Personalized active news recommending service system and method for mobile phone user

Abstract

The invention discloses a personalized active news recommending service system for a mobile phone user, which comprises an interest acquisition module, a position acquisition module, an interest model updating module and an active recommending service processing module, wherein the interest acquisition module is used for determining the preference of the user to the news; the position acquisition module is used for determining the current location of the user according to positioned information of the mobile terminal of the user; the interest model updating module is used for updating the current news preference of the user; and the active recommending service processing module is used for recommending news for the user according to set algorithm. The invention also discloses a personalized active news recommending service method for the mobile phone user. According to the invention, news information which is more suitable for the needs of the user can be recommended to the user, so that a personalized news recommending service is truly realized, and the user can obtain the news contents in which the user is most interested without turning web pages frequently.

Description

technical field [0001] The invention relates to a mobile user personalized news active recommendation service system and method for mobile phones. Background technique [0002] In recent years, the development of information technology and network technology has been quite rapid, especially the rapid development of wireless network communication technology and Internet (Internet) technology, which has revolutionized the way of communication and information dissemination between people, and has provided great support for people's lives, Work and scientific research bring great convenience. At present, the Internet has become a huge treasure house of knowledge and an ocean of information, and the exponential growth of information has also led to "information overload" and "information obsession". Currently, mobile networks use the Internet as an information source to provide mobile users with various information more conveniently. Among them, news information is a kind of in...

AI Technical Summary

Problems solved by technology

As far as the region is concerned, the information recommendation service can only determine the approximate area of ​​the user. For example, the current access port belongs to a certain province or city, etc., and cannot further determine the current specific location of the user. In addition, only Based on location information, it is also difficult to screen out personalized information suitable for users from massive amounts of information

Moreover, when the recommendation service is for mobile users, the situation will be much more complicated. First, the user may be constantly moving. When the user is at the current location, he may be interested in information related to the current location, such as the traffic conditions at the current location. , whether there are traffic control measures at the current location, whether there are major news events in the area where the current location is located; of course, this is only a region-related information recommendation service; since it is ultimately aimed at specific users, it is necessary to understand the user's perception of relevant information The degree of attention, determine the interest preferences among different users, the user's occupation, the user's education level, the user's identity and its changes, etc.

Therefore, the personalized recommendation service, especially the personalized recommendation service based on mobile users, currently faces quite a lot of problems, which is also the key factor that the technology has not yet been oriented to users.

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