Estimation of the Click Volume by Large Scale Regression Analysis.

Lifshits, Yury and Nowotka, Dirk (2007) Estimation of the Click Volume by Large Scale Regression Analysis. [Paper] In: Computer Science Russia (CSR). , 3 - 7 Sep 2007, Ekaterinburg, Russia . Computer Science – Theory and Applications. ; pp. 216-226 . DOI 10.1007/978-3-540-74510-5_23. Lecture Notes in Computer Science .

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Abstract

How could one estimate the total number of clicks a new advertisement could potentially receive in the current market? This question, called the click volume estimation problem is investigated in this paper. This constitutes a new research direction for advertising engines. We propose a model of computing an estimation of the click volume. A key component of our solution is the application of linear regression to a large (but sparse) data set. We propose an iterative method in order to achieve a fast approximation of the solution. We prove that our algorithm always converges to optimal parameters of linear regression. To the best of our knowledge, it is the first time when linear regression is considered in such a large scale context.

Document Type: Conference or Workshop Item (Paper)
Keywords: click volume click-through rate sponsored search advertising engines direct response marketing cost per click conversion rate click rate learning
Research affiliation: Kiel University
Publisher: Springer
Date Deposited: 15 Feb 2013 21:31
Last Modified: 23 Sep 2019 19:39
URI: https://oceanrep.geomar.de/id/eprint/20532

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