{"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\/et\/blog\/news\/microsoft-otkryl-kod-biblioteki-vektornogo-poiska-ispolzuemoj-v-bing","title":{"rendered":"Microsoft avas Bingis kasutatava vektorotsingu raamatukogu koodi.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Microsoft avalikustas<\/a><\/noindex> masin\u00f5ppe raamatukogu algdokumendid SPTAG<\/a><\/noindex> (Space Partition Tree And Graph) koos ligikaudse naaberotsingu algoritmi rakendusega<\/a><\/noindex>. Raamatukogu on v\u00e4lja t\u00f6\u00f6tatud<\/a><\/noindex> Microsoft Researchi uurimisosakonnas ja Microsofti Otsingutehnoloogia Keskuses. Praktikas kasutatakse SPTAG-i Bing\u2019i otsingumootoris, et m\u00e4\u00e4rata konteksti p\u00f5hjal k\u00f5ige asjakohasemad tulemused. Kood on kirjutatud C++ keeles ja levitatakse<\/a><\/noindex> t\u00f6\u00f6tatakse MIT litsentsi all. Toetatud on Linuxi ja Windowsi versioon.<\/p>\n

Kuigi idee vektoriteiriumide rakendamisest otsingus\u00fcsteemides on juba ammu olemas, takistavad nende kasutuselev\u00f5ttu suured ressursisoovitused vektorite operatsioonide ja skaleeritavuse piirangud. S\u00fcvamasin\u00f5ppe meetodite ja ligikaudse naaberotsingu algoritmide \u00fchendamine on v\u00f5imaldanud viia vektors\u00fcsteemide j\u00f5udluse ja skaleeritavuse tasemeni, mis on vastuv\u00f5etav suurtele otsingus\u00fcsteemidele. N\u00e4iteks Bing\u2019is, kus on vektorindeks, mille suurus on \u00fcle 150 miljardi vektori, kulub k\u00f5ige asjakohasemate tulemuste saamiseks alla 8 ms.<\/p>\n

Raamatukogu sisaldab vahendeid indeksite koostamiseks ja vektorite otsingu korraldamiseks, samuti kogumit t\u00f6\u00f6riistu jaotatud online-otsingus\u00fcsteemi toetamiseks, mis katab v\u00e4ga suuri vektorkogusid. Pakutakse<\/a><\/noindex> j\u00e4rgnevaid mooduleid: indeksiehitaja indekseerimiseks, otsija indeksi alusel otsimiseks, jaotatud klastris mitme s\u00f5lme vahel, server t\u00f6\u00f6tluse k\u00e4ivitamiseks s\u00f5lmedes, Aggregator mitme serveri \u00fchendamiseks \u00fcheks ja klient p\u00e4ringute edastamiseks. Uute vektorite lisamine indekssi ja vektorite eemaldamine toimub jooksvalt.<\/p>\n

Raamatukogu eeldab, et t\u00f6\u00f6deldud ja kogude esitatud andmed on esitatud seotud vektoritena, mida saab v\u00f5rrelda euclidean<\/a><\/noindex> (L2) v\u00f5i kosinus<\/a><\/noindex> vahemaa alusel. Otsingu p\u00e4ringu korral tagastatakse vektoreid, mille vahemaa algvektoriga on minimaalne. SPTAG-is on kaks meetodit vektoriruumi korraldamiseks: SPTAG-KDT (K-dimensionaalne puu (kd-tree<\/a><\/noindex>) ja suhete naabruskonna graaf<\/a><\/noindex>) ja SPTAG-BKT (k-meetodite puu (k-means tree<\/a><\/noindex> ja suhteline naabruskond). Esimene meetod n\u00f5uab indeksi t\u00f6\u00f6ks v\u00e4hem ressursse, teine aga n\u00e4itab v\u00e4ga suurte vektorikogumite puhul k\u00f5rgemat otsingutulemustele t\u00e4psust.<\/p>\n

Samas ei piirdu vektoriline otsing tekstiga, vaid seda saab rakendada ka multimeedia teabele ja piltidele ning automaatse soovituss\u00fcsteemide jaoks. N\u00e4iteks, \u00fches protot\u00fc\u00fcbis, mis p\u00f5hineb PyTorchi raamistikul, on rakendatud vektoriline s\u00fcsteem objektide sarnasuse p\u00f5hjal piltide otsinguks, mis on \u00fcles ehitatud mitmest standardkogumist loomade, kasside ja koerte piltidelt, mis on muudetud vektoriteks. Kui sisendpilt saadetakse otsingu jaoks, muudetakse see masin\u00f5ppe mudeli abil vektoriks, mille alusel valitakse SPTAG algoritmi abil indeksist k\u00f5ige sarnasemad vektorid ja tulemusena tagastatakse nendega seotud pildid.<\/p>\n

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

Allikas: 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. […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-33865","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47Microsoft avas Bingis kasutatava vektorilise otsingu raamatukogu koodi | ProHoster","description":"Microsoft avaldas masin\u00f5ppe raamatukogu 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