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How to combine human-labelled data with user behavior data?

Data Science Asked by SHASHANK GUPTA on December 22, 2020

I am working on a supervised learning problem for a web-search task, where I have access to a relatively small set of human-labeled examples and lots of user-behavior data.

Now, user behavior data is biased, because of presentation bias, position bias etc. So it’s likely that its’ distribution will be different from human-labeled data.

I am planning to use both to train a Neural Network model.

Now I am confused about how to combine both datasets?

One Answer

That is a common scenario in a learning to rank problem. One heuristic is to separately model explicit (human-labeled) and implicit (user-behavior) features. Then combine the separate feature groups with a learned weight for their final relative contribution. Improving Web Search Ranking by Incorporating User Behavior Information by Agichtein et al goes into greater detail.

RankNet takes this approach using a neural network.

Answered by Brian Spiering on December 22, 2020

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