Google llc (20240107125). SYSTEM AND METHOD FOR MODELLING ACCESS REQUESTS TO MULTI-CHANNEL CONTENT SHARING PLATFORMS simplified abstract

SYSTEM AND METHOD FOR MODELLING ACCESS REQUESTS TO MULTI-CHANNEL CONTENT SHARING PLATFORMS

Organization Name

google llc

Inventor(s)

Brian James Mulford of Rolling Hills Estates CA (US)

T.J. Gaffney of Mountain View CA (US)

Michael John De Ridder of Sunnyvale CA (US)

Colby D. Ranger of Palo Alto CA (US)

SYSTEM AND METHOD FOR MODELLING ACCESS REQUESTS TO MULTI-CHANNEL CONTENT SHARING PLATFORMS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240107125 titled 'SYSTEM AND METHOD FOR MODELLING ACCESS REQUESTS TO MULTI-CHANNEL CONTENT SHARING PLATFORMS

Simplified Explanation

The patent application describes a system and method for predicting the number of access requests that a future video posted via a channel is expected to receive based on past video data.

• The system identifies past videos posted via a first group of channels.
• It determines the average number of access requests that a future video posted via a channel of a second group is predicted to receive within a specific time interval.
• An adjustment factor is applied to adjust the predicted number of access requests based on the performance of past videos posted via the respective channel.
• The system then evaluates whether the second group of channels meets a predetermined access criterion.

Potential Applications

This technology could be applied in video content creation platforms to help creators optimize their posting schedule and channel selection based on predicted viewer engagement.

Problems Solved

This technology solves the problem of uncertainty in predicting the performance of future video content, allowing creators to make more informed decisions on content distribution.

Benefits

The system provides creators with valuable insights into the expected performance of their videos, helping them maximize viewer engagement and reach a wider audience.

Potential Commercial Applications

This technology could be valuable for video hosting platforms, marketing agencies, and content creators looking to improve the effectiveness of their video content strategies.

Possible Prior Art

One possible prior art could be algorithms used in recommendation systems for predicting user preferences based on past behavior data.

=== What are the limitations of this technology in predicting video performance accurately? The accuracy of the predictions may be affected by external factors such as changes in viewer behavior or trends in the online video landscape.

=== How can this technology be further optimized to provide more precise predictions? Further optimization could involve incorporating real-time data analysis and machine learning algorithms to continuously improve the prediction models based on evolving viewer preferences and behaviors.

Original Abstract Submitted

a system and method are disclosed for identifying a plurality of past videos posted via a first group of channels, determining, for each channel of a second group, an average number of access requests that a future video to be posted via a respective channel is predicted to receive within a first time interval after posting, determining, for each channel of the second group, a plurality of adjusted average numbers of access requests that the future video to be posted via the respective channel of the second group is predicted to receive within the first time interval, wherein each of the plurality of adjusted average numbers of access requests is determined using an adjustment factor reflecting a number of access requests received by a past video posted via a respective channel of the first group, and determining whether the second group of channels satisfies a predetermined access criterion.