Field-oriented personalized intelligent recommendation system and implementation method

Abstract

The invention discloses a field-oriented personalized intelligent recommendation system and an implementation method. Aiming at the defect of poor universality of the traditional recommendation manner, a reasonable data organization mode is adopted, so that the recommendation service has a cross-field property, and field conversion can be realized by configuring field information according to the characteristics of different fields; aiming at the problem of data sparseness caused by single user information acquisition source and low quantity in the traditional recommendation manner, a context perception technology for actively acquiring context information of interactive behaviors of a user and the system is introduced, so that the quantity of the acquired user information is greatly increased, and the time distribution of the acquired user information is more reasonable; the acquisition of the user information is directly related with the interactive behaviors of the user and the system; the system can acquire the current condition of the user in real time, so that the recommendation service can dynamically reflect the change condition of user demand; and the recommendation service quality is improved through a recommendation learning model by continuously using the reflection of the user on the recommendation result.

Description

technical field [0001] The invention relates to computer information processing and network communication technologies, in particular to a field-oriented personalized intelligent recommendation system and its implementation method. Background technique [0002] With the development of information technology, especially network technology, the scale of information system is getting bigger and bigger, the amount of information is also increasing, the tools and methods of obtaining information are becoming more and more abundant, and more and more information is provided to users through the network. At the same time, the structure and content of information systems are becoming more and more complex. In the massive amount of information, it becomes more difficult to provide users with the information they need in a timely and accurate manner. The main reasons are as follows: First, because it is difficult to accurately describe the characteristics of the required information,...

AI Technical Summary

Problems solved by technology

Although the existing hybrid recommendation methods improve the quality of recommendation service within a certain range, they still cannot solve cross-domain problems and cannot improve the quality of recommendation service for loyal users.

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