Method for mining customer style preferences through IM chat content analysis
A technology of chat content and style, applied in instruments, probabilistic networks, computing models, etc., can solve problems such as affecting delivery quality and user experience, inability to deeply understand user preferences, and inability to accurately convey requirements, reducing follow-up communication time. , convenient introduction and recommendation, the effect of reducing the time to choose a style
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Embodiment 1
[0030] 1) Query the customer's historical orders and classify the orders into each style;
[0031] 2) Sorting customer IM chat information, separating vocabulary through word segmentation tools, sorting, merging, listing the frequency of keywords in it, sorting according to frequency, and taking out keywords with higher frequency of occurrence as statistical dimensions;
[0032] 3) Count the number of occurrences of keywords obtained in the previous step in each order.
[0033] Table 1 is sorted out as follows:
[0034]
[0035]
[0036] Table 1 takes 4 keywords as an example. In practical applications, the more keywords, the greater the reference value of the final results.
[0037] The process of calculating the probability in this embodiment is as follows:
[0038] Suppose, at this time, in the user's chat history, two keywords "wooden" and "smart" appear; by the above formula:
[0039] max(P)=max(P(A1|S)P(A2|S)...P(An|S)P(S))
[0040] The relative possibility can...
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