{"id":"https://openalex.org/W2508432084","doi":"https://doi.org/10.1145/2939672.2939686","title":"Days on Market","display_name":"Days on Market","publication_year":2016,"publication_date":"2016-08-08","ids":{"openalex":"https://openalex.org/W2508432084","doi":"https://doi.org/10.1145/2939672.2939686","mag":"2508432084"},"language":"en","primary_location":{"id":"doi:10.1145/2939672.2939686","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939686","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-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/A5049015446","display_name":"Hengshu Zhu","orcid":"https://orcid.org/0000-0003-4570-643X"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hengshu Zhu","raw_affiliation_strings":["Baidu Research-Big Data Lab, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Baidu Research-Big Data Lab, Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101862104","display_name":"Hui Xiong","orcid":"https://orcid.org/0000-0001-6016-6465"},"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"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Xiong","raw_affiliation_strings":["Rutgers University, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University, Newark, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013159056","display_name":"Fangshuang Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangshuang Tang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029820058","display_name":"Qi Liu","orcid":"https://orcid.org/0000-0001-8847-7417"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Liu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101744165","display_name":"Yong Ge","orcid":"https://orcid.org/0000-0001-8094-4180"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Ge","raw_affiliation_strings":["University of Arizona, Tucson, USA"],"affiliations":[{"raw_affiliation_string":"University of Arizona, Tucson, USA","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048237545","display_name":"Enhong Chen","orcid":"https://orcid.org/0000-0002-4835-4102"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enhong Chen","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032187620","display_name":"Yanjie Fu","orcid":"https://orcid.org/0000-0002-1767-8024"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanjie Fu","raw_affiliation_strings":["Missouri University of Science and Technology, Rolla, USA"],"affiliations":[{"raw_affiliation_string":"Missouri University of Science and Technology, Rolla, USA","institution_ids":["https://openalex.org/I20382870"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5049015446"],"corresponding_institution_ids":["https://openalex.org/I98301712"],"apc_list":null,"apc_paid":null,"fwci":18.4792,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.98907472,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"393","last_page":"402"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10632","display_name":"Housing Market and Economics","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10632","display_name":"Housing Market and Economics","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9907000064849854,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9750999808311462,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/real-estate","display_name":"Real estate","score":0.8994778990745544},{"id":"https://openalex.org/keywords/market-liquidity","display_name":"Market liquidity","score":0.6784719824790955},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.49046775698661804},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4882628917694092},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4766426980495453},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.45488786697387695},{"id":"https://openalex.org/keywords/listing","display_name":"Listing (finance)","score":0.45362818241119385},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.42025870084762573},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.41966724395751953},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.28004592657089233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2749234437942505},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1138700544834137}],"concepts":[{"id":"https://openalex.org/C82279013","wikidata":"https://www.wikidata.org/wiki/Q684740","display_name":"Real estate","level":2,"score":0.8994778990745544},{"id":"https://openalex.org/C183582576","wikidata":"https://www.wikidata.org/wiki/Q184783","display_name":"Market liquidity","level":2,"score":0.6784719824790955},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.49046775698661804},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4882628917694092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4766426980495453},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.45488786697387695},{"id":"https://openalex.org/C2779820595","wikidata":"https://www.wikidata.org/wiki/Q798505","display_name":"Listing (finance)","level":2,"score":0.45362818241119385},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.42025870084762573},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.41966724395751953},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.28004592657089233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2749234437942505},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1138700544834137},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2939672.2939686","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939686","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1497745584","https://openalex.org/W1527986077","https://openalex.org/W1599871777","https://openalex.org/W1871180460","https://openalex.org/W1973749534","https://openalex.org/W1989060270","https://openalex.org/W1992323181","https://openalex.org/W1996824651","https://openalex.org/W1997446671","https://openalex.org/W1998805852","https://openalex.org/W2004355295","https://openalex.org/W2009833034","https://openalex.org/W2018096278","https://openalex.org/W2031250362","https://openalex.org/W2047851078","https://openalex.org/W2065180801","https://openalex.org/W2066049967","https://openalex.org/W2074693857","https://openalex.org/W2095814328","https://openalex.org/W2126288184","https://openalex.org/W2133491790","https://openalex.org/W2143104527","https://openalex.org/W2159514083","https://openalex.org/W2165644552","https://openalex.org/W2401606901","https://openalex.org/W2913340405","https://openalex.org/W2949664970","https://openalex.org/W3101782091","https://openalex.org/W3209042722","https://openalex.org/W4231250306"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2015747722","https://openalex.org/W2368049389","https://openalex.org/W2170801710","https://openalex.org/W2384861574","https://openalex.org/W2952704802","https://openalex.org/W4294565801","https://openalex.org/W2142306706"],"abstract_inverted_index":{"Days":[0],"on":[1,13,91,157,195],"Market":[2],"(DOM)":[3],"refers":[4],"to":[5,52,78,105,122],"the":[6,14,31,54,60,92,124,170,216,219],"number":[7],"of":[8,22,41,56,68,86,94,126,140,152,172,218],"days":[9],"a":[10,38,46,57,84,95,115,127,162,205],"property":[11,129,184],"is":[12,18,35,64,75,121],"active":[15],"market,":[16],"which":[17,88],"an":[19,65],"important":[20,66],"measurement":[21],"market":[23,71],"liquidity":[24,109,224],"in":[25,100,114,201,225],"real":[26,69,107,142,173,197,226],"estate":[27,70,108,198,227],"industry.":[28],"Indeed,":[29],"at":[30],"micro":[32],"level,":[33,62],"DOM":[34,63,93,125,171],"not":[36],"only":[37],"special":[39,119],"concern":[40],"house":[42,147],"sellers,":[43],"but":[44],"also":[45],"useful":[47],"indicator":[48,67],"for":[49,168,182,208,222],"potential":[50],"buyers":[51],"evaluate":[53],"popularity":[55],"house.":[58],"At":[59],"macro":[61],"status.":[72],"However,":[73],"it":[74],"very":[76],"challenging":[77],"measure":[79,106],"DOM,":[80],"since":[81],"there":[82],"are":[83],"variety":[85],"factors":[87,113],"can":[89,177],"impact":[90],"property.":[96],"To":[97],"this":[98,101],"end,":[99],"paper,":[102],"we":[103,132,160,191],"aim":[104],"by":[110,186],"examining":[111],"multiple":[112,138,188],"holistic":[116],"manner.":[117],"A":[118],"goal":[120],"predict":[123],"given":[128],"listing.":[130],"Specifically,":[131],"first":[133],"extract":[134],"key":[135],"features":[136],"from":[137],"types":[139],"heterogeneous":[141],"estate-related":[143],"data,":[144],"such":[145],"as":[146],"profiles":[148],"and":[149,203],"geo-social":[150],"information":[151],"residential":[153],"communities.":[154],"Then,":[155],"based":[156,165],"these":[158],"features,":[159],"develop":[161,204],"multi-task":[163],"learning":[164],"regression":[166],"approach":[167,176,221],"predicting":[169],"estates.":[174],"This":[175],"effectively":[178],"learn":[179],"district-aware":[180],"models":[181],"different":[183],"listings":[185],"considering":[187],"factors.":[189],"Finally,":[190],"conduct":[192],"extensive":[193],"experiments":[194],"real-world":[196],"data":[199],"collected":[200],"Beijing":[202],"prototype":[206],"system":[207],"practical":[209],"use.":[210],"The":[211],"experimental":[212],"results":[213],"clearly":[214],"validate":[215],"effectiveness":[217],"proposed":[220],"measuring":[223],"markets.":[228]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-09-16T00:00:00"}
