Text recognition model training method and device, text recognition method and device and medium
The embodiment of the invention discloses a text recognition model training method, a text recognition method, a text recognition device and a medium. The text recognition model training method comprises the steps of obtaining to-be-processed short text training data; generating a text vector sequen...
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| creator | WANG JIE FU QIANG WU JINXIN ZHOU XIAOMING HOU LIDONG PAN SHENLING TIAN YE YANG MANZHI MENG BAOQUAN LIANG YU JIN HONG HUANG ZHI CAI LIN CHEN XIAOGUANG DENG QIAOBO LI LINHAN |
| description | The embodiment of the invention discloses a text recognition model training method, a text recognition method, a text recognition device and a medium. The text recognition model training method comprises the steps of obtaining to-be-processed short text training data; generating a text vector sequence according to the to-be-processed short text training data; performing sequence feature extraction processing on the text vector sequence to obtain a sequence feature extraction result, and determining the sequence feature extraction result as a short text classification result, wherein the short text classification result comprises a first short text classification label and a first label probability; performing entity feature extraction processing on the sequence feature extraction result to obtain an entity feature extraction result; and training a text recognition model according to a sequence feature extraction result and an entity feature extraction result. According to the technical scheme provided by the |
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The text recognition model training method comprises the steps of obtaining to-be-processed short text training data; generating a text vector sequence according to the to-be-processed short text training data; performing sequence feature extraction processing on the text vector sequence to obtain a sequence feature extraction result, and determining the sequence feature extraction result as a short text classification result, wherein the short text classification result comprises a first short text classification label and a first label probability; performing entity feature extraction processing on the sequence feature extraction result to obtain an entity feature extraction result; and training a text recognition model according to a sequence feature extraction result and an entity feature extraction result. According to the technical scheme provided by the</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; HANDLING RECORD CARRIERS ; PHYSICS ; PRESENTATION OF DATA ; RECOGNITION OF DATA ; RECORD CARRIERS</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211008&DB=EPODOC&CC=CN&NR=113486178A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211008&DB=EPODOC&CC=CN&NR=113486178A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WANG JIE</creatorcontrib><creatorcontrib>FU QIANG</creatorcontrib><creatorcontrib>WU JINXIN</creatorcontrib><creatorcontrib>ZHOU XIAOMING</creatorcontrib><creatorcontrib>HOU LIDONG</creatorcontrib><creatorcontrib>PAN SHENLING</creatorcontrib><creatorcontrib>TIAN YE</creatorcontrib><creatorcontrib>YANG MANZHI</creatorcontrib><creatorcontrib>MENG BAOQUAN</creatorcontrib><creatorcontrib>LIANG YU</creatorcontrib><creatorcontrib>JIN HONG</creatorcontrib><creatorcontrib>HUANG ZHI</creatorcontrib><creatorcontrib>CAI LIN</creatorcontrib><creatorcontrib>CHEN XIAOGUANG</creatorcontrib><creatorcontrib>DENG QIAOBO</creatorcontrib><creatorcontrib>LI LINHAN</creatorcontrib><title>Text recognition model training method and device, text recognition method and device and medium</title><description>The embodiment of the invention discloses a text recognition model training method, a text recognition method, a text recognition device and a medium. The text recognition model training method comprises the steps of obtaining to-be-processed short text training data; generating a text vector sequence according to the to-be-processed short text training data; performing sequence feature extraction processing on the text vector sequence to obtain a sequence feature extraction result, and determining the sequence feature extraction result as a short text classification result, wherein the short text classification result comprises a first short text classification label and a first label probability; performing entity feature extraction processing on the sequence feature extraction result to obtain an entity feature extraction result; and training a text recognition model according to a sequence feature extraction result and an entity feature extraction result. 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The text recognition model training method comprises the steps of obtaining to-be-processed short text training data; generating a text vector sequence according to the to-be-processed short text training data; performing sequence feature extraction processing on the text vector sequence to obtain a sequence feature extraction result, and determining the sequence feature extraction result as a short text classification result, wherein the short text classification result comprises a first short text classification label and a first label probability; performing entity feature extraction processing on the sequence feature extraction result to obtain an entity feature extraction result; and training a text recognition model according to a sequence feature extraction result and an entity feature extraction result. According to the technical scheme provided by the</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
| title | Text recognition model training method and device, text recognition method and device and medium |
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