乐胖代购免代理版

{"id":"https://openalex.org/W2139095291","doi":"https://doi.org/10.1145/1963192.1963216","title":"A study on the impact of product images on user clicks for online shopping","display_name":"A study on the impact of product images on user clicks for online shopping","publication_year":2011,"publication_date":"2011-03-28","ids":{"openalex":"https://openalex.org/W2139095291","doi":"https://doi.org/10.1145/1963192.1963216","mag":"2139095291"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/1963192.1963216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5012908666","display_name":"Anjan Goswami","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150719","display_name":"eBay (United States)","ror":"https://ror.org/05cnabr44","country_code":"US","type":"company","lineage":["https://openalex.org/I4210150719"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anjan Goswami","raw_affiliation_strings":["eBay Inc., San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"eBay Inc., San Jose, CA, USA","institution_ids":["https://openalex.org/I4210150719"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058171061","display_name":"Naren Chittar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150719","display_name":"eBay (United States)","ror":"https://ror.org/05cnabr44","country_code":"US","type":"company","lineage":["https://openalex.org/I4210150719"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Naren Chittar","raw_affiliation_strings":["eBay Inc., San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"eBay Inc., San Jose, CA, USA","institution_ids":["https://openalex.org/I4210150719"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091646778","display_name":"Chung H. Sung","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150719","display_name":"eBay (United States)","ror":"https://ror.org/05cnabr44","country_code":"US","type":"company","lineage":["https://openalex.org/I4210150719"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chung H. Sung","raw_affiliation_strings":["eBay Inc., San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"eBay Inc., San Jose, CA, USA","institution_ids":["https://openalex.org/I4210150719"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.759,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":33,"citation_normalized_percentile":{"value":0.889091,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":92,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"45","last_page":"46"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9917,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9917,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9905,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9457,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting","score":0.6865634},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to Rank","score":0.5500433},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.48338738},{"id":"https://openalex.org/keywords/regression-function","display_name":"Regression function","score":0.46566227},{"id":"https://openalex.org/keywords/click-through-rate","display_name":"Click-through rate","score":0.42722145}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7426961},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6865634},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5917728},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5500433},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.53654814},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.51069194},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.50110865},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.49196026},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.48338738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48335263},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.4831333},{"id":"https://openalex.org/C2988035592","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression function","level":3,"score":0.46566227},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.45256713},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.43329686},{"id":"https://openalex.org/C115174607","wikidata":"https://www.wikidata.org/wiki/Q1100934","display_name":"Click-through rate","level":2,"score":0.42722145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3783577},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3361276},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17024353},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16332838},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.14334333},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/1963192.1963216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":5,"referenced_works":["https://openalex.org/W2066478430","https://openalex.org/W2070493638","https://openalex.org/W2134774992","https://openalex.org/W2245625259","https://openalex.org/W4321466059"],"related_works":["https://openalex.org/W4310492845","https://openalex.org/W4310224730","https://openalex.org/W4289703016","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W3094138326","https://openalex.org/W2967733078","https://openalex.org/W2885778889","https://openalex.org/W2885516856","https://openalex.org/W2766514146"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"study":[4],"the":[5,12,17,50,82],"importance":[6],"of":[7,19,43],"image":[8,45,83],"based":[9,32,46,57,65],"features":[10,33,72,84],"on":[11],"click-through":[13],"rate":[14],"(CTR)":[15],"in":[16,34,49,53],"context":[18],"a":[20,40,61],"large":[21],"scale":[22],"product":[23,27],"search":[24,28],"engine.":[25],"Typically":[26],"engines":[29],"use":[30],"text":[31,56],"their":[35],"ranking":[36],"function.":[37],"We":[38,59,87],"present":[39],"novel":[41],"idea":[42],"using":[44],"features,":[47],"common":[48],"photography":[51],"literature,":[52],"addition":[54],"to":[55,68,91],"features.":[58],"used":[60],"stochastic":[62],"gradient":[63],"boosting":[64],"regression":[66],"model":[67],"learn":[69],"relationships":[70],"between":[71,81],"and":[73,85,93],"CTR.":[74,86],"Our":[75],"results":[76],"indicate":[77],"statistically":[78],"significant":[79],"correlations":[80],"also":[88],"see":[89],"improvements":[90],"NDCG":[92],"mean":[94],"standard":[95],"regression.":[96]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2139095291","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":5},{"year":2014,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2025-02-17T06:35:49.248660","created_date":"2016-06-24"}