Personalized Search - Building a prototype to infer the user's interest

In the world of Search, understanding the intend of the user is often seen as the holy grail. When a user performs multiple search and click actions while having a conversation with the search engine, then this behavior reveals a piece of her/his interest. A search engine that is aware of the user’s interest is able to add a personal layer in its responses and this could add a new dimension of accuracy and value to a search implementation. But what technology does it take to build it? What data is needed? How well does it really work? This presentation describes the journey to find a practical implementation of a recommendation engine. It answers all the questions above and more. We’ll guide you through the lessons learned while creating an engine that generates potentially interesting items for the user based on collaborative filtering and anomaly detection. We’ll demonstrate a prototype where even a minimal set of user actions could lead to a personalized search experience.

Tom Burgmans

Wolters Kluwer

Tom is the Technology Product Owner Search at Wolters Kluwer where he leads the Search Center of Excellence team. Search has been the main theme through the last 18 years of Tom’s career, as webmaster (SEO techniques), as a post sales consultant for Autonomy (enterprise search implementations) and as a search engineer for Wolters Kluwer (optimizing search quality). In his current role as Product Owner Tom oversees the development and adoption of the Search Service that powers various large online research products.