Abstract: A poor-QoE assessment method and a related device are provided. The method includes: obtaining m data streams transmitted by a network device; screening the m data streams, and determining that p data streams in the m data streams and that meet a first preset condition are data streams corresponding to a first type; performing feature extraction on the data streams corresponding to the first type, to obtain known feature vectors corresponding to the first type; training, by using the known feature vectors corresponding to the first type, an untrained first poor-QoE assessment model, to obtain a trained first poor-QoE assessment model; and performing, by using the trained first poor-QoE assessment model, poor-QoE assessment on n data streams corresponding to the first type, to obtain a first poor-QoE assessment result. This method can be universally used instead of an application.

Abstract: A poor-QoE assessment method and a related device are provided. The method includes: obtaining m data streams transmitted by a network device; screening the m data streams, and determining that p data streams in the m data streams and that meet a first preset condition are data streams corresponding to a first type; performing feature extraction on the data streams corresponding to the first type, to obtain known feature vectors corresponding to the first type; training, by using the known feature vectors corresponding to the first type, an untrained first poor-QoE assessment model, to obtain a trained first poor-QoE assessment model; and performing, by using the trained first poor-QoE assessment model, poor-QoE assessment on n data streams corresponding to the first type, to obtain a first poor-QoE assessment result. This method can be universally used instead of an application.