{"id":"https://openalex.org/W4388455852","doi":"https://doi.org/10.1145/3631937","title":"Improving First-stage Retrieval of Point-of-interest Search by Pre-training Models","display_name":"Improving First-stage Retrieval of Point-of-interest Search by Pre-training Models","publication_year":2023,"publication_date":"2023-11-07","ids":{"openalex":"https://openalex.org/W4388455852","doi":"https://doi.org/10.1145/3631937"},"language":"en","primary_location":{"id":"doi:10.1145/3631937","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3631937","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3631937","source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3631937","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102857942","display_name":"Lang Mei","orcid":"https://orcid.org/0000-0002-7960-3036"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lang Mei","raw_affiliation_strings":["Beijing Key Laboratory of Big Data Management and Analysis Methods, Gaoling School of Artificial Intelligence, Renmin University of China, China"],"raw_orcid":"https://orcid.org/0000-0002-7960-3036","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Big Data Management and Analysis Methods, Gaoling School of Artificial Intelligence, Renmin University of China, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072119199","display_name":"Jiaxin Mao","orcid":"https://orcid.org/0000-0002-9257-5498"},"institutions":[{"id":"https://openalex.org/I4401726870","display_name":"Didi Chuxing (China)","ror":"https://ror.org/02ksqcf75","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726870"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxin Mao","raw_affiliation_strings":["Didi Chuxing, China"],"raw_orcid":"https://orcid.org/0000-0002-9257-5498","affiliations":[{"raw_affiliation_string":"Didi Chuxing, China","institution_ids":["https://openalex.org/I4401726870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074670791","display_name":"Juan Hu","orcid":"https://orcid.org/0009-0007-2886-3966"},"institutions":[{"id":"https://openalex.org/I4401726870","display_name":"Didi Chuxing (China)","ror":"https://ror.org/02ksqcf75","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726870"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juan Hu","raw_affiliation_strings":["Didi Chuxing, China"],"raw_orcid":"https://orcid.org/0009-0007-2886-3966","affiliations":[{"raw_affiliation_string":"Didi Chuxing, China","institution_ids":["https://openalex.org/I4401726870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020921636","display_name":"Naiqiang Tan","orcid":"https://orcid.org/0009-0008-4687-5212"},"institutions":[{"id":"https://openalex.org/I4401726870","display_name":"Didi Chuxing (China)","ror":"https://ror.org/02ksqcf75","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726870"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Naiqiang Tan","raw_affiliation_strings":["Didi Chuxing, China"],"raw_orcid":"https://orcid.org/0009-0008-4687-5212","affiliations":[{"raw_affiliation_string":"Didi Chuxing, China","institution_ids":["https://openalex.org/I4401726870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101684383","display_name":"Hua Chai","orcid":"https://orcid.org/0000-0002-8351-1935"},"institutions":[{"id":"https://openalex.org/I4401726870","display_name":"Didi Chuxing (China)","ror":"https://ror.org/02ksqcf75","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726870"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Chai","raw_affiliation_strings":["Didi Chuxing, China"],"raw_orcid":"https://orcid.org/0000-0002-8351-1935","affiliations":[{"raw_affiliation_string":"Didi Chuxing, China","institution_ids":["https://openalex.org/I4401726870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025631695","display_name":"Ji-Rong Wen","orcid":"https://orcid.org/0000-0002-9777-9676"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji-Rong Wen","raw_affiliation_strings":["Beijing Key Laboratory of Big Data Management and Analysis Methods, Gaoling School of Artificial Intelligence, Renmin University of China, China"],"raw_orcid":"https://orcid.org/0000-0002-9777-9676","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Big Data Management and Analysis Methods, Gaoling School of Artificial Intelligence, Renmin University of China, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6782,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.66890709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"42","issue":"3","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9962999820709229,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9962999820709229,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9944000244140625,"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/T10757","display_name":"Geographic Information Systems Studies","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"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/computer-science","display_name":"Computer science","score":0.839580774307251},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6636273860931396},{"id":"https://openalex.org/keywords/point-of-interest","display_name":"Point of interest","score":0.6598348617553711},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.562003493309021},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5514397621154785},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.4557002782821655},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.44660574197769165},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4454880952835083},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.4267074465751648},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4137394428253174},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28695714473724365}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.839580774307251},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6636273860931396},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.6598348617553711},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.562003493309021},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5514397621154785},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.4557002782821655},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.44660574197769165},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4454880952835083},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.4267074465751648},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4137394428253174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28695714473724365},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C136264566","wikidata":"https://www.wikidata.org/wiki/Q159810","display_name":"Economy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3631937","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3631937","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3631937","source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3631937","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3631937","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3631937","source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G3842386738","display_name":null,"funder_award_id":"BJJWZYJH012019100020098","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G559290415","display_name":null,"funder_award_id":"61902209, U2001212","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6096155391","display_name":null,"funder_award_id":"BJJWZYJH012019100020098","funder_id":"https://openalex.org/F4320322499","funder_display_name":"Renmin