Ad Click Prediction for the Web Mapping Service

Student: Denisova Alina

Supervisor: Stanislav N. Fedotov

Educational Programme: Data Science (Master)

Year of Graduation: 2019

Map services are one of the most popular Internet services. This attracts the owners of organizations to buy advertise on the maps for thematic requests. Priority placement allows the advertising organization to rise above the rest in the list of issue on request and be more visible on the geographic map with the answers. One of the key characteristics of any advertising platform is its effectiveness for the advertiser. In this work was developed the model for predicting the effect that organisation will have after the purchase advertising. For this was determine a metric of the priority allocation effect, was collect a dataset on user actions, and was built a prediction model with using CatBoost. In contrast to the task of predicting the CTR of advertisements in a search engine, in addition to the list issuance, we have search results on the map. Research and development of geospatial attributes for an organization has become an important part of improving the model. To test the quality of the model, an A / B experiment design was developed and launched on real users.

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