0677"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhongrui Wang","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008832723","display_name":"Edmund Y. Lam","orcid":"https://orcid.org/0000-0001-6268-950X"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Edmund Y. Lam","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030090268","display_name":"Jichang Zhao","orcid":"https://orcid.org/0000-0002-5319-8060"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jichang Zhao","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.9991000294685364,"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"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.964900016784668,"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/beijing","display_name":"Beijing","score":0.84328693151474},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7363722324371338},{"id":"https://openalex.org/keywords/real-estate","display_name":"Real estate","score":0.7108125686645508},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5306063294410706},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5255421996116638},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.49514809250831604},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.4870041012763977},{"id":"https://openalex.org/keywords/socioeconomic-status","display_name":"Socioeconomic status","score":0.4717878997325897},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.43872296810150146},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39556825160980225},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.26180708408355713},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.2528950572013855},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19234800338745117},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.12848946452140808}],"concepts":[{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.84328693151474},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7363722324371338},{"id":"https://openalex.org/C82279013","wikidata":"https://www.wikidata.org/wiki/Q684740","display_name":"Real estate","level":2,"score":0.7108125686645508},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5306063294410706},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5255421996116638},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.49514809250831604},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.4870041012763977},{"id":"https://openalex.org/C147077947","wikidata":"https://www.wikidata.org/wiki/Q1515895","display_name":"Socioeconomic status","level":3,"score":0.4717878997325897},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.43872296810150146},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39556825160980225},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.26180708408355713},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.2528950572013855},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19234800338745117},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.12848946452140808},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"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/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsaa54385.2022.10032424","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/dsaa54385.2022.10032424","pdf_url":null,"source":{"id":"https://openalex.org/S4363608340","display_name":"2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1904380837","https://openalex.org/W1980398988","https://openalex.org/W1983883318","https://openalex.org/W2079040974","https://openalex.org/W2099352442","https://openalex.org/W2185914977","https://openalex.org/W2190432600","https://openalex.org/W2251575556","https://openalex.org/W2593831809","https://openalex.org/W2802726527","https://openalex.org/W2889230014","https://openalex.org/W3107381801","https://openalex.org/W4319586081","https://openalex.org/W4319586336","https://openalex.org/W6675295256"],"related_works":["https://openalex.org/W2015747722","https://openalex.org/W2362050182","https://openalex.org/W2382418233","https://openalex.org/W2369897927","https://openalex.org/W3031731056","https://openalex.org/W4293167957","https://openalex.org/W2361035307","https://openalex.org/W2380455807","https://openalex.org/W2993975634","https://openalex.org/W2367835030"],"abstract_inverted_index":{"The":[0,45,65,98],"study":[1],"of":[2,11,20,55,68],"socioeconomic":[3],"status":[4],"has":[5],"been":[6],"reformed":[7],"by":[8],"the":[9],"availability":[10],"digital":[12],"records":[13],"containing":[14],"data":[15,49],"on":[16,50],"real":[17,51,88],"estate,":[18,89],"points":[19,54],"interest,":[21,56],"traffic":[22,57],"and":[23,40,59,78,83],"social":[24,94],"media":[25],"trends":[26,61],"such":[27],"as":[28],"micro-blogging.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33],"describe":[34],"a":[35],"heterogeneous,":[36],"multi-source,":[37],"multi-modal,":[38],"multi-view":[39],"multi-distributional":[41],"dataset":[42,47,99],"named":[43],"\"H4M\".":[44],"mixed":[46],"contains":[48],"estate":[52],"transactions,":[53],"patterns":[58],"micro-blogging":[60],"from":[62],"Beijing,":[63],"China.":[64],"unique":[66],"composition":[67],"H4M":[69],"makes":[70],"it":[71],"an":[72],"ideal":[73],"test":[74],"bed":[75],"for":[76],"methodologies":[77],"approaches":[79],"aimed":[80],"at":[81],"studying":[82],"solving":[84],"problems":[85],"related":[86],"to":[87],"traffic,":[90],"urban":[91],"mobility":[92],"planning,":[93],"sentiment":[95],"analysis":[96],"etc.":[97],"is":[100],"available":[101],"at:":[102],"https://indigopurple.github.io/H4M/index.html.":[103]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}