University of China"},{"id":"https://openalex.org/G6686603084","display_name":null,"funder_award_id":"U2001212","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322499","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92"},{"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/W4388455852.pdf","grobid_xml":"https://content.openalex.org/works/W4388455852.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W1722903425","https://openalex.org/W2055981215","https://openalex.org/W2111006384","https://openalex.org/W2124509324","https://openalex.org/W2136189984","https://openalex.org/W2186845332","https://openalex.org/W2187089797","https://openalex.org/W2206373005","https://openalex.org/W2798812533","https://openalex.org/W2896457183","https://openalex.org/W2905463021","https://openalex.org/W2945127593","https://openalex.org/W2962739339","https://openalex.org/W2998702515","https://openalex.org/W3011574394","https://openalex.org/W3012871709","https://openalex.org/W3015883388","https://openalex.org/W3021244424","https://openalex.org/W3021397474","https://openalex.org/W3034326350","https://openalex.org/W3036320503","https://openalex.org/W3038098779","https://openalex.org/W3038572442","https://openalex.org/W3080720646","https://openalex.org/W3088409176","https://openalex.org/W3091814605","https://openalex.org/W3092683697","https://openalex.org/W3093570284","https://openalex.org/W3098468692","https://openalex.org/W3099446234","https://openalex.org/W3101118213","https://openalex.org/W3103981637","https://openalex.org/W3105817677","https://openalex.org/W3115195983","https://openalex.org/W3118668786","https://openalex.org/W3119866685","https://openalex.org/W3145630588","https://openalex.org/W3152562554","https://openalex.org/W3155895380","https://openalex.org/W3168875417","https://openalex.org/W3170553237","https://openalex.org/W3188983256","https://openalex.org/W3194466018","https://openalex.org/W3217305727","https://openalex.org/W4224325265","https://openalex.org/W4224865658","https://openalex.org/W4226244192","https://openalex.org/W4251326898","https://openalex.org/W4284691245","https://openalex.org/W4284702754","https://openalex.org/W4285079552","https://openalex.org/W4287391717","https://openalex.org/W4287816019","https://openalex.org/W4292358656","https://openalex.org/W4297733535","https://openalex.org/W4300427681","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6758015726"],"related_works":["https://openalex.org/W2560191017","https://openalex.org/W3037187668","https://openalex.org/W2012531322","https://openalex.org/W2402761219","https://openalex.org/W2348892528","https://openalex.org/W2014728371","https://openalex.org/W3194422352","https://openalex.org/W3117467770","https://openalex.org/W2785900585","https://openalex.org/W2353730437"],"abstract_inverted_index":{"Point-of-interest":[0],"(POI)":[1],"search":[2,19,116,198],"is":[3,20],"important":[4],"for":[5,114],"location-based":[6],"services,":[7],"such":[8],"as":[9],"navigation":[10],"and":[11,40,61,99,135,150,170,186,212,232],"online":[12,196],"ride-hailing":[13],"service.":[14],"The":[15],"goal":[16],"of":[17,42,56,79,88,129,180],"POI":[18,30,43,81,91,115,154,182,197,265],"to":[21,117,140,183,224],"find":[22],"the":[23,38,74,80,86,96,101,119,123,127,143,147,153,178,189,213,226,230,244,249,254],"most":[24,45],"relevant":[25],"destinations":[26],"from":[27,194,248],"a":[28,33,51,109,137,159,165,220],"large-scale":[29],"database":[31],"given":[32],"text":[34,231],"query.":[35],"To":[36],"improve":[37],"effectiveness":[39],"efficiency":[41],"search,":[44],"existing":[46,89,263],"approaches":[47],"are":[48],"based":[49,163,206],"on":[50,73,164,207,243],"multi-stage":[52],"pipeline":[53],"that":[54,176,253],"consists":[55],"an":[57,195,237],"efficiency-oriented":[58,76],"retrieval":[59,77,92,260,266],"stage":[60,78],"one":[62],"or":[63],"more":[64],"effectiveness-oriented":[65],"re-rank":[66],"stages.":[67],"In":[68],"this":[69],"article,":[70],"we":[71,107,156,200],"focus":[72],"first":[75,84,157],"search.":[82],"We":[83,217],"identify":[85],"limitations":[87],"first-stage":[90,264],"models":[93,132],"in":[94],"capturing":[95],"semantic-geography":[97],"relationship":[98],"modeling":[100],"fine-grained":[102,227],"geographical":[103,233],"context":[104,234],"information.":[105],"Then,":[106],"propose":[108],"Geo-Enhanced":[110],"Dense":[111],"Retrieval":[112],"framework":[113,125,256],"alleviate":[118],"above":[120],"problems.":[121],"Specifically,":[122],"proposed":[124,255],"leverages":[126],"capacity":[128],"pre-trained":[130],"language":[131,168],"(e.g.,":[133],"BERT)":[134],"designs":[136],"pre-training":[138,161,174,204],"approach":[139],"better":[141],"model":[142,225],"semantic":[144],"match":[145],"between":[146,215,229],"query":[148,209,239],"prefix":[149],"POIs.":[151,216],"With":[152,188],"collection,":[155],"perform":[158],"token-level":[160],"task":[162],"geographical-sensitive":[166],"masked":[167],"prediction":[169],"design":[171,201],"two":[172,202],"retrieval-oriented":[173],"tasks":[175,205],"link":[177],"address":[179],"each":[181],"its":[184],"name":[185],"geo-location.":[187],"user":[190],"behavior":[191,211],"logs":[192],"collected":[193,247],"system,":[199],"additional":[203],"users\u2019":[208],"reformulation":[210],"transitions":[214],"also":[218],"utilize":[219],"late-interaction":[221],"network":[222],"structure":[223],"interactions":[228],"information":[235],"within":[236],"acceptable":[238],"latency.":[240],"Extensive":[241],"experiments":[242],"real-world":[245],"datasets":[246],"Didichuxing":[250],"application":[251],"demonstrate":[252],"can":[257],"achieve":[258],"superior":[259],"performance":[261],"over":[262],"methods.":[267]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
