{"id":33865,"date":"2019-10-31T21:55:06","date_gmt":"2019-10-31T18:55:06","guid":{"rendered":"https:\/\/prohoster.info\/blog\/microsoft-otkryl-kod-biblioteki-vektornogo-poiska-ispolzuemoj-v-bing\/"},"modified":"2019-10-31T21:55:06","modified_gmt":"2019-10-31T18:55:06","slug":"microsoft-otkryl-kod-biblioteki-vektornogo-poiska-ispolzuemoj-v-bing","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sv\/blog\/news\/microsoft-otkryl-kod-biblioteki-vektornogo-poiska-ispolzuemoj-v-bing","title":{"rendered":"Microsoft har \u00f6ppnat koden f\u00f6r biblioteket f\u00f6r vektors\u00f6kning som anv\u00e4nds i Bing","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Microsoft F\u00f6retaget publicerade<\/a><\/noindex> ursprungstexter fr\u00e5n maskininl\u00e4rningsbiblioteket SPTAG<\/a><\/noindex> (Space Partition Tree And Graph) med implementation av algoritmen f\u00f6r approximativ n\u00e4rmaste granne<\/a><\/noindex>. Biblioteket har utvecklats<\/a><\/noindex> i forskningsdivisionen Microsoft Research och utvecklingscentret f\u00f6r s\u00f6kteknologier (Microsoft Search Technology Center). I praktiken anv\u00e4nds SPTAG i s\u00f6kmotorn Bing f\u00f6r att best\u00e4mma de mest relevanta resultaten med h\u00e4nsyn till kontexten av s\u00f6kfr\u00e5gor. Koden \u00e4r skriven i C++ och sprids<\/a><\/noindex> under MIT-licens. St\u00f6d f\u00f6r byggnation f\u00f6r Linux och Windows finns. Det finns en bindning f\u00f6r Python.<\/p>\n

Trots att id\u00e9erna om att anv\u00e4nda vektorlager i s\u00f6kmotorer har funnits l\u00e4nge, hindras implementeringen i praktiken av den stora resursf\u00f6rbrukningen vid vektoroperationer och begr\u00e4nsningar i skalbarheten. Kombinationen av metoder f\u00f6r djupinl\u00e4rning med algoritmer f\u00f6r approximativ n\u00e4rmaste granne har gjort det m\u00f6jligt att n\u00e5 acceptabel prestanda och skalbarhet f\u00f6r vektorsystem i stora s\u00f6kmotorer. Till exempel, i Bing f\u00f6r ett vektorindex med mer \u00e4n 150 miljarder vektorer tar det mindre \u00e4n 8 ms att h\u00e4mta de mest relevanta resultaten.<\/p>\n

Biblioteket inkluderar verktyg f\u00f6r att bygga index och organisera vektorers s\u00f6kning, samt en upps\u00e4ttning verktyg f\u00f6r att st\u00f6dja ett distribuerat system f\u00f6r online-s\u00f6kning som omfattar mycket stora samlingar av vektorer. F\u00f6ljande moduler erbjuds:<\/a><\/noindex> index builder f\u00f6r indexering, searcher f\u00f6r s\u00f6kning med hj\u00e4lp av indexet distribuerat i en kluster av flera noder, server f\u00f6r att k\u00f6ra processorer p\u00e5 noder, Aggregator f\u00f6r att sammanfoga flera servrar till en enhet och klient f\u00f6r att skicka f\u00f6rfr\u00e5gningar. St\u00f6d finns f\u00f6r att inkludera nya vektorer i indexet och ta bort vektorer i realtid.<\/p>\n

Biblioteket f\u00f6ruts\u00e4tter att de bearbetade och presenterade data i samlingen \u00e4r utformade som relaterade vektorer som kan j\u00e4mf\u00f6ras baserat p\u00e5 euclidean<\/a><\/noindex> (L2) eller cosinus<\/a><\/noindex> avst\u00e5nd. Vid en s\u00f6kfr\u00e5ga returneras vektorer vars avst\u00e5nd till den ursprungliga vektorn \u00e4r minimalt. I SPTAG tillhandah\u00e5lls tv\u00e5 metoder f\u00f6r organisering av vektorutrymmet: SPTAG-KDT (K-dimensionellt tr\u00e4d (kd-tree<\/a><\/noindex>) och graf av relativa grannskap<\/a><\/noindex>) och SPTAG-BKT (k-medeltr\u00e4d (k-means tree<\/a><\/noindex> och grafen av relativa grannskap). Den f\u00f6rsta metoden kr\u00e4ver f\u00e4rre resurser vid arbete med index, medan den andra uppvisar h\u00f6gre noggrannhet i s\u00f6kresultaten vid mycket stora samlingar av vektorer.<\/p>\n

Vektor-s\u00f6kning begr\u00e4nsas inte till text och kan till\u00e4mpas p\u00e5 multimediainformation och bilder, liksom i system f\u00f6r automatisk rekommendationsgenerering. Till exempel, i en av prototyperna baserade p\u00e5 PyTorch-ramverket implementerades ett vektorsystem f\u00f6r s\u00f6kning baserat p\u00e5 objektens likhet i bilder, byggt med data fr\u00e5n flera referenssamlingar med bilder p\u00e5 djur, katter och hundar, som omvandlades till upps\u00e4ttningar av vektorer. N\u00e4r en ing\u00e5ende bild ska s\u00f6kas omvandlas den med hj\u00e4lp av en maskininl\u00e4rningsmodell till en vektor, baserat p\u00e5 vilken algoritmen SPTAG fr\u00e5n indexet v\u00e4ljer de mest liknande vektorerna och resultatet returnerar de relaterade bilderna.<\/p>\n

<\/a><\/noindex><\/p>\n

K\u00e4lla: opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f Microsoft \u043e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043b\u0430 \u0438\u0441\u0445\u043e\u0434\u043d\u044b\u0435 \u0442\u0435\u043a\u0441\u0442\u044b \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f SPTAG (Space Partition Tree And Graph) \u0441 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0435\u0439 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0430 \u043f\u0440\u0438\u0431\u043b\u0438\u0437\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u043f\u043e\u0438\u0441\u043a\u0430 \u0431\u043b\u0438\u0436\u0430\u0439\u0448\u0435\u0433\u043e \u0441\u043e\u0441\u0435\u0434\u0430. \u0411\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0430 \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0430\u043d\u0430 \u0432 \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u0441\u043a\u043e\u043c \u043f\u043e\u0434\u0440\u0430\u0437\u0434\u0435\u043b\u0435\u043d\u0438\u0438 Microsoft Research \u0438 \u0446\u0435\u043d\u0442\u0440\u0435 \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u044b\u0445 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0439 (Microsoft Search Technology Center). \u041d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435 SPTAG \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u0432 \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u043e\u0439 \u0441\u0438\u0441\u0442\u0435\u043c\u0435 Bing \u0434\u043b\u044f \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u044f \u043d\u0430\u0438\u0431\u043e\u043b\u0435\u0435 \u0440\u0435\u043b\u0435\u0432\u0430\u043d\u0442\u043d\u044b\u0445 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u043e\u0432 \u0441 \u0443\u0447\u0451\u0442\u043e\u043c \u043a\u043e\u043d\u0442\u0435\u043a\u0441\u0442\u0430 \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u044b\u0445 \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432. 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