Unknown intention recognition method and device, equipment and storage medium
The invention discloses an unknown intention recognition method and device, equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining an intention unknown sample when an intention recognition model is called to fail in...
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| creator | BAO MENGJIAO |
| description | The invention discloses an unknown intention recognition method and device, equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining an intention unknown sample when an intention recognition model is called to fail in intention recognition of a to-be-recognized sample; performing anomaly detection on the semantic representation vector of the intention unknown sample to obtain a local outlier factor density in the sample; in response to the fact that the density is larger than a density threshold value, determining that an unknown intention exists in an intention unknown sample, and the intention unknown sample being used for training the intention recognition model again after a new intention is manually marked. According to the method, an intention unknown sample is confirmed again through anomaly detection of a local outlier factor, and a sample in which an unknown intention really exists is screened out, so that extension tra |
| format | Patent |
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The method comprises the steps of obtaining an intention unknown sample when an intention recognition model is called to fail in intention recognition of a to-be-recognized sample; performing anomaly detection on the semantic representation vector of the intention unknown sample to obtain a local outlier factor density in the sample; in response to the fact that the density is larger than a density threshold value, determining that an unknown intention exists in an intention unknown sample, and the intention unknown sample being used for training the intention recognition model again after a new intention is manually marked. 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The method comprises the steps of obtaining an intention unknown sample when an intention recognition model is called to fail in intention recognition of a to-be-recognized sample; performing anomaly detection on the semantic representation vector of the intention unknown sample to obtain a local outlier factor density in the sample; in response to the fact that the density is larger than a density threshold value, determining that an unknown intention exists in an intention unknown sample, and the intention unknown sample being used for training the intention recognition model again after a new intention is manually marked. According to the method, an intention unknown sample is confirmed again through anomaly detection of a local outlier factor, and a sample in which an unknown intention really exists is screened out, so that extension tra</abstract><oa>free_for_read</oa></addata></record> |
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| language | chi ; eng |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
| title | Unknown intention recognition method and device, equipment and storage medium |
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