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Video Content-Based Advertisement Recommendation Using Text Classification

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# Advertisement-Recommendation
Video Content-Based Advertisement Recommendation Using Text Classification & Video Classification 
[Click here for implementation guide](https://medium.com/analytics-vidhya/video-content-based-advertisement-recommendation-using-nlp-4512430c169e)

Content-based advertising is a method by which we advertise on a video media based 
on a relevant topic assigned to the video. In digital advertising, the advertisements shown to a
user is based on the user’s behaviour on the internet. Streaming platforms are then used to
target audience based on parameters like user’s geo-location, interests, watch history, age, etc.
In most cases, the advertisements shown are not relevant; an undesired impact is created.
Content-based advertising helps to convey the message with increased efficiency and
simultaneously optimizes its conversion rate. In this proposed system we take the video
metadata as input and apply the NLP techniques for text classification which categories the
video and assigns a relevant advertisement to it. The second module takes the video as an
input. Thereafter the video is converted into N individual frames to tackle the video
classification as an image classification problem. In this proposed system we train a
Convolutional Neural Network to identify the topic of the video on an image dataset and
compare its performance with a pre-trained model. We create the image dataset by
downloading images from the internet. We also create a video advertisement's dataset by web
scrapping. This proposed system makes sure that the user is shown the advertisement in
reference to the video. This increases probability of the user visiting the client's website.

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