Session information processing method and device and storage medium

A computing device comprising one or more processors, memory coupled to the one or more processors and a plurality of programs stored in the memory that, when executed by the one or more processors, cause the computing device to perform a plurality of operations comprising:

• extracting a to-be-analyzed sentence and a preset quantity of preceding sentences of the to-be-analyzed sentence from a session;
• performing word segmentation on the to-be-analyzed sentence and the preset quantity of preceding sentences, to obtain a first feature set comprising a plurality of first features;
• extracting a second feature set comprising one or more second features from a first word set corresponding to the to-be-analyzed sentence and a second word set corresponding to the preset quantity of preceding sentences, one second feature comprising a phrase or sentence comprising a first word and a second word, the first word being one or more words in the first word set, and the second word being one or more words in the second word set;
• and
• determining, according to the first feature set and the second feature set, a sentence category to which the to-be-analyzed sentence belongs, the sentence category comprising a first category indicating that a sentence is complete, and semantics is unambiguous and a second category indicating that a sentences is incomplete, or semantics is ambiguous.

A non-transitory computer readable storage medium storing a plurality of machine readable instructions in connection with a computing device having one or more processors, wherein the plurality of machine readable instructions, when executed by the one or more processors, cause the computing device to perform a plurality of operations including:

• extracting a to-be-analyzed sentence and a preset quantity of preceding sentences of the to-be-analyzed sentence from a session;
• performing word segmentation on the to-be-analyzed sentence and the preset quantity of preceding sentences, to obtain a first feature set comprising a plurality of first features;
• extracting a second feature set comprising one or more second features from a first word set corresponding to the to-be-analyzed sentence and a second word set corresponding to the preset quantity of preceding sentences, one second feature comprising a phrase or sentence comprising a first word and a second word, the first word being one or more words in the first word set, and the second word being one or more words in the second word set;
• and
• determining, according to the first feature set and the second feature set, a sentence category to which the to-be-analyzed sentence belongs, the sentence category comprising a first category indicating that a sentence is complete, and semantics is unambiguous and a second category indicating that a sentences is incomplete, or semantics is ambiguous.