E-commerce product search: personalization, diversification, and beyond

The focus of this tutorial will is e-commerce product search. Several challenges appear in this context, both from a research standpoint as well as an application standpoint. We present various approaches adopted in the industry, review well-known research techniques developed over the last decade, draw parallels to traditional web search highlighting the new challenges in this setting, and dig deep into some of the algorithmic and technical approaches developed. A specific approach that advances theoretical techniques and illustrates practical impact considered here is of identifying most suited results quickly from a large database. Settings span cold start users and advanced users for whom personalization is possible. In this context, top-$k$ and skylines are discussed as they form a key approach that spans the web, data mining, and database communities. These present powerful tools for search across multi-dimensional items with clear preferences within each attribute, like product search as opposed to regular web search.