Information recommending method and information recommending device in social media

Abstract

The present invention provides an information recommendation method and apparatus in social media. The method comprises an offline procedure and an online procedure. The offline procedure comprises: determining a point of interest (POI) of a target user from historical operation information of the target user in social media; selecting, from historical operation information of high-quality users related to the POI in the social media, information related to the POI for use as a labeled corpus; and training an interest classification model of the target user by using the labeled corpus as a training sample. The online procedure comprises: acquiring to-be-recommended information of social media; inputting the to-be-recommended information to the interest classification model of the target user, so as to determine whether the to-be-recommended information conforms to the interest of the target user; and if the to-be-recommended information conforms to the interest of the target user, recommending the to-be-recommended information to the target user. By means of the present invention, the efficiency of information recommendation in social media can be improved.

Description

【Technical field】 [0001] The invention relates to the technical field of computer applications, in particular to an information recommendation method and device in social media. 【Background technique】 [0002] With the continuous development of network technology, the total amount of information on the Internet is expanding at an annual growth rate of 50%. About 80% of the data generated in recent years are generated by individual users, especially by social media. type of website or app. For example, 3 billion pieces of content are shared on Facebook every month, and 12TB of Twitter information is shared every day. Moreover, with the popularity of mobile terminals, this explosive trend has not eased. As of the end of December 2012, Sina Weibo had more than 500 million registered users, 46.29 million daily active users, and 75% of active users Users use mobile clients, and the proportion of active users throughout the year is stable at 9-10%. [0003] However, the other s...

AI Technical Summary

Problems solved by technology

[0004] Because the amount of information in social media is too large, it is impossible to label every piece of information, and the existing recommendation technology is mainly based on the recommendation of information labels, and the timeliness of information in social media is strong, which may cause a lot of confusion to users. Valuable information is seldom forwarded, commented or even read, and the recommendation effect is poor

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