Method and system for constructing social behavior sequence diagram, mobile terminal and readable storage medium

Abstract

The invention discloses a method for constructing a social behavior sequence diagram. The method comprises the following steps: acquiring a social behavior record set; converting each social behavior record in the social behavior record set into a sequence record in a standard text format; inputting the sequence records into a pre-constructed causal relationship judgment model, and calculating the probability that all other sequence records of which the occurrence time is earlier than that of one sequence record and the sequence record are causal relationships through the causal relationship judgment model to obtain the probability that the sequence records are causal relationships; constructing a node for each social behavior of each person in the social behavior record set, and obtaining the probability of a causal relationship between the nodes; and according to the probability of the causal relationship between the nodes, constructing the social sequence graph. A complete social behavior sequence which is carried out among a plurality of people, contains a plurality of themes and has a clear causal relationship between sentences or behaviors can be extracted, and the use scene is expanded.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method for constructing a social behavior sequence diagram, a mobile terminal and a readable storage medium. Background technique [0002] People's daily communication is increasingly dependent on social chat software, such as WeChat, QQ, etc. At present, the extraction of social behavior sequences based on WeChat, QQ, etc. is usually based on the dialogue records between two people, and only for continuous dialogue segments based on topic word pairs Text clustering, that is, the conversation between two people is divided into several segments in time, and each segment contains one or several topics, but it cannot handle some of the following situations, resulting in limited usage scenarios: [0003] 1. A dialogue among several persons; [0004] 2. Dialogue on multiple topics; [0005] 3. Interval dialogues on a certain topic (that is, interspersed with different topi...

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Problems solved by technology

[0002] People's daily communication is increasingly dependent on social chat software, such as WeChat, QQ, etc. At present, the extraction of social behavior sequences based on WeChat, QQ, etc. is usually based on the dialogue records between two people, and only for continuous dialogue segments based on topic word pairs Text clustering, that is, the conversation between two people is divided into several segments in time, and each segment contains one or several topics, but it cannot handle some of the following situations, resulting in limited usage scenarios:

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