Exploiting web scraping in a collaborative filtering- based approach to web advertising

Abstract

Web scraping is the set of techniques used to automatically get some information from a website instead of manually copying it. The goal of a Web scraper is to look for certain kinds of information, extract, and aggregate it into new Web pages. In particular, scrapers are focused on transforming unstructured data and save them in structured databases. In this paper, among others kind of scraping, we focus on those techniques that extract the content of a Web page. In particular, we adopt scraping techniques in the Web advertising field. To this end, we propose a collaborative filtering-based Web advertising system aimed at finding the most relevant ads for a generic Web page by exploiting Web scraping. To illustrate how the system works in practice, a case study is presented.