Behavioural Targeting in online advertising using web surf history analysis and contextual segmentation

摘要

The online advertisement publishing industry is a rapidly growing multi-billion dollar industry. Organisations in this industry generate revenue by creating and/or acquiring online advertising space that they can sell at a profit. Their success is directly dependent on the effectiveness of their publishing strategy in terms of its ability to create traffic and interest for their clients by delivering advertisements which are closely in line with the recipient's interests. We propose a supervised learning based ad targeting technique which will help online advertisement publishers achieve this goal. Empirical tests of the new technique are very promising.