{"id":"https://openalex.org/W2953199134","doi":"https://doi.org/10.1145/3292500.3330671","title":"PinText: A Multitask Text Embedding System in Pinterest","display_name":"PinText: A Multitask Text Embedding System in Pinterest","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2953199134","doi":"https://doi.org/10.1145/3292500.3330671","mag":"2953199134"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330671","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & 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/A5060548099","display_name":"Jinfeng Zhuang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jinfeng Zhuang","raw_affiliation_strings":["Pinterest, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Pinterest, Seattle, WA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101664633","display_name":"Yu Liu","orcid":"https://orcid.org/0000-0003-2281-6791"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu Liu","raw_affiliation_strings":["Pinterest, San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Pinterest, San Francisco, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060548099"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8401,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80008163,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2653","last_page":"2661"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10028","display_name":"Topic Modeling","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11644","display_name":"Spam and Phishing Detection","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/embedding","display_name":"Embedding","score":0.7928855419158936},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7420856356620789},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.6766703724861145},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.590686023235321},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5840876698493958},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5247994661331177},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.45760253071784973},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.456880658864975},{"id":"https://openalex.org/keywords/vector-space","display_name":"Vector space","score":0.4542541801929474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4418167173862457},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.42964833974838257},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.4206070303916931},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13154110312461853},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13144081830978394}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7928855419158936},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7420856356620789},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6766703724861145},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.590686023235321},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5840876698493958},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5247994661331177},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.45760253071784973},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.456880658864975},{"id":"https://openalex.org/C13336665","wikidata":"https://www.wikidata.org/wiki/Q125977","display_name":"Vector space","level":2,"score":0.4542541801929474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4418167173862457},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.42964833974838257},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.4206070303916931},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13154110312461853},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13144081830978394},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3292500.3330671","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330671","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4000000059604645,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1010415138","https://openalex.org/W1832693441","https://openalex.org/W1924770834","https://openalex.org/W1928278792","https://openalex.org/W2064675550","https://openalex.org/W2113552117","https://openalex.org/W2117130368","https://openalex.org/W2158139315","https://openalex.org/W2162006472","https://openalex.org/W2163605009","https://openalex.org/W2164019165","https://openalex.org/W2165698076","https://openalex.org/W2170973209","https://openalex.org/W2250539671","https://openalex.org/W2295072214","https://openalex.org/W2493916176","https://openalex.org/W2624871570","https://openalex.org/W2730640268","https://openalex.org/W2741609678","https://openalex.org/W2755957574","https://openalex.org/W2888329843","https://openalex.org/W2950577311","https://openalex.org/W2962739339","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963563735","https://openalex.org/W2964207259","https://openalex.org/W2964301648","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4221011941","https://openalex.org/W2596026555","https://openalex.org/W4254304201","https://openalex.org/W2798669739","https://openalex.org/W2592069528","https://openalex.org/W3155235018","https://openalex.org/W2991391395","https://openalex.org/W3204643324","https://openalex.org/W2921972128","https://openalex.org/W3083244731"],"abstract_inverted_index":{"Text":[0],"embedding":[1,36,45,58,79,124],"is":[2,21,105],"a":[3,55,82,111,127,129,132],"fundamental":[4],"component":[5],"for":[6,62],"extracting":[7],"text":[8,57,78],"features":[9],"in":[10,47,73],"production-level":[11],"data":[12],"mining":[13],"and":[14,38,42,71,85,171,180],"machine":[15],"learning":[16],"systems":[17],"given":[18],"textual":[19],"information":[20],"the":[22,30,99,108,118],"most":[23],"ubiqutious":[24],"signals.":[25],"However,":[26],"practitioners":[27],"often":[28],"face":[29],"tradeoff":[31],"between":[32,101,110],"effectiveness":[33,175],"of":[34,40,126,176,184],"underlying":[35],"algorithms":[37,80],"cost":[39,183],"training":[41],"maintaining":[43],"various":[44],"results":[46],"large-scale":[48],"applications.":[49],"In":[50,142],"this":[51,143,177],"paper,":[52],"we":[53,90,122,148],"propose":[54],"multitask":[56],"solution":[59,84],"called":[60],"PinText":[61,178],"three":[63],"major":[64],"vertical":[65],"surfaces":[66],"including":[67],"homefeed,":[68],"related":[69],"pins,":[70],"search":[72,133,156],"Pinterest,":[74],"which":[75],"consolidates":[76],"existing":[77],"into":[81],"single":[83],"produces":[86],"state-of-the-art":[87],"performance.":[88],"Specifically,":[89],"learn":[91],"word":[92,139],"level":[93,140],"semantic":[94,120],"vectors":[95],"by":[96,135,159],"enforcing":[97],"that":[98],"similarity":[100,109],"positive":[102],"engagement":[103],"pairs":[104],"larger":[106],"than":[107],"randomly":[112],"sampled":[113],"background":[114],"pairs.":[115],"Based":[116],"on":[117,165],"learned":[119],"vectors,":[121],"derive":[123],"vector":[125,146],"user,":[128],"pin,":[130],"or":[131,162],"query":[134],"simply":[136],"averaging":[137],"its":[138],"vectors.":[141],"common":[144],"compact":[145],"space,":[147],"are":[149],"able":[150],"to":[151],"do":[152],"unified":[153],"nearest":[154],"neighbor":[155],"with":[157],"hashing":[158],"Hadoop":[160],"jobs":[161],"dockerized":[163],"images":[164],"Kubernetes":[166],"cluster.":[167],"Both":[168],"offline":[169],"evaluation":[170],"online":[172],"experiments":[173],"show":[174],"system":[179],"save":[181],"storage":[182],"multiple":[185],"open-sourced":[186],"embeddings":[187],"significantly.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}