Service-aware Recommendation and Justification of Results
Zhongli Filippo Hu · 2022
The opinions of people who previously experienced items are crucial to decision-making. My Ph.D. research project is focused on finding a better way to recommend experience goods and in particular services such as apartments and tourism experiences by exploiting a description of the service underlying item fruition, such as Service Journey Maps or Blueprint. Regarding the recommender system, I propose an extension of a Top-N algorithm that takes into account service-based dimensions. For the presentation of the results, I plan to develop an incremental view that holistically summarizes the items, showing quantitative data in bar graphs and qualitative data extracted from previous consumer feedback. As a testbed for the research, I exploited the home-booking domain, using publicly available data from Airbnb.