Chatting robot knowledge base and construction method thereof
A chat robot and construction method technology, applied in the field of automatic chat robot knowledge base and its construction, can solve the problems of unable to chat person personalized reply, not recording chat person attribute information, not recording chat discourse context information, etc.
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Embodiment 1
[0036] This embodiment relates to an online video social platform, which is divided into several channels according to social content, and each channel has multiple video chat rooms. Tourists and VIP members can interact with the host in the room. One of the important communication methods is text chat. During the service peak period, the room host can interact and chat with users in person, but during the service peak period, there are too many users in the room, and the room host cannot interact with each user, which seriously affects the user experience. Therefore, it is necessary to develop a chatbot that can simulate the moderator's work to relieve the moderator's work pressure, and a key problem in developing a chatbot is to build a chat knowledge base. First, the text chat records of room hosts and users on the platform are extracted as artificial chat data. The time span is 1 month, and there are more than 30 million chat words in total. Due to system reasons, the art...
example
[0040] [The platform customer logs into the system, the system queries the chat person attribute database to obtain the user's attribute information, the gender is "male", the region is "Zhejiang", and the chat keyword includes "singing"]
[0041] Here is the chat process:
[0042] 1) Chatbot: Brother fellow, we meet again~ [Greeting, the restriction of this greeting is "gender = male", the current user meets the restriction]
[0043] 2) Platform users: yes
[0044] 3) Chatbot: I’m afraid I won’t be able to see you [the user’s words above are only the word “yes”, the amount of information is too small, query the chat discourse database, and determine the most appropriate reply through contextual information matching]
[0045] 4) Platform users: just went out for a while
[0046] 5) Chatbot: Oh, I thought you were asleep [According to the user's words and contextual information, query the chat discourse database to determine the reply words]
[0047] 6) Platform users: beaut...
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Abstract
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