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Personalized Info display on Social Media

IP.com Disclosure Number: IPCOM000248291D
Publication Date: 2016-Nov-15
Document File: 5 page(s) / 44K

Publishing Venue

The IP.com Prior Art Database

Abstract

The discoluse describes method how display the news by personalized designed on social media, which includs two implementation models. The first one is obaining the users' behavior by meaching learning process. The second one is users mark the important friends and interesting offical accounts by themselves. As a result, the messages come from these two implementation model will be showed firstly on users' social media page. In this way, users won't be flooded in less valuable content and miss the news they really care. It can improve the users' reading quality on social media in a limited time.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 52% of the total text.

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Personalized Info display on Social Media

Social media has been enjoying a great deal of success in recent years. Millions of users browse news and communicate with others through the social media. These social media sites rely principally on their users to create and contribute content.

As the content on these social media sites keep growth, users become having more difficulty to get the info they really need recently. Furthermore, users may be flooded with the information from normal friends, advertise. Among the info, there are some content user have less interest recently. In this kind situation, user always miss the info they really care or the update from the important people.

One way site address the issue is by providing users with personalized ranking info on social media. The social media show the content to user in the order of the ranking list provided by users themselves or machine learning result according to users' behavior.

The disclosure provide a solution that users can define the information order on social media. The messages in social circle can be displayed by the order come from users' daily behavior machine learning result.

What's more, user can rank the people they care more and choose the subscription topic they are interested in recently. When the user open the social media, the info they select before or they usually read will be showed to user firstly.

The solution make sure that the users will not miss the update from friends who they really care. And they can read the valuable information in a limited time. If users have enough leisure time, they can go on browse other less important content.

Displaying personalize info on social media can be implemented by following methods.

Method 1: For display messages by machine learning result.

The message showed by the order of the machine learning result should be determined by the following factors:
1)The frequency of the interaction with friends, which include clicking a like, leave message and private communication.
2)The standing time when users browse a official accounts news.

3)Click action ever happen when users browse the messages from friends or official accounts.

The three factors above will be assigned difference weight to determine the ranking result.

In test stage, the factors should be assigned a initial weight, some users also should been involved to the test stage.

According to feedback from users, the factors will be adjust iteratively.

After that the tree factors can be assigned final weight value.

Method 2: For user's define the messages display rank.

First of all, some tabs need to be added to the friends ID card in social media. For example figure 1.

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1)In friends ID card and official accounts, add a tab. In the tab, you can set a prope...