On-line activity identification method and system based on Markov logic network

Abstract

The invention discloses an on-line activity identification method and system based on the Markov logic network. The method includes the steps of acquiring all operation behaviors and storing the operation behaviors in a database to obtain behavior data, processing the behavior data and identifying corresponding activity results according to the behavior data to obtain activity data, and processing the identified activity data and displaying the activity data in a visible way. The system comprises a data acquisition unit, an identification processing unit and a data displaying unit. User activities can be automatically identified from activity logs by establishing an activity identification model, and the expandability is good. Adding logic rules by users is allowed, and strong association rules are mined out from a training sample set by using a rule mining algorithm and serve as logic rules. Uncertainty of corresponding relation between action and on-line activities can be overcome, and the identification accuracy is improved. The method and system can be widely applicable in the computer field.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an online activity recognition method and system based on a Markov logic network. Background technique [0002] With the rapid development of the mobile Internet, smart devices such as smartphones and smart watches are becoming more and more popular, and more and more human activities are happening online. The recorded situation of the user's interaction with the online system is recorded. How to identify the behind-the-scenes activities from the action data recorded by the user's online system is of great help to improve the click-through rate of the website and provide personalized services, especially in the research fields of smart home, medical monitoring, and e-commerce. [0003] The purpose of activity recognition is to analyze the user action records recorded by the computer, so as to identify the current activities of the user. An action record reflects a user's oper...

AI Technical Summary

Problems solved by technology

[0008] However, the existing methods cannot solve the above problems well.

The logic-based method relies on definite logic rules for reasoning, which cannot solve the uncertainty of the corresponding relationship between actions and online activities well, and also cannot solve the problem of total noise in the data well.

The method based on probabilistic reasoning requires a large number of training samples, which are often difficult to obtain in practice, and cannot use the domain background knowledge of activity recognition.

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