Given endless possibilities to travel around the world, it has become challenging to choose where to travel to. We argue that traditional media is insufficient to make informed decisions where to travel to, because of lacking objectivity, comparability and being out-of-date. Thus, travel planning is an interesting field to establish data-driven recommender systems that support users to master information explosion. We present working packages for a doctorate project that brings together the fields of recommender systems and user modeling with data mining. The core contributions will be a framework for the integration of heterogeneous data sources from the travel domain, novel user modeling techniques and constraint-based recommender algorithms to master the complexities of travel.     «

Given endless possibilities to travel around the world, it has become challenging to choose where to travel to. We argue that traditional media is insufficient to make informed decisions where to travel to, because of lacking objectivity, comparability and being out-of-date. Thus, travel planning is an interesting field to establish data-driven recommender systems that support users to master information explosion. We present working packages for a doctorate project that brings together the fiel...     »